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International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： Kézia de Vasconcelos Oliveira Angelo Perkusich Kyller Costa Gorgônio Leandro Dias da Silva Aldenor Falcão Martins Center of Electrical Engineering and Informatics Federal University of Campina Grande Campina Grande Paraiba Brazil Computing Institute Federal University of Alagoas Maceio Alagoas Brazil Graduate Program in Electrical Engineering Federal University of Campina Grande Campina Grande Paraiba Brazil

The reliability on Safety Instrumented Systems (SIS) is critical for the safe operation of many industrial applications. In particular, SIS play an important role in oil and gas processing plants. SIS are responsible not only for the continuous operation of the plant, it also keeps the plant in a safe state, avoiding damages to the environment and minimizing risks to employees. Therefore, the correct behavior of such systems is an important goal to achieve when building industrial plants. Verification and testing of SIS programs is a very hard task to accomplish. This happens mainly for two reasons. First, testing the real system is very expensive and sometimes it may take a huge amount of time, weeks or even months. Second, those systems deal with a huge number of variables. It is not always possible for a human tester to check if all of them are correct when performing tests. Providing an automatic and formal testing approach for such systems is an important contribution for the development of such systems. In this work we introduce a new method for generating test cases for SIS programs running on programable Logic Controller (PLC). As we did on previous work, ISA 5.2 diagrams are used as specification of the systems, but now we are using a hardware-in-the-loop technique, and the target artifact is a software running on a PLC. To avoid the execution of redundant tests, we introduced a new test case generation algorithm that is based on equivalence classes. Finally, we discussed a study case in which our method is used to detect error, that were introduced on purpose, on a simple system.

关键词： Automata Testing Safety Valves Input variables Computational modeling Instruments

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Computer-aided instruction for introductory linear circuit analysis

Computer-aided instruction for introductory linear circuit a...

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Frontiers in Education (FIE) Conference

作者： B. J. Skromme P. J. Rayes C. D. Whitlatch Q. Wang A. Barrus J. M. Quick R. K. Atkinson T. S. Frank School of Electrical Computer and Energy Engrg. School of Computing Informatics and Decision Systems Engrg. Arizona State University Tempe AZ USA Engineering Program South Mountain Community College Phoenix AZ USA

A step-based tutoring system for linear circuit analysis is being developed with the capabilities to automatically generate circuit problems with specified characteristics, including randomly generated topologies and element values. The system further generates fully-worked, error-free solutions using the methods typically taught in such classes, and accepts a rich variety of student input such as equations, matrix equations, numerical and multiple-choice answers, re-drawn circuit diagrams, and sketches of waveforms. A randomized, controlled study was conducted using paid student volunteers to compare the effectiveness of two of our tutorials in comparison to working conventional textbook-based problems. The average learning gain was only 3/100 points for the textbook users, but 29/100 points, about 10 times higher, for the tutorial users. The effect size on the post-test scores was 1.21 pooled standard deviations (Cohen d-value) and was statistically significant. A motivational survey administered to these students yielded a 0.53 point higher rating for the software than for the textbook (on a 1-5 scale). The system is being used in Spring 2013 by over 340 students in EEE 202 at Arizona State and two community colleges. About 99% of these students rated the system as “very helpful” or “somewhat helpful”.

关键词： Equations Tutorials Software Materials Educational institutions Linear circuits Topology

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Frictional characteristics measurement of a ceramic aerostatic linear bearing 5

Frictional characteristics measurement of a ceramic aerostat...

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5th International Conference on Advanced Micro-Device engineering, AMDE 2013

作者： Kitabata, Kouki Iwashita, Hiroshi Takita, Akihiro Djamal, Mitra Pornsuwancharoen, Nithiroth Fujii, Yusaku Education Program of Electronics and Informatics Mathematics and Physics Graduate School of Science and Technology Gunma University 1-5-1 Tenjin-cho Kiryu Gunma376-8515 Japan Depatment of Electronics Graduate School of Engineering Gunma University 1-5-1 Tenjin-cho Kiryu Gunma376-8515 Japan Division of Mechanical Sience and Technology Graduate School of Tecnology Gunma University 1-5-1 Tenjin-cho Kiryu Gunma376-8515 Japan Theoretical High Energy Physics and Instrumentation Research Group Faculty of Mathematics and Natural Sciences Institut Teknologi Bandung Jl. Ganesa 10 Bandung40132 Indonesia Department of Electrical Engineering Faculty of Industry and Technology Rajamangala University of Technology Isan Sakonnakon47160 Thailand

