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International Symposium on Collaborative Technologies and Systems

作者： Obinna B. Anya John V. Carlis Brent J. Hecht Daniel Keefe Obinna Anya Neale R. Chumbler Saif Khairat Joseph A. Konstan Danilo Pani Jason Evgenides Janet Girton Arlene King Joseph Zahn Gregory Padula Mary Galvin Accelerated Discovery Lab Almaden Research Center California USA University of Minnesota - Twin Cities Minnesota USA Department of Health Policy and Management College of Public Health University of Georgia - Athens Georgia USA Institute for Health Informatics University of Minnesota - Twin Cities Minnesota USA Department of Computer Science and Engineering University of Minnesota - Twin Cities Minnesota USA EOLAB - Microelectronics and Bioengineering Lab Dept. of Electrical and Electronic Engineering University of Cagliari Italy Organizational Enablement Shiloh Illinois USA Cyber Semantics Shiloh Illinois USA Strategic Communication C5T Shiloh Illinois USA Knowledge Management Specialist C5T Shiloh Illinois USA Vice President-Operations C5T Shiloh Illinois USA LexisNexis Special Services Inc. (LNSSI) Washington D.C. USA

This panel explores the many roles of data analytics in today's cross-domain collaborations. In some instances, cross-domain analytics are required to understand big data. In others, big data holds the key to understanding and evaluating how people collaborate across domains. Panelists will present their experiences with big data and collaboration, and discussion will be guided by the following questions: How does “understanding data through collaboration” relate to “understanding collaboration through data”? What modeling tools, visualizations, abstractions, and metrics can help facilitate collaborative discovery from big data? To what extent should these tools be tailored to specific domains or groups? How much do we need to know about another domain or group before we can intersect domain specific activities that constitute the context to various analytical processes, and cross-pollinate ideas for deeper analytics? What optimally would that other domain or group need to know about us? How much of this knowledge can we extract from data?

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A self-organized, service-oriented GMPLS optical network testbed

A self-organized, service-oriented GMPLS optical network tes...

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8th International ICST Conference on Testbeds and research Infrastructures: Development of Networks and Communities, TridentCom 2012

作者： Siokis, Apostolis Vlachos, Kyriakos Computer Engineering and Informatics Dept. Computer Technology Institute and Press University of Patras GR26500 Rio Patras Greece

ISBN: (纸本)9783642355752

In this paper, we detail the implementation of a self-organized GMPLS network using the DRAGON software suite to introduce service awareness in a GMPLS network. DRAGON daemon has been extended to support anycast routing to allow forwarding user (service) requests to the most suitable servers based on their advertised service attributes. Furthermore, OSPF daemon has been also extended to allow for these advertisements to propagate through the network and modify shortest paths based on these service attributes that can be network (i.e. bandwidth, delay etc) and non-network (storage capacity, CPU units, availability etc) resources. © 2012 ICST institute for computer Science, Social informatics and Telecommunications engineering.

关键词： Network routing

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Transferring evolved reservoir features in reinforcement learning tasks

Transferring evolved reservoir features in reinforcement lea...

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9th European Workshop on Reinforcement Learning, EWRL 2011

作者： Chatzidimitriou, Kyriakos C. Partalas, Ioannis Mitkas, Pericles A. Vlahavas, Ioannis Dept. of Electrical and Computer Engineering Aristotle University of Thessaloniki Greece Informatics and Telematics Institute Centre for Research and Technology Hellas Greece Dept. of Informatics Aristotle University of Thessaloniki Greece

ISBN: (纸本)9783642299452

The major goal of transfer learning is to transfer knowledge acquired on a source task in order to facilitate learning on another, different, but usually related, target task. In this paper, we are using neuroevolution to evolve echo state networks on the source task and transfer the best performing reservoirs to be used as initial population on the target task. The idea is that any non-linear, temporal features, represented by the neurons of the reservoir and evolved on the source task, along with reservoir properties, will be a good starting point for a stochastic search on the target task. In a step towards full autonomy and by taking advantage of the random and fully connected nature of echo state networks, we examine a transfer method that renders any inter-task mappings of states and actions unnecessary. We tested our approach and that of inter-task mappings in two RL testbeds: the mountain car and the server job scheduling domains. Under various setups the results we obtained in both cases are promising. © 2012 Springer-Verlag.

