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2013 2nd IEEE International Conference on Teaching, Assessment and Learning for Engineering, TALE 2013

作者： Diana Suharjito Information Technology Department School of Computer Science Bina Nusantara University Jakarta Indonesia Information Technology Program Bina Nusantara Graduate Program Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9781467363556

The use of IT applications in teaching and learning had changed the way students learn using e-learning which was more modern, effective and efficient. This paper will explain the result for e-learning system performance evaluation based on faculties and students perspective using the Web-Based Evaluation model of E-Learning system. Number of samples used in this study were 348 students and 270 lecturers who use e-learning system namely Binusmaya. Results obtained from this study were the characteristics and problems of e-learning systems that were complained by users as well as an alternative solution to solve these problems and suggest some recommendations. © 2013 IEEE.

关键词： Students

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Verification of relationship between heart rate and body movement for fatigue estimation

Verification of relationship between heart rate and body mov...

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IEEE International Conference on Industrial Informatics (INDIN)

作者： Jinhua She Hitoshi Nakamura Junya Imani Yasuhiro Ohyama Hiroshi Hashimoto Min Wu School of Information Science and Engineering Hunan Engineering Laboratory for Advanced Control and Intelligent Automation Changsha China School of Computer Science Tokyo University of Technology Hachioji Japan Graduate School of Bionics Tokyo University of Technology Hachioji Japan Master Program of Innovation for Design and Engineering Advanced Institute of Industrial Technology Japan

It is an urgent need to find an objective way to estimate the degree of fatigue of employees. In this study, we designed a monitoring and estimation system for the degree of fatigue. This paper explains a long-term pedaling experiment that we use it to explore the possibility to use only the time sequence data of head movement during pedaling to estimate the fatigue. While we show the possibility for this through experimental data, it is clear that we need to collect more data to establish an estimation method.

关键词： Fatigue Heart rate Estimation Educational institutions Monitoring Correlation Electronic mail

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Maximum Entropy Threshold Segmentation for Target Matching Using Speeded-Up Robust Features

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Journal of Electrical and Computer Engineering 2014年第1期2014卷 1-12页

作者： Zhou, Mu Hong, Xia Tian, Zengshan Dong, Huining Wang, Mingchun Xu, Kunjie Chongqing Key Laboratory of Mobile Communications Technology Chongqing University of Posts and Telecommunications Chongqing400065 China Chongqing Laboratory of Material Physics and Information Display Chongqing University of Posts and Telecommunications Chongqing400065 China Graduate Telecommunications and Networking Program University of Pittsburgh PittsburghPA15260 United States

This paper proposes a 2-dimensional (2D) maximum entropy threshold segmentation (2DMETS) based speeded-up robust features (SURF) approach for image target matching. First of all, based on the gray level of each pixel and the average gray level of its neighboring pixels, we construct a 2D gray histogram. Second, by the target and background segmentation, we localize the feature points at the interest points which have the local extremum of box filter responses. Third, from the 2D Haar wavelet responses, we generate the 64-dimensional (64D) feature point descriptor vectors. Finally, we perform the target matching according to the comparisons of the 64D feature point descriptor vectors. Experimental results show that our proposed approach can effectively enhance the target matching performance, as well as preserving the real-time capacity. © 2014 Mu Zhou et al.

关键词： Pixels

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Towards statistical linear accuracy of neighbor matching localization in Wi-Fi environment

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Journal of Computational information Systems 2013年第22期9卷 9177-9184页

作者： Zhou, Mu Tian, Zengshan Xu, Kunjie Hong, Xia Tang, Xiaomou Chongqing Key Lab. of Mobile Communications Technology School of Communication and Information Engineering Chongqing University of Posts and Telecommunications Chongqing 400065 China Graduate Telecommunication and Networking Program School of Information Science University of Pittsburgh Pittsburgh 15260 United States

As one of the most significant work of interest for the pervasive computing and ubiquitous context-awareness, the ways to effectively locate people's positions and realize the real-time interaction among different location-based services and devices have always been seriously concerned. Although a large number of localization systems for outdoor environments have been proposed in the past decade ranging from the military to public uses, their accuracy in indoor and urban environments can not be guaranteed because of the received signal strength (RSS) shadowing and multi-path interference. Therefore, the neighbor matching localization using Wi-Fi network in indoor areas has been significantly favored since the invention of the world's first RSS fingerprints-based RADAR localization system in 2000. However, there is no rigorous analytical solution to the statistical errors of neighbor matching localization. Therefore, we will present some mathematical analysis towards the statistical linear errors of neighbor matching localization and introduce the position entropy as a new metric to examine the variations of accuracy. Furthermore, the mathematical results and some related interesting observations from this paper are also verified by the numerical and simulation evaluations. © 2013 Binary information Press.

