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10th International Conference on Informatics in Control, Automation and Robotics, ICINCO 2013

作者： She, Jinhua Nakamura, Hitoshi Makino, Koji Ohyama, Yasuhiro Hashimoto, Hiroshi Wu, Min Graduate School of Bionics Computer and Media Sciences Tokyo University of Technology 1404-1 Katakura Hachioji Tokyo 192-0982 Japan Interdisciplinary Graduate School of Medical and Engineering University of Yamanashi 4-3-11 Takeda Kofu 400-8511 Japan Master Program of Innovation for Design and Engineering Advanced Institute of Industrial Technology Shinagawa Tokyo 140-0011 Japan School of Information Science and Engineering Central South University Changsha 410083 China

ISBN: (纸本)9789898565716

Maximum heart rate (MHR) is commonly used to estimate exercise intensity with the Karvonen formula, and there are several methods of calculating it. In this study, we used pedaling experiments on a cycle ergometer to evaluate methods of determining MHR in order to select the ones most suitable for the Karvonen formula. In the experiments, 43 subjects rode an aerobike. The results show that, for people in their 20s, two methods are suitable for estimating exercise intensity with the Karvonen formula. The main physical parameters affecting exercise intensity were also extracted, based on the experimental results.

关键词： Heart

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Human-robotic collaborative intelligent control for reaching performance

Human-robotic collaborative intelligent control for reaching...

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7th International Conference on Foundations of Augmented Cognition, AC 2013, Held as Part of 15th International Conference on Human-computer Interaction, HCI International 2013

作者： Gentili, Rodolphe J. Oh, Hyuk Shuggi, Isabelle M. Goodman, Ronald N. Rietschel, Jeremy C. Hatfield, Bradley D. Reggia, James A. Department of Kinesiology Cognitive Motor Neuroscience Laboratory University of Maryland College Park MD 20742 United States Neuroscience and Cognitive Science Program University of Maryland College Park MD 20742 United States Maryland Robotics Center University of Maryland College Park MD 20742 United States Institute for Systems Research University of Maryland College Park MD 20742 United States Veterans Health Administration Maryland Exercise and Robotics Center of Excellence Baltimore MD 21201 United States Department of Computer Science University of Maryland College Park MD 20742 United States Maryland Institute for Advanced Computer Studies University of Maryland College Park MD 20742 United States

ISBN: (纸本)9783642394539

In most human-robot interfaces, the user completely controls the robot that operates as a passive tool without adaptation capabilities. However, a synergetic human-robot interface where both agents collaborate could improve the user's performance while reducing the cognitive and physical workload. Specifically, when considering this framework applied to rehabilitation, we examined a shared collaborative control between a human user and an adaptive biologically inspired neurocontroller in order to perform reaching movements with a simulated prosthetic arm. When this neurocontroller was enabled, it progressively learned from the user to control the prosthetic arm, increasing its role in the shared performance and facilitating the user's reaching movements. This resulted in the user's performance enhancement and in a reduction of his/her cognitive workload. The long term goal of this work is to contribute to the development of the next generation of intelligent human-robotic interfaces for rehabilitation. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Adaptive control systems

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A unified optimization method for real-time trajectory generation of mobile robots with kinodynamic constraints in dynamic environment

A unified optimization method for real-time trajectory gener...

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IEEE Conference on Robotics, Automation and Mechatronics

作者： Wenhao Luo Jun Peng Weirong Liu Jing Wang Wentao Yu Department of Automation Key Laboratory of System Control And Information Processing Shanghai China School of Information Science and Engineering Hunan Engineering Laboratory for Advanced Controland Intelligent Automation Changsha China Computer Engineering Program Bethune-Cookman University Daytona Beach FL USA

This paper presents an efficient analytic method for a mobile robot to determine a collision-free trajectory with unified optimization. The robot kinodynamic constraints and the geometric constraints due to obstacles are addressed by considering a set of constrained inequalities from parameterized trajectories model. Two optimal performance matrices are employed to assess optimization problems. Particularly, both the constraints and performance functions are incorporated by similar forms in terms of trajectory parameters, which thereby can be considered in a uniform way. A parameter space of adjustable trajectory parameters is constructed to solve the unified optimization problem with constraints and results in more flexible and better optimal performance. The proposed approach is complete and enhances methods of deterministic real-time planning by overcoming typical drawbacks as intermediate configuration, curvature discontinuities, vertical singularities and incomplete optimization. Simulation results verify the validity and superiority of the proposed method.