关键词： Stochastic systems

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On Achieving All-Optical Failure Restoration via Monitoring Trails

On Achieving All-Optical Failure Restoration via Monitoring ...

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IEEE INFOCOM Conference

作者： Janos Tapolcai Pin-Han Ho Peter Babarczi Lajos Ronyai MTA-BME Future Internet Research Group High-Speed Networks Laboratory (HSNLab) Dept. of Telecommunications and Media Informatics Budapest University of Technology Dept. of Electrical and Computer Engineering University of Waterloo Canada Computer and Automation Research Institute Hungarian Academy of Sciences and BME

ISBN: (纸本)9781467359443

The paper investigates a novel monitoring trail (m-trail) scenario that can enable any shared protection scheme for achieving all-optical and ultra-fast failure restoration. Given a set of working (W-LPs) and protection (P-LPs) lightpaths, we firstly define the neighborhood of a node, which is a set of links whose failure states should be known to the node in restoration of the corresponding W-LPs. A set of m-trails is routed such that each node can localize any failure in its neighborhood according to the ON-OFF status of the traversing m-trails. Bound analysis is performed on the minimum bandwidth required for the m-trails. Extensive simulation is conducted to verify the proposed scheme.

关键词： Line of nodes restoration trails bandwidth requirement

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Enhancing automatic detection of frustration induced during HCI with moment-based biosignal features

Enhancing automatic detection of frustration induced during ...

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5th International Conference on Advances in computer-Human Interactions, ACHI 2012

作者： Giakoumis, Dimitris Tzovaras, Dimitrios Hassapis, George Centre for Research and Technology Hellas Informatics and Telematics Institute Thessaloniki Greece Dept. of Electrical and Computer Engineering Aristotle University of Thessaloniki Greece

ISBN: (纸本)9781612081779

Enhancing HCI systems with the capability to detect user's frustration and respond appropriately is a significant challenge. In this line, biosignal features based on the theory of orthogonal Krawtchouk and Legendre moments are assessed in the present work over their ability to enhance accuracy in automatic detection of frustration, which is induced through HCI, during video-game playing. Experimental evaluation, conducted over a multi-subject dataset over frustration detection showed that conventional features, typically extracted from Galvanic Skin Response and Electrocardiogram in the past, achieved correct classification rate (CCR) of 83.59%. Fusing these conventional features with moment-based ones extracted from the same modalities resulted to significantly higher accuracy, at the level of 93%. Furthermore, moment-based features lead also to over 10% increase in CCR when the aim was to identify both bored and frustrated cases, within a 3-classs affect detection problem. Copyright © IARIA, 2012.

关键词： Human computer interaction

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Erratum to: Measurement of the inclusive jet cross-section in proton-proton collisions at s = 7 TeV using 4.5 fb −1 of data with the ATLAS detector

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Journal of High Energy Physics 2015年第9期2015卷 1-39页