ISBN: (纸本)9783038354659

The resultant force acting on the moving part of the ceramic aerostatic linear bearing is measured highly accurately as the inertial force of the moving part of the bearing by means of the levitation mass method (LMM). The measurement results of the ceramic aerostatic linear bearing and metal aerostatic linear bearing of different mass are compared. The regression equation of the ceramic aerostatic linear bearing and metal aerostatic linear bearing are calculated. The ceramic linear bearing and metal linear bearing have extremely small frictional force.. © (2015) Trans Tech Publications, Switzerland.

关键词： Aerodynamics

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Study of [Formula: see text] and [Formula: see text] production in [Formula: see text] collisions at [Formula: see text] and search for anomalous quartic gauge couplings with the ATLAS experiment

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The European physical journal. C, Particles and fields 2017年第9期77卷 646页

作者： M Aaboud G Aad B Abbott O Abdinov B Abeloos S H Abidi O S AbouZeid N L Abraham H Abramowicz H Abreu R Abreu Y Abulaiti B S Acharya S Adachi L Adamczyk J Adelman M Adersberger T Adye A A Affolder T Agatonovic-Jovin C Agheorghiesei J A Aguilar-Saavedra S P Ahlen F Ahmadov G Aielli S Akatsuka H Akerstedt T P A Åkesson E Akilli A V Akimov G L Alberghi J Albert P Albicocco M J Alconada Verzini S C Alderweireldt M Aleksa I N Aleksandrov C Alexa G Alexander T Alexopoulos M Alhroob B Ali M Aliev G Alimonti J Alison S P Alkire B M M Allbrooke B W Allen P P Allport A Aloisio A Alonso F Alonso C Alpigiani A A Alshehri M I Alstaty B Alvarez Gonzalez D Álvarez Piqueras M G Alviggi B T Amadio Y Amaral Coutinho C Amelung D Amidei S P Amor Dos Santos S Amoroso G Amundsen C Anastopoulos L S Ancu N Andari T Andeen C F Anders J K Anders K J Anderson A Andreazza V Andrei S Angelidakis I Angelozzi A Angerami A V Anisenkov N Anjos A Annovi C Antel M Antonelli A Antonov D J Antrim F Anulli M Aoki L Aperio Bella G Arabidze Y Arai J P Araque V Araujo Ferraz A T H Arce R E Ardell F A Arduh J-F Arguin S Argyropoulos M Arik A J Armbruster L J Armitage O Arnaez H Arnold M Arratia O Arslan A Artamonov G Artoni S Artz S Asai N Asbah A Ashkenazi L Asquith K Assamagan R Astalos M Atkinson N B Atlay K Augsten G Avolio B Axen M K Ayoub G Azuelos A E Baas M J Baca H Bachacou K Bachas M Backes M Backhaus P Bagnaia M Bahmani H Bahrasemani J T Baines M Bajic O K Baker E M Baldin P Balek F Balli W K Balunas E Banas A Bandyopadhyay Sw Banerjee A A E Bannoura L Barak E L Barberio D Barberis M Barbero T Barillari M-S Barisits J T Barkeloo T Barklow N Barlow S L Barnes B M Barnett R M Barnett Z Barnovska-Blenessy A Baroncelli G Barone A J Barr L Barranco Navarro F Barreiro J Barreiro Guimarães da Costa R Bartoldus A E Barton P Bartos A Basalaev A Bassalat R L Bates S J Batista J R Batley M Battaglia M Bauce F Bauer H S Bawa J B Beacham M D Beattie T Beau P H Beauchemin P Bechtle H P Beck H C Beck K Becker M Becker M Beckingham C Becot A J Beddall A Beddall Faculté des Sciences Université Mohamed Premier and LPTPM Oujda Morocco. CPPM Aix-Marseille Université and CNRS/IN2P3 Marseille France. Homer L. Dodge Department of Physics and Astronomy University of Oklahoma Norman OK USA. Institute of Physics Azerbaijan Academy of Sciences Baku Azerbaijan. LAL Univ. Paris-Sud CNRS/IN2P3 Université Paris-Saclay Orsay France. Department of Physics University of Toronto Toronto ON Canada. Santa Cruz Institute for Particle Physics University of California Santa Cruz Santa Cruz CA USA. Department of Physics and Astronomy University of Sussex Brighton UK. Raymond and Beverly Sackler School of Physics and Astronomy Tel Aviv University Tel Aviv Israel. Department of Physics Technion: Israel Institute of Technology Haifa Israel. Center for High Energy Physics University of Oregon Eugene OR USA. Department of Physics Stockholm University Stockholm Sweden. The Oskar Klein Centre Stockholm Sweden. INFN Gruppo Collegato di Udine Sezione di Trieste Udine Italy. ICTP Trieste Italy. International Center for Elementary Particle Physics and Department of Physics The University of Tokyo Tokyo Japan. Faculty of Physics and Applied Computer Science AGH University of Science and Technology Kraków Poland. Department of Physics Northern Illinois University DeKalb IL USA. Fakultät für Physik Ludwig-Maximilians-Universität München Munich Germany. Particle Physics Department Rutherford Appleton Laboratory Didcot UK. Institute of Physics University of Belgrade Belgrade Serbia. Department of Physics Alexandru Ioan Cuza University of Iasi Iasi Romania. Laboratório de Instrumentação e Física Experimental de Partículas-LIP Lisbon Portugal. Departamento de Fisica Teorica y del Cosmos and CAFPE Universidad de Granada Granada Spain. Department of Physics Boston University Boston MA USA. Joint Institute for Nuclear Research JINR Dubna Dubna Russia. INFN Sezione di Roma Tor Vergata Rome Italy. Dipartimento di Fisica Università di Roma