关键词： Trajectory Robot kinematics Collision avoidance Mobile robots Acceleration Optimization

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Sensors: Stretchable, Multiplexed pH Sensors With Demonstrations on Rabbit and Human Hearts Undergoing Ischemia (Adv. Healthcare Mater. 1/2014)

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advanced Healthcare Materials 2014年第1期3卷

作者： Hyun‐Joong Chung Matthew S. Sulkin Jong‐Seon Kim Camille Goudeseune Hsin‐Yun Chao Joseph W. Song Sang Yoon Yang Yung‐Yu Hsu Roozbeh Ghaffari Igor R. Efimov John A. Rogers Department of Chemical and Materials Engineering University of Alberta Edmonton AB T6G 2V4 Canada Department of Materials Science and Engineering University of Illinois at Urbana‐Champaign Urbana IL 61801 USA Department of Biomedical Engineering Washington University in Saint Louis Saint Louis MO USA Department of Chemical and Biomolecular Engineering (BK21 Program) Korea Advanced Institute of Science and Technology Daejeon Korea Illinois Simulator Laboratory Beckman Institute University of Illinois Urbana IL 61801 USA MC10 Inc. 36 Cameron Avenue Cambridge MA 02140 USA Department of Materials Science and Engineering Chemistry Mechanical Science and Engineering Electrical and Computer Engineering Beckman Institute for Advanced Science and Technology and Frederick Seitz Materials Research Laboratory University of Illinois at Urbana‐Champaign Urbana IL 61801 USA

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Smart environmental architecture for node localization in a wireless sensor network

Smart environmental architecture for node localization in a ...

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8th International Conference on Intelligent Environments, IE 2012

作者： Jauregui-Ortiz, Salvador Siller, Mario Ramos, Felix Scalabrin, Edson Electrical Engineering and Computer Science Department Center of Research and Advanced Studies Guadalajara Jalisco Mexico Graduate Program in Computer Science Pontifical Catholic University Parana Brazil Curitiba Parana Brazil

ISBN: (纸本)9780769547411

As far as we know, there is not a Node Localization Algorithm (NLA) that presents the same accuracy for all possible scenarios. We believe that a NLA should be able to interpret the dynamic information of the environment. In this sense, simple NLAs are rather focused and might perform well for specific scenarios and applications. Therefore, information fusion and context awareness seems to be an appropriate approach to address this issue. We propose the Smart Environmental Architecture for Node Localization (SEA-NL), which is composed by two main elements: (i) the Smart Beacon Nodes (SBNs) and (ii) the Logical Position of Nodes (LPN). In (i) the obstruction level indicator is estimated and can improve the estimation of distances among nodes. In (ii) environment information and a one to one relation between a node and an object are used and can also improve location estimation. Via simulation, our architecture was tested indoors and outdoors considering three localization algorithms: the Weighed Centroid Localization (WCL), the Centroid Localization, and the Triangular Centroid Localization. Finally, we present an accuracy comparison among NLAs used in isolated way, and by using the SBNs, the LPN, and the SEA-NL, where our architecture improves WCL up to ~30.88%. © 2012 IEEE.

关键词： Information fusion

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Improved malware classification through sensor fusion using disjoint union

Improved malware classification through sensor fusion using ...

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6th International Conference on Information Systems, Management and Technology, ICISTM 2012

作者： LeDoux, Charles Walenstein, Andrew Lakhotia, Arun Center for Advanced Computer Studies University of Louisiana at Lafayette Lafayette LA United States School of Computing and Informatics Computer Science Program University of Louisiana at Lafayette Lafayette LA United States

ISBN: (纸本)9783642291654

In classifying malware, an open research question is how to combine similar extracted data from program analyzers in such a way that the advantages of the analyzers accrue and the errors are minimized. We propose an approach to fusing multiple program analysis outputs by abstracting the features to a common form and utilizing a disjoint union fusion function. The approach is evaluated in an experiment measuring classification accuracy on fused dynamic trace data on over 18,000 malware files. The results indicate that a naïve fusion approach can yield improvements over non-fused results, but the disjoint union fusion function outperforms naïve union by a statistically significant amount in three of four classification methods applied. © 2012 Springer-Verlag.