作者： G. Aad B. Abbott J. Abdallah S. Abdel Khalek O. Abdinov R. Aben B. Abi M. Abolins O. S. AbouZeid H. Abramowicz H. Abreu R. Abreu Y. Abulaiti B. S. Acharya L. Adamczyk D. L. Adams J. Adelman S. Adomeit T. Adye T. Agatonovic-Jovin J. A. Aguilar-Saavedra M. Agustoni S. P. Ahlen F. Ahmadov G. Aielli H. Akerstedt T. P. A. Åkesson G. Akimoto A. V. Akimov G. L. Alberghi J. Albert S. Albrand M. J. Alconada Verzini M. Aleksa I. N. Aleksandrov C. Alexa G. Alexander G. Alexandre T. Alexopoulos M. Alhroob G. Alimonti L. Alio J. Alison B. M. M. Allbrooke L. J. Allison P. P. Allport J. Almond A. Aloisio A. Alonso F. Alonso C. Alpigiani A. Altheimer B. Alvarez Gonzalez M. G. Alviggi K. Amako Y. Amaral Coutinho C. Amelung D. Amidei S. P. Amor Dos Santos A. Amorim S. Amoroso N. Amram G. Amundsen C. Anastopoulos L. S. Ancu N. Andari T. Andeen C. F. Anders G. Anders K. J. Anderson A. Andreazza V. Andrei X. S. Anduaga S. Angelidakis I. Angelozzi P. Anger A. Angerami F. Anghinolfi A. V. Anisenkov N. Anjos A. Annovi A. Antonaki M. Antonelli A. Antonov J. Antos F. Anulli M. Aoki L. Aperio Bella R. Apolle G. Arabidze I. Aracena Y. Arai J. P. Araque A. T. H. Arce J-F. Arguin S. Argyropoulos M. Arik A. J. Armbruster O. Arnaez V. Arnal H. Arnold M. Arratia O. Arslan A. Artamonov G. Artoni S. Asai N. Asbah A. Ashkenazi B. Åsman L. Asquith K. Assamagan R. Astalos M. Atkinson N. B. Atlay B. Auerbach K. Augsten M. Aurousseau G. Avolio G. Azuelos Y. Azuma M. A. Baak A. Baas C. Bacci H. Bachacou K. Bachas M. Backes M. Backhaus J. Backus Mayes E. Badescu P. Bagiacchi P. Bagnaia Y. Bai T. Bain J. T. Baines O. K. Baker P. Balek F. Balli E. Banas Sw. Banerjee A. A. E. Bannoura V. Bansal H. S. Bansil L. Barak S. P. Baranov E. L. Barberio D. Barberis M. Barbero T. Barillari M. Barisonzi T. Barklow N. Barlow B. M. Barnett R. M. Barnett Z. Barnovska A. Baroncelli G. Barone A. J. Barr F. Barreiro J. Barreiro Guimarães da Costa R. Bartoldus A. E. Barton P. Bartos V. Bartsch A. Bassalat A. Basye R. L. Bates J. R. Batley M. Battaglia M. Battistin F. Bauer H CPPM Aix-Marseille Université and CNRS/IN2P3 Marseille France Homer L. Dodge Department of Physics and Astronomy University of Oklahoma Norman United States Institute of Physics Academia Sinica Taipei Taiwan LAL Université Paris-Sud and CNRS/IN2P3 Orsay France Institute of Physics Azerbaijan Academy of Sciences Baku Azerbaijan Nikhef National Institute for Subatomic Physics and University of Amsterdam Amsterdam Netherlands Department of Physics Oklahoma State University Stillwater United States Department of Physics and Astronomy Michigan State University East Lansing United States Department of Physics University of Toronto Toronto Canada 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 CERN Geneva Switzerland 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 Department of Physics King’s College London London United Kingdom AGH University of Science and Technology Faculty of Physics and Applied Computer Science Krakow Poland Physics Department Brookhaven National Laboratory Upton United States Department of Physics Yale University New Haven United States Fakultät für Physik Ludwig-Maximilians-Universität München München Germany Particle Physics Department Rutherford Appleton Laboratory Didcot United Kingdom Institute of Physics University of Belgrade Belgrade Serbia Laboratorio de Instrumentacao e Fisica Experimental de Particulas - LIP Lisboa Portugal Departamento de Fisica Teorica y del Cosmos and CAFPE Universidad de Granada Granada Spain Albert Einstein Center for Fundamental Physics and Laboratory for High Energy Physics University of Bern Bern Switzerland Department of Physics Boston University Boston United States Joint Institute for Nuclear Research JINR Dubna Dubna Russia INFN

It was found that the non-perturbative corrections calculated using Pythia with the Perugia 2011 tune did not include the effect of the underlying event. The affected correction factors were recomputed using the Pythia 6.427 generator. These corrections are applied as baseline to the NLO pQCD calculations and thus the central values of the theoretical predictions have changed by a few percent with the new corrections. This has a minor impact on the agreement between the data and the theoretical predictions. Figures 2 and 6 to 13, and all the tables have been updated with the new values. A few sentences in the discussion in sections 5.2 and 9 were altered or removed.

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Question generation for adaptive assessment for student knowledge modeling in probabilistic domains

Question generation for adaptive assessment for student know...

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20th Conference on User Modeling, Adaptation, and Personalization, UMAP 2012

作者： Khodeir, Nabila Wanas, Nayer Darwish, Nevin Hegazy, Nadia Informatics Dept. Electronics Research Institute Tahrir St. Giza Egypt Dept. of Computer Engineering Faculty of Engineering Cairo University Giza Egypt

In this paper a question generation approach for adaptive assessment is purposed to estimate the student knowledge model in a probabilistic domain within an intelligent tutoring system. Assessing questions are generated adaptively according to the student knowledge based on two factors (i) the student misconceptions that are entailed in the student knowledge model, and (ii) the information gain maximizing. Updating and verification of the student model are conducted based on the matching between the student's and model answers to assessing questions. Comparison between using the adapted questions and random questions is investigated. Results suggest that utilizing adapted generated questions increases the approximation accuracy of the student model by 40% in addition to decreasing of the required assessing questions by 50% compared to using fixed questions.