This paper presents a study of and triboson production using events from proton-proton collisions at a centre-of-mass energy of recorded with the ATLAS detector at the LHC and corresponding to an integrated luminosity of 20.2 fb . The production cross-section is determined using a final state containing an electron, a muon, a photon, and neutrinos ( ). Upper limits on the production cross-section of the final state and the and final states containing an electron or a muon, two jets, a photon, and a neutrino ( or ) are also derived. The results are compared to the cross-sections predicted by the Standard Model at next-to-leading order in the strong-coupling constant. In addition, upper limits on the production cross-sections are derived in a fiducial region optimised for a search for new physics beyond the Standard Model. The results are interpreted in the context of anomalous quartic gauge couplings using an effective field theory. Confidence intervals at 95% confidence level are derived for the 14 coupling coefficients to which and production are sensitive.

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Poster abstracts

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Sleep and Biological Rhythms 2016年第1期5卷 A1-A189页

作者： J. Ferrie M. Shipley F. Cappuccio E. Brunner M. Miller M. Kumari M. Marmot A. Coenen J. L. Castillo F. Araya G. Bustamante L. Montecino C. Torres S. Oporto J. Gronli E. Fiske R. Murison B. Bjorvatn E. Sorensen R. Ursin C. M. Portas S. Rajaraman A. Gribok N. Wesensten T. Balkin J. Reifman N. Dursunoglu S. Ozkurt S. Baser O. Delen S. Sarikaya P. Sadler P. Mitchell D. Françon M. Decobert B. Herve A. Richard G. Griebel P. Avenet B. Scatton G. L. Fur D. Eckert A. Jordan A. Wellman S. Smith A. Malhotra D. White D. Bruck I. Thomas A. Kritikos W. Oertel K. Stiasny-Kolster D. Garcia-Borreguero W. Poewe B. Hoegl R. Kohnen E. Schollmayer J. Keffel C. Trenkwalder A. Valle S. Roizenblatt F. Fregni P. Boggio S. Tufik K. Ward L. Robertson L. Palmer P. Eastwood D. Hillman J. Lee S. Mukherjee V. de Padova G. Barbato G. Ficca I. Zilli P. Salzarulo M. Veldi T. Hion V. Vasar M. Kull L. Nowak J. Davis Y. Latzer O. Tzischinsky S. Crowley M. Carskadon M. Anca-Herschkovitsch D. Frey J. Ortega C. Wiseman C. Farley K. Wright A. Campbell A. Neill K. Spiegel R. Leproult E. Tasali N. Scherberg E. van Cauter A. T. Noradina N. A. Karim I. Norlinah A. A. Raymond R. Sahathevan B. Hamidon E. Werth R. Poryazova R. Khatami C. Bassetti R. G. Beran L. Ainley G. Holand J. Duncan H. Kinney B. Davis B. Hood S. Frey C. Schmidt M. Hofstetter P. Peigneux C. Cajochen W.-P. Hu J.-D. Li C. Zhang L. Boehmer J. Siegel Q.-Y. Zhou Y. Sagawa H. Kondo T. Takemura H. Kanayama Y. Kaneko M. Sato T. Kanbayashi Y. Hishikawa T. Shimizu A. Viola L. James L. Schlangen D.