关键词： Malware

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XXIV World Allergy Congress 2015 Seoul, Korea. 14-17 October 2015 Abstracts

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WORLD ALLERGY ORGANIZATION JOURNAL 2016年第1期9卷 1-206页

作者： [Anonymous] Korea University College of Medicine Guro Hospital Seoul South Korea College of Medicine Korea University Seoul South Korea Korea University Guro Hospital Seoul South Korea Seoul National University Boramae Hospital Seoul South Korea Division of Clinical Immunology Faculty of Medicine University of Debrecen Debrecen Hungary Meiji Pharmaceutical University Tokyo Japan Suri Medical Foundation Hospital Uttar Pradesh State India Shahid Beheshti University Tehran Iran Airlangga University Teaching Hospital Surabaya Indonesia Tokyo Metropolitan Police Hospital Tokyo Japan Shinichiro KogaSamsung Changwon Hospital Seoul South Korea Sapporo Tokushukai Hospital Sapporo Japan Department of Dermatology Yonsei University College of Medicine Seoul South Korea Brain Korea 21 PLUS Project for Medical Science Yonsei University College of Medicine Seoul South Korea Sureyyapasa Chest Diseases and Chest Surgery Training Hospital Istanbul Turkey Kangnam Sacred Heart Hospital Seoul South Korea Sakai City Medical Center Sakai Japan Osaka University Suita Japan Yonsei University College of Medicine Seoul South Korea Osaka-Minami Medical Center Kawachinagano Japan Inha University College of Medicine Incheon South Korea Inha University Hospital Incheon South Korea Center for Rhinology and Allergology Wiesbaden Wiesbaden Germany Leti Pharma Gmbh Witten Germany Postgraduate Institute of Medical Education and Research Chandigarh India West Bengal Technical University Kolkata India Institute of Microbiology Academy of Sciences of the Czech Republic Prague Czech Republic Seoul National University Hospital Seoul South Korea Ent and Allergy Centre(INDIA) Panchkula India University of Santo Tomas Hospital Manila Philippines University of Santo Tomas Faculty of Medicine Manila Philippines Kyung Hee University Hospital at Gang-Dong Seoul South Korea Sangji University Wonju South Korea Division of Allergy and Immunology Department of Internal Medicine Yonsei University Colle

A1 Pirfenidone inhibits TGF-b1-induced extracellular matrix production in nasal polyp-derived fibroblasts Jae-Min Shin, Heung-Man Lee, Il-Ho Park A2 The efficacy of a 2-week course of oral steroid in the treatment of chronic spontaneous urticaria refractory to antihistamines Hyun-Sun Yoon, Gyeong Yul Park A3 The altered distribution of follicular t helper cells may predict a more pronounced clinical course of primary sjögren’s syndrome Margit Zeher A4 Betamethasone suppresses Th2 cell development induced by langerhans cell like dendritic cells Katsuhiko Matsui, Saki Tamai, Reiko Ikeda A5 An evaluation of variousallergens in cases of allergic bronchial asthma at lucknow and neighbouring districts by intradermal skintest Drsushil Suri, Dranu Suri A6 Evaluation ferqency of ADHD in childhood asthma Marzieh Heidarzadeh Arani A7 Steven johnson syndrome caused by typhoid fever in a child Azwin Lubis, Anang Endaryanto A8 Chronic Bronchitis with Radio Contrast Media Hypersensitivity: A Case with Hypothesized GINA Step 1 Asthma Shinichiro Koga A9 The association between asthma and depression in Korean adult : An analysis of the fifth korea national health and nutrition examination survey (2010-2012) Lee Ju Suk A10 Management of allergic disease exacerbations in pregnancy Yasunobu Tsuzuki A11 Subcutaneous immunotherapy mouse model for atopic dermatitis Seo Hyeong Kim, Jung U Shin, Ji Yeon Noh, Shan Jin, Shan Jin, Hemin Lee, Jungsoo Lee, Chang Ook Park, Kwang Hoon Lee, Kwang Hoon Lee A12 Atopic disease and/or atopy are risk factors for local anesthetic allergy in patients with history of hypersensitivity reactions to drugs? Fatma Merve Tepetam A13 Food hypersensitivity in patients with atopic dermatitis in Korea Chun Wook Park, Jee Hee Son, Soo Ick Cho, Yong Se Cho, Yun Sun Byun, Yoon Seok Yang, Bo Young Chung, Hye One Kim, Hee Jin Cho A14 Anaphylaxis caused by an ant (Brachyponera chinensis) in Japan Yoshinori Katada, Toshio Tanaka, Akihiko Nakabayashi, Koji Nishida, Kenichi A