关键词： Entropy

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Cross-camera vehicle tracking via affine invariant object matching for video forensics applications

Cross-camera vehicle tracking via affine invariant object ma...

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2013 IEEE International Conference on Multimedia and Expo, ICME 2013

作者： Hsu, Chao-Yung Kang, Li-Wei Mark Liao, Hong-Yuan Institute of Information Science Academia Sinica Taipei Taiwan Graduate School of Engineering Science and Technology-Doctoral Program Department of Computer Science and Information Engineering National Yunlin University of Science and Technology Yunlin Taiwan

ISBN: (纸本)9781479900152

The recent deployment of very large-scale camera networks consisting of fixed/moving surveillance cameras and vehicle video recorders, has led to a novel field in object tracking problem. The major goal is to detect and track each vehicle within a large area, which can be applied to video forensics. For example, a suspected vehicle can be automatically identified for mining digital criminal evidences from a large amount of video data. In this paper, we propose an efficient cross-camera vehicle tracking technique via affine invariant object matching. More specifically, we formulate the problem as invariant image feature matching among different viewpoints of cameras. To achieve vehicle matching, we first extract invariant image feature based on ASIFT (affine and scale-invariant feature transform) for each detected vehicle in a camera network. Then, to improve the accuracy of ASIFT feature matching between images from different viewpoints, we propose to efficiently match feature points based on our observed spatially invariant property of ASIFT, as well as the min-hash technique. As a result, cross-camera vehicle tracking can be efficiently and accurately achieved. Experimental results demonstrate the efficacy of the proposed algorithm and the feasibility to video forensics applications. © 2013 IEEE.

关键词： Tracking (position)

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Haze effect removal from image via haze density estimation in optical model

Haze effect removal from image via haze density estimation i...

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作者： Yeh, Chia-Hung Kang, Li-Wei Lee, Ming-Sui Lin, Cheng-Yang Department of Electrical Engineering National Sun Yat-sen University 804 Taiwan Graduate School of Engineering Science and Technology-Doctoral Program Department of Computer Science and Information Engineering National Yunlin University of Science and Technology Yunlin 640 Taiwan Graduate Institute of Networking and Multimedia Department of Computer Science and Information Engineering National Taiwan University Taipei 106 Taiwan

Images/videos captured from optical devices are usually degraded by turbid media such as haze, smoke, fog, rain and snow. Haze is the most common problem in outdoor scenes because of the atmosphere conditions. This paper proposes a novel single image-based dehazing framework to remove haze artifacts from images, where we propose two novel image priors, called the pixel-based dark channel prior and the pixel-based bright channel prior. Based on the two priors with the haze optical model, we propose to estimate atmospheric light via haze density analysis. We can then estimate transmission map, followed by refining it via the bilateral filter. As a result, high-quality haze-free images can be recovered with lower computational complexity compared with the state-of-the-art approach based on patch-based dark channel prior. ©2013 Optical Society of America.

关键词： Pixels

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Error analysis for RADAR neighbor matching localization in linear logarithmic strength varying Wi-Fi environment

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The Scientific World Journal 2014年第1期2014卷 647370页

作者： Zhou, Mu Tian, Zengshan Xu, Kunjie Yu, Xiang Wu, Haibo Chongqing Key Lab of Mobile Communications Technology Chongqing University of Posts and Telecommunications Chongqing 400065 China Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Kowloon Hong Kong Graduate Telecommunications and Networking Program University of Pittsburgh Pittsburgh PA 15260 United States China Internet Research Lab Computer Network Information Center Chinese Academy of Sciences Beijing 100190 China