-J. Dijk R. Andretic Y.-C. Kim K.-A. Han F. Jones R. Greenspan L. Sanford L. Yang X. Tang K. Dieter E. Uta H. Sven M. Richard N. Oyane S. Pallesen F. Holsten Y. Inoue M. Fujita N. Emura K. Kuroda N. Uchimura A. Johnston J. Astbury G. Kennedy K. Hoedlmoser M. Schabus T. Pecherstorfer S. Moser G. Gruber P. Anderer W. Klimesch N. Naidoo M. Ferber A. Pack D. Neu O. Mairesse G. Hoffmann A. Dris L. Lambrecht P. Linkowski P. Verbanck O. Le Bon N. Matsuura M. Yamao N. Adachi R. Aritomi Y. Komada H. Tanaka S. Shirak University College London London UK University College London London USA Warwick Medical School London UK Warwick Medical School Coventry USA Radboud University Nijmegen Nijmegen Netherlands Department of Neurology University of Chile Santiago Chile Neurology Service Hospital del Salvador Santiago Chile Family Health Center Juan Pablo II Santiago Chile Department of Biomedicine Section on Physiology Univeristy of Bergen Bergen Norway Department of Public Health and Primary Health Care Univeristy of Bergen Bergen Norway Department of Public Health and Primary Health Care University of Bergen Bergen Norway Norwegian Competence Center for Sleep Disorders Haukeland University Hospital Bergen Norway Department of Child and Adolescent Psychiatry Haukeland University Hospital Univeristy of Bergen Bergen Norway Department of Biomedicine University of Bergen Bergen Norway US Army Medical Research and Materiel Command Fort Detrick Frederick USA Walter Reed Army Institute of Research Silver Spring USA Department of Behavioral Biology Walter Reed Army Institute of Research Silver Spring USA Faculty Department of Pulmonology Pamukkale University Medical Denizli Turkey University of Ballarat Ballarat Australia Sanofi-Aventis Recherche et Developpement Paris France Brigham and Women’s Hospital Harvard Medical School Boston USA The University of Queensland Adelaide Australia School of Psychology University of Queensland Brisbane Australia The University of Queensland Brisbane Australia Victoria University Melbourne Australia Department of Psychology Victoria University Melbourne Australia School of Psychology Victoria University Melbourne Australia Philips-Universität Marburg Germany Philips-Universitaet-Marburg Marburg Germany Instituto de Investigaciones del Sueno Madrid Spain Universitätsklinik für Neurologie Innsbruck Austria Universitaetsklinik fuer Neurologie Innsbruck Austria IMEREM GmbH Nuernberg Germany Schwarz Pharma AG Monheim Germany

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Proceedings of the 3rd IPLeiria's International Health Congress Abstracts

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BMC HEALTH SERVICES RESEARCH 2016年第3期16卷 111-242页

