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21st Medicine Meets Virtual Reality Conference, NextMed/MMVR 2014

作者： Kramers, Matthew Armstrong, Ryan Bakhshmand, Saeed M. Fenster, Aaron De Ribaupierre, Sandrine Eagleson, Roy Biomedical Engineering Graduate Program University of Western Ontario Canada Department of Clinical Neurological Sciences University of Western Ontario Canada Department of Electrical and Computer Engineering University of Western Ontario Canada Robarts Research Institute University of Western Ontario Canada

ISBN: (纸本)9781614993742

Image guidance can provide surgeons with valuable contextual information during a medical intervention. Often, image guidance systems require considerable infrastructure, setup-time, and operator experience to be utilized. Certain procedures performed at bedside are susceptible to navigational errors that can lead to complications. We present an application for mobile devices that can provide image guidance using augmented reality to assist in performing neurosurgical tasks. A methodology is outlined that evaluates this mode of visualization from the standpoint of perceptual localization, depth estimation, and pointing performance, in scenarios derived from a neurosurgical targeting task. By measuring user variability and speed we can report objective metrics of performance for our augmented reality guidance system.© 2014 The authors and IOS Press. All rights reserved.

关键词： Augmented reality

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Author Correction: The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

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Scientific data 2021年第1期8卷 72页

作者： Gilberto Pastorello Carlo Trotta Eleonora Canfora Housen Chu Danielle Christianson You-Wei Cheah Cristina Poindexter Jiquan Chen Abdelrahman Elbashandy Marty Humphrey Peter Isaac Diego Polidori Markus Reichstein Alessio Ribeca Catharine van Ingen Nicolas Vuichard Leiming Zhang Brian Amiro Christof Ammann M Altaf Arain Jonas Ardö Timothy Arkebauer Stefan K Arndt Nicola Arriga Marc Aubinet Mika Aurela Dennis Baldocchi Alan Barr Eric Beamesderfer Luca Belelli Marchesini Onil Bergeron Jason Beringer Christian Bernhofer Daniel Berveiller Dave Billesbach Thomas Andrew Black Peter D Blanken Gil Bohrer Julia Boike Paul V Bolstad Damien Bonal Jean-Marc Bonnefond David R Bowling Rosvel Bracho Jason Brodeur Christian Brümmer Nina Buchmann Benoit Burban Sean P Burns Pauline Buysse Peter Cale Mauro Cavagna Pierre Cellier Shiping Chen Isaac Chini Torben R Christensen James Cleverly Alessio Collalti Claudia Consalvo Bruce D Cook David Cook Carole Coursolle Edoardo Cremonese Peter S Curtis Ettore D'Andrea Humberto da Rocha Xiaoqin Dai Kenneth J Davis Bruno De Cinti Agnes de Grandcourt Anne De Ligne Raimundo C De Oliveira Nicolas Delpierre Ankur R Desai Carlos Marcelo Di Bella Paul di Tommasi Han Dolman Francisco Domingo Gang Dong Sabina Dore Pierpaolo Duce Eric Dufrêne Allison Dunn Jiří Dušek Derek Eamus Uwe Eichelmann Hatim Abdalla M ElKhidir Werner Eugster Cacilia M Ewenz Brent Ewers Daniela Famulari Silvano Fares Iris Feigenwinter Andrew Feitz Rasmus Fensholt Gianluca Filippa Marc Fischer John Frank Marta Galvagno Mana Gharun Damiano Gianelle Bert Gielen Beniamino Gioli Anatoly Gitelson Ignacio Goded Mathias Goeckede Allen H Goldstein Christopher M Gough Michael L Goulden Alexander Graf Anne Griebel Carsten Gruening Thomas Grünwald Albin Hammerle Shijie Han Xingguo Han Birger Ulf Hansen Chad Hanson Juha Hatakka Yongtao He Markus Hehn Bernard Heinesch Nina Hinko-Najera Lukas Hörtnagl Lindsay Hutley Andreas Ibrom Hiroki Ikawa Marcin Jackowicz-Korczynski Dalibor Janouš Wilma Jans Rachhpal Jassal Shicheng Jiang Tomomichi Kato Myr Computational Research Division Lawrence Berkeley National Laboratory Berkeley CA 94720 USA. gzpastorello@lbl.gov. DIBAF University of Tuscia Viterbo 01100 Italy. Euro-Mediterranean Centre on Climate Change Foundation (CMCC) Lecce 73100 Italy. Climate & Ecosystem Sciences Division Lawrence Berkeley National Laboratory Berkeley CA 94720 USA. Computational Research Division Lawrence Berkeley National Laboratory Berkeley CA 94720 USA. Department of Civil Engineering California State University Sacramento CA 95819 USA. Department of Geography Environment and Spatial Sciences Michigan State University East Lansing MI 48823 USA. Department of Computer Science University of Virginia Charlottesville VA 22904 USA. TERN Ecosystem Processes Menzies Creek VIC3159 Australia. Max Planck Institute for Biogeochemistry Jena 07701 Germany. Laboratoire des Sciences du Climat et de l'Environnement (LSCE) CEA CNRS UVSQ UPSACLAY Gif sur Yvette 91190 France. Key Laboratory of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing 100101 China. Department of Soil Science University of Manitoba Winnipeg MB R3T2N2 Canada. Department of Agroecology and Environment Agroscope Research Institute Zürich 8046 Switzerland. School of Geography and Earth Sciences McMaster University L8S4K1 Hamilton ON Canada. Department of Physical Geography and Ecosystem Science Lund University Lund 22362 Sweden. Department of Agronomy and Horticulture University of Nebraska-Lincoln Lincoln NE 68583 USA. School of Ecosystem and Forest Sciences The University of Melbourne Richmond VIC3121 Australia. Department of Biology Research Group PLECO University of Antwerp Antwerp 2610 Belgium. Joint Research Centre European Commission Ispra 21027 Italy. TERRA Teaching and Research Center University of Liege Gembloux B-5030 Belgium. Finnish Meteorological Institute Helsinki 00560 Finland. ES