This paper studies the statistical errors for the fingerprint-based RADAR neighbor matching localization with the linearly calibrated reference points (RPs) in logarithmic received signal strength (RSS) varying Wi-Fi environment. To the best of our knowledge, little comprehensive analysis work has appeared on the error performance of neighbor matching localization with respect to the deployment of RPs. However, in order to achieve the efficient and reliable location-based services (LBSs) as well as the ubiquitous context-awareness in Wi-Fi environment, much attention has to be paid to the highly accurate and cost-efficient localization systems. To this end, the statistical errors by the widely used neighbor matching localization are significantly discussed in this paper to examine the inherent mathematical relations between the localization errors and the locations of RPs by using a basic linear logarithmic strength varying model. Furthermore, based on the mathematical demonstrations and some testing results, the closed-form solutions to the statistical errors by RADAR neighbor matching localization can be an effective tool to explore alternative deployment of fingerprint-based neighbor matching localization systems in the future. © 2014 Mu Zhou et al.

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A lightweight method for wireless sensor network intrusion detections

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ICIC Express Letters 2013年第6期7卷 1793-1798页

作者： Chen, Rung-Ching Hsieh, Chia-Fen Huang, Yung-Fa Department of Information Management College of Informatics Chaoyang University of Technology No. 168 Jifeng E. Rd Wufeng District Taichung 41349 Taiwan Graduate Institute of Informatics Doctoral Program College of Informatics Chaoyang University of Technology No. 168 Jifeng E. Rd Wufeng District Taichung 41349 Taiwan Department of Information and Communication Engineering College of Informatics Chaoyang University of Technology No. 168 Jifeng E. Rd Wufeng District Taichung 41349 Taiwan

Wireless sensor networks can be applied to health care and disaster response, etc. The importance and accuracy of the information requirements of wireless sensors are more stringent. It corresponding to the use of information security should be taken seriously. The detection technology of intrusion detection system (IDS) will affect the lifetime of entire wireless sensor network (WSN). This study combines ontology with intrusion detection system to propose a lightweight ontology intrusion detection system (OWIDS). The system builds the relationship of sensor node in the ontology to detect Sybil attack firstly. The patrol node loads a part of the ontology to detect Sybil attack. Finally, the system uses the isolation table to continue isolation abnormal nodes to avoid duplicate detection energy-consuming. The preliminary experimental result shows that our proposed method can reduce the energy consumption for wireless sensor network intrusion detection, and improve the availability of intrusion detection systems. © 2013 ISSN 1881-803X.

关键词： Ontology

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Effect of hop counts on power division ratio in multi-hop power transfer via magnetic resonance

Effect of hop counts on power division ratio in multi-hop po...

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IEEE Wireless Power Transfer Conference (WPTC)

作者： Akiro Shimada Yuki Ito Hideyuki Uehara Takashi Ohira Graduate Program of Electrical and Electronic Information Engineering Toyohashi University of Technology Japan Department of Electrical and Electronic Information Engineering Toyohashi University of Technology Japan

In this paper, we discuss the effect of the number of hops on the power division in wireless power transfer via magnetic resonance based on the electric circuit theory. First, a power division ratio (PDR) of single-hop power transfer to multiple receivers is addressed by using an equivalent circuit. The PDR of each receiver is shown to be inversely proportional to load resistances. Secondly, the PDR of multi-hop power transfer to multiple receivers is discussed focusing on the parity of the number of hops. Under the condition that a transmitter and intermediate couplers are arranged on an equal distance, it is needed to switch the control strategy of adjusting load resistance according to the parity of the number of hops on multi-hop power transfer to multiple receivers.

关键词： Receivers Resistance Couplers Wireless communication Magnetic resonance Equivalent circuits Couplings

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Publisher Correction: Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity

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Nature genetics 2018年第5期50卷 766-767页