作者： [Anonymous] Health Sciences Research Unit: Nursing Collegue of College of Health Technology of Coimbra Coimbra Portugal Sisters Hospitallers of the Sacred Heart of Jesus Casa de Saúde Rainha Santa Isabel Coimbra Portugal Research Unit for Sport and Physical Activity Faculty of Sport Sciences and Physical Education University of Coimbra Coimbra Portugal Complementary Sciences- INESCC Coimbra Portugal CUF Hospitals Lisbon Portugal Breast Unit Champalimaud Clinical Center Lisbon Portugal Swiss Centre for Medical Simulation & Swiss Association of Simulation in Healthcare Basel Switzerland Basel University Hospital Basel Switzerland HELPO Association Cascais Portugal Centro de Linguística Universidade de Lisboa Lisboa Portugal Centro Superior de Estudios Universitarios La Salle Madrid Spain Universidade da Madeira Funchal Portugal Serviço de Saúde da Região Autónoma da Madeira E.P.E. Funchal Portugal Escola Superior de Enfermagem de Lisboa Lisboa Portugal Instituto Superior Miguel Torga Coimbra Portugal Centro de Investigação do Núcleo de Estudos e Intervenção Cognitivo Comportamental Universidade de Coimbra Coimbra Portugal Escola Superior de Saúde de Leiria & Unidade de Investigação em Saúde Instituto Politécnico de Leiria Leiria Portugal National School of Public Health & Centro de Investigação em Saúde Pública Universidade Nova de Lisboa Lisboa Portugal Agrarian Superior School Polytechnic Institute of Viseu Viseu Portugal Laboratory of Microbiology Department of Biological Sciences Faculty of Pharmacy University of Porto Porto Portugal Unit for Multidisciplinary Biomedical Research Institute of Biomedical Sciences Abel Salazar University of Porto Porto Portugal Agrupamento de Centros de Saúde (ACES) Baixo Mondego Figueira da Foz Portugal Universidade de Trás-os-Montes e Alto Douro Vila Real Portugal Centro de Salud La Paz Badajoz España Centro de Salud San Fernando Badajoz España Complejo Hospitalario Universitario de Badajoz Badajoz España Hospital Don Beni

S1 Health literacy and health education in adolescence Catarina Cardoso Tomás S2 The effect of a walking program on the quality of life and well-being of people with schizophrenia Emanuel Oliveira, D. Sousa, M. Uba-Chupel, G. Furtado, C. Rocha, A. Teixeira, P. Ferreira S3 Diagnosis and innovative treatments - the way to a better medical practice Celeste Alves S4 Simulation-based learning and how it is a high contribution Stefan Gisin S5 Formative research about acceptability, utilization and promotion of a home fortification programme with micronutrient powders (MNP) in the Autonomous Region of Príncipe, São Tomé and Príncipe Elisabete Catarino, Nelma Carvalho, Tiago Coucelo, Luís Bonfim, Carina Silva S6 Safety culture of the patient: a reflexion about the therapeutic approach on the patient with vocal pathology Débora Franco S7 About wine, fortune cookies and patient experience Jesús Alcoba González O1 The psychological impact on the emergency crews after the disaster event on February 20, 2010 Helena G. Jardim, Rita Silva O2 Musculoskeletal disorders in midwives Cristina L. Baixinho, Mª Helena Presado, Mª Fátima Marques, Mário E. Cardoso O3 Negative childhood experiences and fears of compassion: Implications for psychological difficulties in adolescence Marina Cunha, Joana Mendes, Ana Xavier, Ana Galhardo, Margarida Couto O4 Optimal age to give the first dose of measles vaccine in Portugal João G. Frade, Carla Nunes, João R. Mesquita, Maria S. Nascimento, Guilherme Gonçalves O5 Functional assessment of elderly in primary care Conceição Castro, Alice Mártires, Mª João Monteiro, Conceição Rainho O6 Smoking and coronary events in a population of Spanish health-care centre: An observational study Francisco P. Caballero, Fatima M. Monago, Jose T. Guerrero, Rocio M. Monago, Africa P. Trigo, Milagros L. Gutierrez, Gemma M. Milanés, Mercedes G. Reina, Ana G. Villanueva, Ana S. Piñero, Isabel R. Aliseda, Francisco B. Ramirez O7 Prevalence of musculoskeletal injuries in Por

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A Heuristic Rule Reduction Approach to Software Fault-proneness Prediction

A Heuristic Rule Reduction Approach to Software Fault-pronen...