关键词： Students

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An application-oriented review of CogInfoCom: The state-of-the-art and future perspectives

An application-oriented review of CogInfoCom: The state-of-t...

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10th IEEE Jubilee International Symposium on Applied Machine Intelligence and informatics, SAMI 2012

作者： Csapo, Adam Baranyi, Peter Budapest University of Technology and Economics Dept. of Telecommunications and Media Informatics Budapest Hungary Computer and Automation Research Institute Budapest Hungary

ISBN: (纸本)9781457701979

Cognitive Infocommunications (CogInfoCom) is an emerging discipline that investigates synergies between infocommunications and the cognitive sciences, with the goal of creating engineering applications in which systems with various levels of cognitive capability are enabled to work together more effectively. While infocommunications deals with the error-free encoding, transmission and decoding of raw data, CogInfoCom aims to transmit information at a higher, conceptual level in a way that appeals to the receiver's cognitive capabilities. Thus, CogInfoCom may have implications for a wide variety of fields in the future, including virtual reality, 3D Internet and Internet of Things. In this paper, we provide a brief, application-oriented overview of the existing background of CogInfoCom, and outline future perspectives for the field. © 2012 IEEE.

关键词： Virtual reality

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ESICM LIVES 2016: part two

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Intensive Care Medicine Experimental 2016年第1期4卷 205-404页

作者： S. Sivakumar F. S. Taccone K. A. Desai C. Lazaridis M. Skarzynski M. Sekhon W. Henderson D. Griesdale L. Chapple A. Deane L. Williams R. Strickland K. Lange D. Heyland M. Chapman M. J. Rowland P. Garry J. Westbrook R. Corkill C. A. Antoniades K. T. Pattinson G. Fatania A. J. Strong R. B. Myers C. M. Jermaine C. S. Robertson C. G. Rusin J. Hofmeijer L. Sondag M. C. Tjepkema-Cloostermans A. Beishuizen F. H. Bosch M. J. A. M. van Putten L. Carteron C. Patet D. Solari M. Oddo M. A. Ali C. Dias R. Almeida A. Vaz-Ferreira J. Silva E. Monteiro A. Cerejo A. P. Rocha A. A. Elsayed A. M. Abougabal B. N. Beshey K. M. Alzahaby S. Pozzebon A. Blandino Ortiz S. Cristallini O. Lheureux A. Brasseur J. L. Vincent J. Creteur M. Hravnak K. Yousef Y. Chang E. Crago R. M. Friedlander S. A. Abdelmonem S. A. Tahon T. A. Helmy H. S. Meligy F. Puig I. Dunn-Siegrist J. Pugin S. Gupta D. Govil S. Srinivasan S. J. Patel J. K. N A. Gupta D. S. Tomar M. Shafi R. Harne D. P. Arora N. Talwar S. Mazumdar E. E. Papakrivou D. Makris E. Manoulakas B. Tsolaki B. Karadodas E. Zakynthinos I. Palacios Garcia A. Diaz Martin V. Sanchez Encinares M. Pachón Ibañez J. Garnacho Montero G. Labrador T. Cebrero Cangueiro V. Poulose J. Koh J. W. Kam H. Yeter A. Kara O. Aktepe A. Topeli I. Tsolakoglou G. Intas P. Stergiannis A. A. Kolaros E. Chalari E. Athanasiadou A. Martika G. Fildisis V. Faivre C. Mengelle B. Favier D. Payen A. Poppe M. S. Winkler E. Mudersbach J. Schreiber M. L. Wruck E. Schwedhelm S. Kluge C. Zöllner T. Tavladaki A. M. Spanaki H. Dimitriou E. Kondili C. Choulaki E. Meleti D. Kafetzopoulos D. Georgopoulos G. Briassoulis A. García-de la Torre M. V. de la Torre-Prados T. Tsvetanova-Spasova P. Nuevo-Ortega C. Rueda-Molina A. Fernández-Porcel E. Camara-Sola L. Salido-Díaz A. García-Alcántara D. E. Meleti B. Suberviola J. Riera L. Rellan M. Sanchez J. C. Robles E. Lopez R. Vicente E. Miñambres M. Santibañez M. Le Guen J. Moore N. Mason M. Windpassinger O. Plattner E. Mascha D. I. Sessler Outcomes research U. Melia J. Fontanet J. P. van den Berg M. Baylor College of Medicine Neurology/Neurocritical Care Houston USA Erasmus Hospital Intensive Care Medicine Brussels Belgium Centre Hospitalier Régional Orléans Réaimation Médicale Orléans France University of British Columbia Vancouver Canada University of Adelaide Discipline of Acute Care Medicine Adelaide Australia Royal Adelaide Hospital Intensive Care Adelaide Australia Griffith University Menzies Health Institute of Queensland Gold Coast Australia University of Adelaide Discipline of Medicine Adelaide Australia Kingston General Hospital Clinical Evaluation Research Unit Kingston Canada University of Oxford Nuffield Department of Clinical Neurosciences Oxford UK Oxford University Hospitals NHS Foundation Trust Neurosciences Intensive Care Unit Oxford UK King’s College Hospital Department of Neurosurgery London UK King’ College London Institute of Psychiatry Psychology and Neuroscience Department of Clinical Neuroscience London UK Rice University Computer Science Houston USA Baylor College of Medicine Neurosurgery Houston USA Baylor College of Medicine Pediatric Cardiology Houston USA University of Twente Clinical Neurophysiology Enschede Netherlands Rijnstate Hospital Neurology Arnhem Netherlands Medical Spectrum Twente Clinical Neurophysiology Enschede Netherlands Medical Spectrum Twente Intensive Care Enschede Netherlands Rijnstate Hospital Intensive Care Arnhem Netherlands CHUV Department of Intensive Care Medicine Neuroscience Critical Care Research Group Lausanne Switzerland Aga Khan University Hospital Anaesthesiology Karachi Pakistan Centro Hospitalar São João Intensive Care Porto Portugal Faculty of Medicine University of Porto Medicine Porto Portugal Faculdade de Ciências Universidade do Porto Departamento de Matemática Porto Portugal Centro de Matemática Universidade do Porto Porto Portugal The Biomedical Research Networking Center in Bioengineering Biomaterials and Nanomedicine Zaragoza Spain Centro Hospitalar