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Human genome meeting 2016 : Houston, TX, USA. 28 February - 2 March 2016

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Human genomics 2016年第1期10 Suppl 1卷 12页

作者： A. K. Srivastava Y. Wang R. Huang C. Skinner T. Thompson L. Pollard T. Wood F. Luo R. Stevenson R. Polimanti J. Gelernter X. Lin I. Y. Lim Y. Wu A. L. Teh L. Chen I. M. Aris S. E. Soh M. T. Tint J. L. MacIsaac F. Yap K. Kwek S. M. Saw M. S. Kobor M. J. Meaney K. M. Godfrey Y. S. Chong J. D. Holbrook Y. S. Lee P. D. Gluckman N. Karnani A. Kapoor D. Lee A. Chakravarti C. Maercker F. Graf M. Boutros G. Stamoulis F. Santoni P. Makrythanasis A. Letourneau M. Guipponi N. Panousis M. Garieri P. Ribaux E. Falconnet C. Borel S. E. Antonarakis S. Kumar J. Curran J. Blangero S. Chatterjee J. Akiyama D. Auer C. Berrios L. Pennacchio T. R. Donti G. Cappuccio M. Miller P. Atwal A. Kennedy A. Cardon C. Bacino L. Emrick J. Hertecant F. Baumer B. Porter M. Bainbridge P. Bonnen B. Graham R. Sutton Q. Sun S. Elsea Z. Hu P. Wang Y. Zhu J. Zhao M. Xiong David A. Bennett A. Hidalgo-Miranda S. Romero-Cordoba S. Rodriguez-Cuevas R. Rebollar-Vega E. Tagliabue M. Iorio E. D’Ippolito S. Baroni B. Kaczkowski Y. Tanaka H. Kawaji A. Sandelin R. Andersson M. Itoh T. Lassmann Y. Hayashizaki P. Carninci A. R. R. Forrest C. A. Semple E. A. Rosenthal B. Shirts L. Amendola C. Gallego M. Horike-Pyne A. Burt P. Robertson P. Beyers C. Nefcy D. Veenstra F. Hisama R. Bennett M. Dorschner D. Nickerson J. Smith K. Patterson D. Crosslin R. Nassir N. Zubair T. Harrison U. Peters G. Jarvik F. Menghi K. Inaki X. Woo P. Kumar K. Grzeda A. Malhotra H. Kim D. Ucar P. Shreckengast K. Karuturi J. Keck J. Chuang E. T. Liu B. Ji A. Tyler G. Ananda G. Carter H. Nikbakht M. Montagne M. Zeinieh A. Harutyunyan M. Mcconechy N. Jabado P. Lavigne J. Majewski J. B. Goldstein M. Overman G. Varadhachary R. Shroff R. Wolff M. Javle A. Futreal D. Fogelman L. Bravo W. Fajardo H. Gomez C. Castaneda C. Rolfo J. A. Pinto K. C. Akdemir L. Chin S. Patterson C. Statz S. Mockus S. N. Nikolaev X. I. Bonilla L. Parmentier B. King F. Bezrukov G. Kaya V. Zoete V. Seplyarskiy H. Sharpe T. McKee K. Popadin N. Basset-Seguin R. Ben Chaabene M. Andrianova C. Verdan K. Grosdemange O. Sumara M. E JCSRI Greenwood Genetic Center Greenwood USA School of Computing Clemson University Clemson USA Biochemical Genetics Laboratory Greenwood Genetic Center Greenwood USA Department Psychiatry Yale Sch Med and VA CT Healthcare Center West Haven USA Department Genetics Yale Sch Med and VA CT Healthcare Center West Haven USA Department Neurobiology Yale Sch Med and VA CT Healthcare Center West Haven USA Singapore Institute for Clinical Sciences Singapore Singapore National University of Singapore Singapore Singapore University of British Columbia Vancouver Canada KK Women’s and Children’s Hospital Singapore Singapore University of Southampton and University Hospital Southampton NHS Foundation Trust Southampton UK University of Auckland Auckland New Zealand McKusick-Nathans Institute of Genetic Medicine Johns Hopkins University School of Medicine Baltimore USA Esslingen University of Applied Sciences Esslingen Germany German Cancer Research Center Heidelberg Germany Department of Genetic Medicine and Development University of Geneva Medical School Geneva Switzerland Geneva University Hospitals-HUG Service of Genetic Medicine Geneva Switzerland GE3 Institute of Genetics and Genomics of Geneva University of Geneva Medical School Geneva Switzerland South Texas Diabetes and Obesity Institute School of Medicine University of Texas Rio-Grande Valley Edinburg USA South Texas Diabetes and Obesity Institute School of Medicine University of Texas Rio-Grande Valley Brownsville USA Institute of Genetic Medicine Johns Hopkins University Baltimore USA Genomics Division Lawrence Berkeley National Laboratory Berkeley USA Molecular and Human Genetics Baylor College of Medicine Houston USA Department of Translational Medical Sciences Federico II University Naples Italy Metabolon Inc Durham USA Section of Pediatric Neurology and Neuroscience Baylor College of Medicine Houston USA Tawam Hospital Abu Dhabi United Arab Emirates Stanford Medical School Stanford USA Sch