作者： Valérie Turcot Yingchang Lu Heather M Highland Claudia Schurmann Anne E Justice Rebecca S Fine Jonathan P Bradfield Tõnu Esko Ayush Giri Mariaelisa Graff Xiuqing Guo Audrey E Hendricks Tugce Karaderi Adelheid Lempradl Adam E Locke Anubha Mahajan Eirini Marouli Suthesh Sivapalaratnam Kristin L Young Tamuno Alfred Mary F Feitosa Nicholas G D Masca Alisa K Manning Carolina Medina-Gomez Poorva Mudgal Maggie C Y Ng Alex P Reiner Sailaja Vedantam Sara M Willems Thomas W Winkler Gonçalo Abecasis Katja K Aben Dewan S Alam Sameer E Alharthi Matthew Allison Philippe Amouyel Folkert W Asselbergs Paul L Auer Beverley Balkau Lia E Bang Inês Barroso Lisa Bastarache Marianne Benn Sven Bergmann Lawrence F Bielak Matthias Blüher Michael Boehnke Heiner Boeing Eric Boerwinkle Carsten A Böger Jette Bork-Jensen Michiel L Bots Erwin P Bottinger Donald W Bowden Ivan Brandslund Gerome Breen Murray H Brilliant Linda Broer Marco Brumat Amber A Burt Adam S Butterworth Peter T Campbell Stefania Cappellani David J Carey Eulalia Catamo Mark J Caulfield John C Chambers Daniel I Chasman Yii-Der I Chen Rajiv Chowdhury Cramer Christensen Audrey Y Chu Massimiliano Cocca Francis S Collins James P Cook Janie Corley Jordi Corominas Galbany Amanda J Cox David S Crosslin Gabriel Cuellar-Partida Angela D'Eustacchio John Danesh Gail Davies Paul I W Bakker Mark C H Groot Renée Mutsert Ian J Deary George Dedoussis Ellen W Demerath Martin Heijer Anneke I Hollander Hester M Ruijter Joe G Dennis Josh C Denny Emanuele Di Angelantonio Fotios Drenos Mengmeng Du Marie-Pierre Dubé Alison M Dunning Douglas F Easton Todd L Edwards David Ellinghaus Patrick T Ellinor Paul Elliott Evangelos Evangelou Aliki-Eleni Farmaki I Sadaf Farooqi Jessica D Faul Sascha Fauser Shuang Feng Ele Ferrannini Jean Ferrieres Jose C Florez Ian Ford Myriam Fornage Oscar H Franco Andre Franke Paul W Franks Nele Friedrich Ruth Frikke-Schmidt Tessel E Galesloot Wei Gan Ilaria Gandin Paolo Gasparini Jane Gibson Vilmantas Giedraitis Anette P Gjesing Penny Gordon-Larsen Mathias Gorski Hans-Jörgen Montreal Heart Institute Université de Montréal Montreal Quebec Canada. Division of Epidemiology Department of Medicine Vanderbilt-Ingram Cancer Center Vanderbilt Epidemiology Center Vanderbilt University School of Medicine Nashville TN USA. Charles Bronfman Institute for Personalized Medicine Icahn School of Medicine at Mount Sinai New York NY USA. Genetics of Obesity and Related Metabolic Traits Program Icahn School of Medicine at Mount Sinai New York NY USA. Department of Epidemiology University of North Carolina Chapel Hill NC USA. Human Genetics Center University of Texas School of Public Health University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences University of Texas Health Science Center at Houston Houston TX USA. Broad Institute of MIT and Harvard Cambridge MA USA. Department of Genetics Harvard Medical School Boston MA USA. Division of Endocrinology and Center for Basic and Translational Obesity Research Boston Children's Hospital Boston MA USA. Center for Applied Genomics Division of Human Genetics Children's Hospital of Philadelphia Philadelphia PA USA. Quantinuum Research LLC San Diego CA USA. Estonian Genome Center University of Tartu Tartu Estonia. Division of Epidemiology Department of Medicine Institute for Medicine and Public Health Vanderbilt Genetics Institute Vanderbilt University Nashville TN USA. Institute for Translational Genomics and Population Sciences LABioMed at Harbor-UCLA Medical Center Torrance CA USA. Wellcome Trust Sanger Institute Hinxton UK. Department of Mathematical and Statistical Sciences University of Colorado Denver CO USA. Wellcome Trust Centre for Human Genetics University of Oxford Oxford UK. Department of Biological Sciences Faculty of Arts and Sciences Eastern Mediterranean University Famagusta Cyprus. Max Planck Institute of Immunobiology and Epigenetics Freiburg Germany. Department of Biostatistics and Center for Statistical Genetics University of M

In the version of this article originally published, one of the two authors with the name Wei Zhao was omitted from the author list and the affiliations for both authors were assigned to the single Wei Zhao in the author list. In addition, the ORCID for Wei Zhao (Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA) was incorrectly assigned to author Wei Zhou. The errors have been corrected in the HTML and PDF versions of the article.

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