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Asia-Pacific Conference on Software engineering

作者： Akito Monden Jacky Keung Shuji Morisaki Yasutaka Kamei Ken-Ichi Matsumoto Graduate School of Information Science Nara Institute of Science and Technology Ikoma Nara Japan Department of Computing Hong Kong Polytechnic University Hong Kong China Faculty of Informatics Shizuoka University Hamamatsu Shizuoka Japan Graduate School and Faculty of Information Science and Electrical Engineering Kyushu University Fukuoka Japan

Background: Association rules are more comprehensive and understandable than fault-prone module predictors (such as logistic regression model, random forest and support vector machine). One of the challenges is that there are usually too many similar rules to be extracted by the rule mining. Aim: This paper proposes a rule reduction technique that can eliminate complex (long) and/or similar rules without sacrificing the prediction performance as much as possible. Method: The notion of the method is to removing long and similar rules unless their confidence level as a heuristic is high enough than shorter rules. For example, it starts with selecting rules with shortest length (length=1), and then it continues through the 2nd shortest rules selection (length=2) based on the current confidence level, this process is repeated on the selection for longer rules until no rules are worth included. Result: An empirical experiment has been conducted with the Mylyn and Eclipse PDE datasets. The result of the Mylyn dataset showed the proposed method was able to reduce the number of rules from 1347 down to 13, while the delta of the prediction performance was only. 015 (from. 757 down to. 742) in terms of the F1 prediction criteria. In the experiment with Eclipsed PDE dataset, the proposed method reduced the number of rules from 398 to 12, while the prediction performance even improved (from. 426 to. 441.) Conclusion: The novel technique introduced resolves the rule explosion problem in association rule mining for software proneness prediction, which is significant and provides better understanding of the causes of faulty modules.

关键词： Measurement Association rules Explosions Software Predictive models Educational institutions

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Gaussian process for dimensionality reduction in transfer learning

Gaussian process for dimensionality reduction in transfer le...

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11th SIAM International Conference on Data Mining, SDM 2011

作者： Tong, Bin Gao, Junbin Thach, Nguyen Huy Suzuki, Einoshin Graduate School of Systems Life Sciences Kyushu University Japan School of Computing and Mathematics Charles Sturt University Australia Department of Informatics Graduate School of Information Science and Electrical Engineering Kyushu University Japan

ISBN: (纸本)9780898719925

Dimensionality reduction has been considered as one of the most significant tools for data analysis. In general, supervised information is helpful for dimensionality reduction. However, in typical real applications, supervised information in multiple source tasks may be available, while the data of the target task are unlabeled. An interesting problem of how to guide the dimensionality reduction for the unlabeled target data by exploiting useful knowledge, such as label information, from multiple source tasks arises in such a scenario. In this paper, we propose a new method for dimensionality reduction in the transfer learning setting. Unlike traditional paradigms where the useful knowledge from multiple source tasks is transferred through distance metric, our proposal firstly converts the dimensionality reduction problem into integral regression problems in parallel. Gaussian process is then employed to learn the underlying relationship between the original data and the reduced data. Such a relationship can be appropriately transferred to the target task by exploiting the prediction ability of the Gaussian process model and inventing different kinds of regularizers. Extensive experiments on both synthetic and real data sets show the effectiveness of our method. Copyright © SIAM.

关键词： Gaussian noise (electronic)

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Reports of the AAAI 2011 conference workshops