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Rotation invariant texture recognition by using Neighbor Discriminant Feature Transform and reinforcement learning

Rotation invariant texture recognition by using Neighbor Dis...

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International Electrical engineering Congress (iEECON)

作者： Nattapong Jundang Surachai Ongkittikul Computer Engineering Graduate Program Mahanakorn University of Technology Bangkok THAILAND Department of Computer Engineering Mahanakorn University of Technology Bangkok THAILAND

This paper presents the method of image texture recognition by Volume Trace Transform-VTT, based on several Trace function. All of 10 trace functions will be selected by the reinforcement learning process and constructed to produce noticeable features. The next process is to sum the results of each function together by “NDFT - Neighbor Discriminant Feature Transform”, this process will all the results from the different positions of image results and construct 2-D histogram. The histogram is evaluated by chi-square statistic test and the process works on the basis of brodatz texture and vision texture database.

关键词： Transforms Measurement Databases

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Causes of blindness and vision impairment in 2020 and trends over 30 years, and prevalence of avoidable blindness in relation to VISION 2020: the Right to Sight: an analysis for the Global Burden of Disease Study (vol 2, pg 144, 2021)

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LANCET GLOBAL HEALTH 2021年第4期9卷 E408-E408页

作者： Steinmetz, Jaimie D. Vision and Eye Research Institute Anglia Ruskin University Cambridge United Kingdom Biomedical Informatics Seoul National University Hospital Seoul South Korea Institute for Health Metrics and Evaluation University of Washington Seattle WA United States Department of Health Metrics Sciences School of Medicine University of Washington Seattle WA United States Institute of Health Services Research Yonsei University Seoul South Korea Department of Ophthalmology University of Washington Seattle WA United States Department of Mathematics Imperial College London London United Kingdom WHO Collaborating Centre for Public Health Education and Training Imperial College London London United Kingdom Department of Primary Care and Public Health Imperial College London London United Kingdom School of Population and Global Health University of Melbourne Carlton VIC Australia School of Optometry and Vision Science UNSW Sydney NSW Australia Brien Holden Vision Institute Sydney Australia Department of Ophthalmology University of Adelaide Adelaide SA Australia Department of Parasitology and Mycology Jahrom University of Medical Sciences Jahrom Iran Department of Clinical Sciences University of Sharjah Sharjah United Arab Emirates Ophthalmic Research Center Shahid Beheshti University of Medical Sciences Tehran Iran Department of Ophthalmology Shahid Beheshti University of Medical Sciences Tehran Iran Research Institute for Endocrine Sciences Shahid Beheshti University of Medical Sciences Tehran Iran Ophthalmic Epidemiology Research Center Shahid Beheshti University of Medical Sciences Tehran Iran Health Services Management Department Qazvin University of Medical Sciences Qazvin Iran Department of Systems Populations and Leadership University of Michigan Ann Arbor MI United States Department of Medicine Sofia Ismail Memorial Medical Centre Bogura Bangladesh The Fred Hollows Foundation Sydney NSW Australia Berhan Public Health & Eye Care Consultancy Addis A