O1 The metabolomics approach to autism: identification of biomarkers for early detection of autism spectrum disorder A. K. Srivastava, Y. Wang, R. Huang, C. Skinner, T. Thompson, L. Pollard, T. Wood, F. Luo, R. Stevenson O2 Phenome-wide association study for smoking- and drinking-associated genes in 26,394 American women with African, Asian, European, and Hispanic descents R. Polimanti, J. Gelernter O3 Effects of prenatal environment, genotype and DNA methylation on birth weight and subsequent postnatal outcomes: findings from GUSTO, an Asian birth cohort X. Lin, I. Y. Lim, Y. Wu, A. L. Teh, L. Chen, I. M. Aris, S. E. Soh, M. T. Tint, J. L. MacIsaac, F. Yap, K. Kwek, S. M. Saw, M. S. Kobor, M. J. Meaney, K. M. Godfrey, Y. S. Chong, J. D. Holbrook, Y. S. Lee, P. D. Gluckman, N. Karnani, GUSTO study group O4 High-throughput identification of specific qt interval modulating enhancers at the SCN5A locus A. Kapoor, D. Lee, A. Chakravarti O5 Identification of extracellular matrix components inducing cancer cell migration in the supernatant of cultivated mesenchymal stem cells C. Maercker, F. Graf, M. Boutros O6 Single cell allele specific expression (ASE) IN T21 and common trisomies: a novel approach to understand DOWN syndrome and other aneuploidies G. Stamoulis, F. Santoni, P. Makrythanasis, A. Letourneau, M. Guipponi, N. Panousis, M. Garieri, P. Ribaux, E. Falconnet, C. Borel, S. E. Antonarakis O7 Role of microRNA in LCL to IPSC reprogramming S. Kumar, J. Curran, J. Blangero O8 Multiple enhancer variants disrupt gene regulatory network in Hirschsprung disease S. Chatterjee, A. Kapoor, J. Akiyama, D. Auer, C. Berrios, L. Pennacchio, A. Chakravarti O9 Metabolomic profiling for the diagnosis of neurometabolic disorders T. R. Donti, G. Cappuccio, M. Miller, P. Atwal, A. Kennedy, A. Cardon, C. Bacino, L. Emrick, J. Hertecant, F. Baumer, B. Porter, M. Bainbridge, P. Bonnen, B. Graham, R. Sutton, Q. Sun, S. Elsea O10 A novel causal methylation network approach to Alzheimer’s

关键词： Pulmonary Arterial Hypertension Oral Squamous Cell Carcinoma Deep Neural Network Autosomal Recessive Polycystic Kidney Disease Whole Genome Bisulfite Sequencing