Reports of the AAAI 2011 conference workshops

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作者： Agmon, Noa Agrawal, Vikas Aha, David W. Aloimonos, Yiannis Buckley, Donagh Doshi, Prashant Geib, Christopher Grasso, Floriana Green, Nancy Johnston, Benjamin Kaliski, Burt Kiekintveld, Christopher Law, Edith Lieberman, Henry Mengshoel, Ole J. Metzler, Ted Modayil, Joseph Oard, Douglas W. Onder, Nilufer O'Sullivan, Barry Pastra, Katerina Precup, Doina Ramachandran, Sowmya Reed, Chris Sariel-Talay, Sanem Selker, Ted Shastri, Lokendra Singh, Satinder Smith, Stephen F. Srivastava, Siddharth Sukthankar, Gita Uthus, David C. Williams, Mary-Anne Department of Computer Science University of Texas at Austin United States Center for Knowledge Driven Information Systems Infosys Labs India Adaptive Systems Section Naval Research Laboratory Washington DC United States Department of Computer Science University of Maryland College Park United States EMC's Center of Excellence in Ireland Research Europe at EMC Ireland Department of Computer Science University of Georgia United States School of Informatics University of Edinburgh United Kingdom Department of Computer Science University of Liverpool United Kingdom Department of Computer Science University of North Carolina Greensboro United States Faculty of Engineering and Information Technology University of Technology Sydney Australia VeriSign Inc. United States Department of Computer Science University of Texas at El Paso United States Machine Learning Department Carnegie Mellon University United States Massachusetts Institute of Technology Media Laboratory United States Carnegie Mellon University's Silicon Valley Campus United States Darrell W. Hughes Program for Religion and Science Dialogue Oklahoma City University United States Department of Computing Science University of Alberta Canada College of Information Studies Institute for Advanced Computer Studies University of Maryland College Park United States Department of Computer Science Michigan Technological University United States Department of Computer Science University College Cork Ireland Cognitive Systems Research Insitute Athens Greece School of Computer Science McGill University Canada Stottler Henke Inc. United States School of Computing University of Dundee United Kingdom Department of Computer Engineering Istanbul Technical University Turkey Convergence Lab Infosys Technologies Ltd. United States Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor United States Robotics Institute Carnegie Mellon University United States University of Wisconsin

The AAAI-11 workshop program was held Sunday and Monday, August 7-18, 2011, at the Hyatt Regency San Francisco in San Francisco, California USA. The AAAI-11 workshop program included 15 workshops covering a wide range of topics in artificial intelligence. The titles of the workshops were Activity Context Representation: Techniques and Languages;Analyzing Microtext;Applied Adversarial Reasoning and Risk Modeling;Artificial Intelligence and Smarter Living: The Conquest of Complexity;Artifiicial Intelligence for Data Center Management and Cloud computing;Automated Action Planning for Autonomous Mobile Robots;Computational Models of Natural Argument;Generalized Planning;Human Computation;Human-Robot Interaction in Elder Care;Interactive Decision Theory and Game Theory, 2010;Language-Action Tools for Cognitive Artificial Agents: Integrating Vision, Action, and Language;Lifelong Learning from Sensorimotor Experience;Plan, Activity, and Intent Recognition;and Scalable Integration of Analytics and Visualization. This article presents short summaries of those events. Copyright © 2012, Association for the Advancement of Artificial Intelligence. All rights reserved.

关键词： Human robot interaction

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How multiple concurrent users react to a quiz agent attentive to the dynamics of their game participation

How multiple concurrent users react to a quiz agent attentiv...

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9th International Joint Conference on Autonomous Agents and Multiagent Systems 2010, AAMAS 2010

作者： Huang, Hung-Hsuan Furukawa, Takuya Ohashi, Hiroki Nishida, Toyoaki Cerekovic, Aleksandra Pandzic, Igor S. Nakano, Yukiko Graduate School of Informatics Kyoto University Japan Faculty of Electrical Engineering and Computing University of Zagreb Croatia Department of Computer and Information Science Seikei University Japan

ISBN: (纸本)9781617387715

This paper presents a quiz game agent who is attentive to the dynamics of multiple concurrent participants. The attentiveness of this agent is meant to be achieved by an utterance policy that determines the nature of the utterance and whether, when, and to whom to utter. Two heuristics are introduced to drive the policy: the interaction atmosphere (AT) of the participants and the participant who tends to lead the conversation (CLP) at a specifi time point. They are estimated from the activeness of the participants' face movements and acoustic information during their discussion of the answer. In order to the inherent drawback of a 2D agent that makes it difficult for multiple concurrent users to distinguish the focus of its attention, a physical pointer is also introduced. This system is then evaluated using questionnaire investigation and video data analysis. The joint results of the experiments indicated that the methods for estimating AT and CLP worked. The participants pay more attention to the agent and participate in the game more actively if the indication of the pointer is more comprehensive. Copyright © 2010, International Foundation for Autonomous Agents and Multiagent Systems (***). All rights reserved.

关键词： Virtual reality

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