Hospital El Salvador: a novel paradigm of intensive care in response to COVID-19 in central America. Lancet Glob Health 2021;9: e241?42?In this Comment, the conflict of interest statement should have included the following: ?By virtue of their roles within a public hospital or the Ministry of Health, MB, LC, WH, and XS are government employees. The findings and conclusions in the Comment are only those of the authors.? This correction has been made as of Feb 26, 2021.

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Applying Interdisciplinarity and Agile Methods in the Development of an Embedded System

Applying Interdisciplinarity and Agile Methods in the Develo...

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International Conference on Information Technology: New Generations (ITNG)

作者： Renan Cavichi de Freitas Jefferson Andrade de Oliveira Fabiano Yukio Alves Hino Juvenal Silva Neto Leonardo Miranda Vicente Adilson Marques da Cunha Luiz Alberto Vieira Dias Computer and Electronic Engineering Graduate Program Brazilian Aeronautics Institute of Technology Sao Paulo Brazil

This poster describes an academic development of an embedded system project named SETRAIF, which was performed during the 2nd half of 2012, by students and professors of computer engineering courses at the Brazilian Aeronautics Institute of Technology (Instituto Tecnologico de Aeronautica - ITA), combining the use of inter disciplinarity, Agile Methods, and Model Driven Development.

关键词： Embedded systems Hardware computers Prototypes Computational modeling Real-time systems

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Construction of time-stamped mobility map for path tracking via smith-waterman measurement matching

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Mathematical Problems in engineering 2014年第1期2014卷 1-17页

作者： Zhou, Mu Tian, Zengshan Xu, Kunjie Wu, Haibo Pu, Qiaolin Yu, Xiang 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 Hong Kong 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

Path tracking in wireless and mobile environments is a fundamental technology for ubiquitous location-based services (LBSs). In particular, it is very challenging to develop highly accurate and cost-efficient tracking systems applied to the anonymous areas where the floor plans are not available for security and privacy reasons. This paper proposes a novel path tracking approach for large Wi-Fi areas based on the time-stamped unlabeled mobility map which is constructed from Smith-Waterman received signal strength (RSS) measurement matching. Instead of conventional location fingerprinting, we construct mobility map with the technique of dimension reduction from the raw measurement space into a low-dimensional embedded manifold. The feasibility of our proposed approach is verified by the real-world experiments in the HKUST campus Wi-Fi networks, sMobileNet. The experimental results prove that our approach is adaptive and capable of achieving an adequate precision level in path tracking. © 2014 Mu Zhou et al.

关键词： Wi-Fi

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Metadata Correction: Importance-Performance Analysis of Personal Health Records in Taiwan: A Web-Based Survey

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Journal of medical Internet research 2017年第6期19卷 e209页

作者： Hsiao-Hsien Rau Yi-Syuan Wu Chi-Ming Chu Fu-Chung Wang Min-Huei Hsu Chi-Wen Chang Kang-Hua Chen Yen-Liang Lee Senyeong Kao Yu-Lung Chiu Hsyien-Chia Wen Anis Fuad Chien-Yeh Hsu Hung-Wen Chiu Graduate Institute of Biomedical Informatics Taipei Medical University Taipei Taiwan. Administration Department Healthconn Corp Taipei Taiwan. Institute of Medical Informatics Department of Computer Science of Information Engineering National Cheng Kung University Tainan Taiwan. School Of Public Health National Defense Medical Center Taiepi Taiwan. National Health Insurance Administration Ministry of Health and Welfare Taiepi Taiwan. School of Nursing College of Medicine Chang Gung University Linkou Taiwan. Division of Endocrinology Department of Pediatrics Linkou Chang Gung Memorial Hospital Linkou Taiwan. Internet of Things Laboratory Chunghwa Telecom Laboratories TaoYuen Taiwan. School of Health Care Administration Taipei Medical University Taipei Taiwan. Department of Biostatistics Epidemiology and Population Health Faculty of Medicine Universitas Gadjah Mada Yogyakarta Indonesia. Department of Information Management National Taipei University of Nursing and Health Sciences Taipei Taiwan. Master Program in Global Health and Development Taipei Medical University Taipei Taiwan.