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Nanoinformatics workshop report: Current resources, community needs and the proposal of a collaborative framework for data sharing and information integration

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Computational science and Discovery 2013年第1期6卷 14008页

作者： Harper, Stacey L. Hutchison, James E. Baker, Nathan Ostraat, Michele Tinkle, Sally Steevens, Jeffrey Hoover, Mark D. Adamick, Jessica Rajan, Krishna Gaheen, Sharon Cohen, Yoram Nel, Andre Cachau, Raul E. Tuominen, Mark Department of Environmental and Molecular Toxicology Oregon State University Corvallis OR United States School of Chemical Biological and Environmental Engineering Oregon State University Corvallis OR United States Department of Chemistry University of Oregon Eugene OR United States Pacific Northwest National Laboratory Richland WA United States RTI International Research Triangle Park NC United States Science and Technology Policy Institute Washington DC United States US Army Engineer Research and Development Center Vicksburg MS United States National Institute for Occupational Safety and Health Morgantown WV United States University Libraries University of Michigan Amherst MA United States Department of Materials Science and Engineering Iowa State University Ames IA United States SAIC Frederick Frederick MD United States Department of Chemical and Biomolecular Engineering University of California Los Angeles CA United States Center for Environmental Implications of Nanotechnology University of California Los Angeles CA United States Advanced Biomedical Computer Center Information Systems Program Frederick National Laboratory for Cancer Research Frederick MD United States Physics Department University of Massachusetts Amherst MA United States

The quantity of information on nanomaterial properties and behavior continues to grow rapidly. Without a concerted effort to collect, organize and mine disparate information coming out of current research efforts, the value and effective use of this information will be limited at best. Data will not be translated to knowledge. At worst, erroneous conclusions will be drawn and future research may be misdirected. Nanoinformatics can be a powerful approach to enhance the value of global information in nanoscience and nanotechnology. Much progress has been made through grassroots efforts in nanoinformatics resulting in a multitude of resources and tools for nanoscience researchers. In 2012, the nanoinformatics community believed it was important to critically evaluate and refine currently available nanoinformatics approaches in order to best inform the science and support the future of predictive nanotechnology. The Greener Nano 2012: Nanoinformatics Tools and Resources Workshop brought together informatics groups with materials scientists active in nanoscience research to evaluate and reflect on the tools and resources that have recently emerged in support of predictive nanotechnology. The workshop goals were to establish a better understanding of current nanoinformatics approaches and to clearly define immediate and projected informatics infrastructure needs of the nanotechnology community. The theme of nanotechnology environmental health and safety (nanoEHS) was used to provide real-world, concrete examples on how informatics can be utilized to advance our knowledge and guide nanoscience. The benefit here is that the same properties that impact the performance of products could also be the properties that inform EHS. From a decision management standpoint, the dual use of such data should be considered a priority. Key outcomes include a proposed collaborative framework for data collection, data sharing and information integration. © 2013 IOP Publishing Ltd.

关键词： Data integration

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Compensation of unknown input dead zone using equivalent-input-disturbance approach

Compensation of unknown input dead zone using equivalent-inp...

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9th International Conference on Informatics in Control, Automation and Robotics, ICINCO 2012

作者： Ouyang, Liyu She, Jinhua Wu, Min Hashimoto, Hiroshi School of Information Science and Engineering Central South University Changsha 410083 China Hunan Engineering Laboratory for Advanced Control and Intelligent Automation Changsha 410083 China School of Computer Science Tokyo University of Technology Hachioji Tokyo 192-0982 Japan Master Program of Innovation for Design and Eng. Advanced Inst. of Industrial Tech. Shinagawa Tokyo 140-0011 Japan

ISBN: (纸本)9789898565211

This paper considers the problem of the compensation of an unknown dead zone in the input of a plant. A new compensation method is presented based on the estimation of an equivalent input disturbance (EID). Unlike other methods, this method does not require the exact information of a dead zone. First, we consider the dead zone as an input-dependent disturbance and employ an EID estimator to estimate it. Then, we incorporate the estimate in the control input and compensate the effect of the dead zone almost completely. Simulation results demonstrate the validity of the method. Copyright © 2012 SciTePress.

关键词： Dead zones

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