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Introducing agent evictions to improve application placement in wireless distributed systems

Introducing agent evictions to improve application placement...

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41st International Conference on Parallel Processing, ICPP 2012

作者： Tziritas, Nikos Lampsas, Petros Lalis, Spyros Loukopoulos, Thanasis Khan, Samee Ullah Xu, Cheng-Zhong Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518067 China Dept. of Informatics and Computer Technology Technological Educational Institute of Lamia Lamia Greece Computer and Communication Engineering Dept. University of Thessaly Volos Greece Department of Electrical and Computer Engineering North Dakota State University Fargo ND 58108-6050 United States Department of Electrical and Computer Engineering Wayne State University Detroit MI 48202 United States Center for Research and Technology Institute of Thessaly Volos Greece

ISBN: (纸本)9780769547961

With the development of mobile code frameworks for embedded systems, an application can be structured as a set of cooperating components (agents) that are placed on the nodes of the system in a flexible way. Reducing the network traffic caused by the application components is a crucial issue for the increase in the lifetime of wireless embedded systems, since it is widely known that the communication cost plays the most significant role in the energy consumption of embedded devices. To this end, most placement algorithms place or move an agent towards the center of gravity of the communication workload. However, if the target node does not have enough capacity, the attempt is usually aborted. In this paper, we introduce eviction-enabled algorithms that allow nodes to free capacity by forcing a locally hosted agent to move to another node, even at a loss, to accept a new and potentially more beneficial agent. To the best of our knowledge, this is the first time that agents are evicted by local hosts to enable beneficial agent migrations and eventually improve the total network cost. In this paper, we provide algorithms tackling the aforementioned problem in a fully distributed manner. We also present and discuss the results of extensive simulations, showing that eviction-enabled algorithms can outperform their counterparts by up to 300%. © 2012 IEEE.

关键词： Mobile agents

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