[This corrects the article DOI: .].

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Floor plan construction via anonymous Wi-Fi signal fragment matching

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ICIC Express Letters, Part B: Applications 2014年第4期5卷 981-987页

作者： Zhou, Mu Tian, Zengshan Xu, Kunjie Tang, Xiaomou Wang, Zhuoran Chongqing Key Lab of Mobile Communications Technology School of Communication and Information Engineering Chongqing University of Posts and Telecommunications No. 2 Chongwen Road Nan'an Dist. Chongqing 400065 China Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong Graduate Telecommunications and Networking Program University of Pittsburgh PA 15260 United States

Floor plan construction is the basis for fingerprint-based localization and people's activity learning, especially in the environments where the geometrical map is not available or does not exist. To this end, we propose a new received signal strength (RSS) fragment matching approach to identify the location points (LPs) in floor plan as the overlapped pieces between the fragments. Then, by means of the Smith-Waterman alignment, each LP can be recognized as a winning path in scoring space. Finally, we use the Allen's interval algebra to assemble the time-stamped LPs into a floor plan in target area. The experiments with the actual Wi-Fi RSS measurements recorded in HKUST campus demonstrate that our proposed approach performs better than the conventional K-means clustering and spectral clustering in floor plan construction. © 2014 ICIC International.

关键词： Algebra

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Comparison between wire and wireless EEG acquisition systems based on SSVEP in an Independent-BCI

Comparison between wire and wireless EEG acquisition systems...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Richard M. G. Tello Sandra M. T. Müller Teodiano Bastos-Filho Andre Ferreira Post-Graduate Program of Electrical Engineering (PPGEE). UFES Vitoria Brazil Department of Computer and Electronics (CEUNES) Brazil

This paper presents a comparison between two different technologies of acquisition systems (BrainNet36 and Emotiv Epoc) for an Independent-BCI based on Steady-State Visual Evoked Potential (SSVEP). Two stimuli separat... 详细信息

关键词： Visualization Electrodes Indexes Accuracy Brain-computer interfaces Synchronization Feature extraction

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Evolving fuzzy classifier based on clustering algorithm and drift detection for fault diagnosis applications

Evolving fuzzy classifier based on clustering algorithm and ...

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2014 Annual Conference of the Prognostics and Health Management Society, PHM 2014

作者： Inacio, Maurilio Lemos, Andre Caminhas, Walmir Graduate Program in Electrical Engineering Federal University of Minas Gerais Belo Horizonte31270-901 Brazil Dept. of Computer Engineering Faculdade de Ciencia e Tecnologia de Montes Claros Montes Claros39400-142 Brazil Dept. of Electronic Engineering Federal University of Minas Gerais Belo Horizonte31270-901 Brazil

ISBN: (纸本)9781936263172

Nowadays, in several areas, efficient fault diagnosis methods for complex machinery and equipments are required. Several fault diagnosis methods based on different theories and approaches have been proposed in the literature. In general, these methods use mathematical/statistical models, accumulated experience, or even process historical data to perform fault diagnosis. Although methods based on models or experience have shown to be effective, they have the disadvantage of requiring previous knowledge of the dynamic system in question. On the contrary, methods based on process historical data do not require a prior knowledge, they are based solely on data obtained directly from the dynamic system. The application of so-called "Evolving Intelligent Systems" to accomplish fault diagnosis from process data have been shown a promising approach. This paper proposes an evolving fuzzy classifier based on a new approach that combines a recursive clustering algorithm and a drift detection method and its application on dynamic systems fault diagnosis. The novel approach provides greater robustness to outliers and noise present in data from process sensors. The classifier is evaluated in fault diagnosis of an interacting tank system and the results are promising.

关键词： Failure analysis

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