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Corrigendum to “Modelling opportunistic spectrum renting in mobile cellular networks” [J. Netw. Comput. Appl. 52 (2015) 129–138]

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Journal of Network and Computer Applications 2016年 73卷 98-98页

作者： Tien Van Do Nam H. Do Ádám Horváth Jinting Wang Division of Knowledge and System Engineering for ICT (KSE-ICT) Faculty of Information Technology Ton Duc Thang University Ho Chi Minh City Viet Nam Analysis Design and Development of ICT Systems (AddICT) Laboratory Budapest University of Technology and Economics H-1117 Magyar tudósok körútja 2 Budapest Hungary Faculty of Informatics University of Debrecen Egyetem tér 1 PO Box 12 4010 Debrecen Hungary Institute of Informatics and Economics University of West Hungary Bajcsy-Zsilinszky u. 9. Sopron Hungary Department of Mathematics School of Science Beijing Jiaotong University Beijing 100044 China

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Reports of the AAAI 2014 conference workshops

Reports of the AAAI 2014 conference workshops

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作者： Albrecht, Stefano V. Barreto, André M. S. Braziunas, Darius Buckeridge, David L. Cuayáhuitl, Heriberto Dethlefs, Nina Endres, Markus Farahmand, Amir-Massoud Fox, Mark Frommberger, Lutz Ganzfried, Sam Guillet, Sébastien Gil, Yolanda Hunter, Lawrence E. Jhala, Arnav Kersting, Kristian Konidaris, George Lecue, Freddy McIlraith, Sheila Natarajan, Sriraam Noorian, Zeinab Poole, David Ronfard, Rémi Saffiotti, Alessandro Shaban-Nejad, Arash Srivastava, Biplav Tesauro, Gerald Uceda-Sosa, Rosario Van Den Broeck, Guy Van Otterlo, Martijn Wallace, Byron C. Weng, Paul Wiens, Jenna Zhang, Jie School of Informatics University of Edinburgh United Kingdom Department of Applied and Computational Mathematics Brazilian National Laboratory Brazil Big Data Group Kobo Inc. Brazil Department of Epidemiology and Biostatistics McGill University Canada School of Mathematical and Computer Sciences Heriot-Watt University in Edinburgh United Kingdom University of Augsburg Germany Carnegie Mellon University United States University of Toronto Canada Cognitive Systems Group University of Bremen Germany LIARA UQAC Chicoutimi Canada Information Sciences Institute University of Southern California Computer Science Department United States Center for Computational Pharmacology University of Colorado School of Medicine United States Department of Computational Media University of California Santa Cruz United States Computer Science Department Technical University of Dortmund Germany MIT Computer Science and Artificial Intelligence Laboratory CambridgeMA United States IBM Research - Smarter Cities Technology Centre Dubline Ireland School of Informatics and Computing Indiana University United States Department of Computer Science University of Saskatchewan Canada University of British Columbia Canada INRIA University of Grenoble France Orebro University Sweden McGill Clinical and Health Informatics Group McGill University Canada IBM Research United States Cognitive Computing Department IBM Research Yorktown HeightsNY United States Computer Science Department Katholieke Universiteit Leuven Belgium Cognitive Artificial Intelligence Department Radboud University Nijmegen Netherlands University of Texas Austin United States Pierre and Marie Curie University Paris France University of Michigan United States School of Computer Engineering Nanyang Technological University Singapore

The AAAI-14 Workshop program was held Sunday and Monday, July 27-28, 2014, at the Québec City Convention Centre in Québec, Canada. The AAAI-14 workshop program included 15 workshops covering a wide range of topics in artificial intelligence. The titles of the workshops were Artificial Intelligence and Robotics;Artificial Intelligence Applied to Assistive Technologies and Smart Environments;Cognitive Computing for Augmented Human Intelligence;Computer Poker and Imperfect information;Discovery Informatics;Incentives and Trust in Electronic Communities;Intelligent Cinematography and Editing;Machine Learning for Interactive systems: Bridging the Gap Between Perception, Action, and Communication;Modern Artificial Intelligence for Health Analytics;Multiagent Interaction Without Prior Coordination;Multidisciplinary Workshop on Advances in Preference Handling;Semantic Cities - Beyond Open data to Models, Standards, and Reasoning;Sequential Decision Making with Big data;Statistical Relational AI;and the World Wide Web and Public Health Intelligence. This article presents short summaries of those events. © 2015, Association for the Advancement of Artificial Intelligence. All rights reserved.

关键词： Decision making

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Highlights from the 11th ISCB Student Council Symposium 2015. Dublin, Ireland. 10 July 2015

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BMC bioinformatics 2016年第3期17 Suppl 3卷 95页

作者： Katie Wilkins Mehedi Hassan Margherita Francescatto Jakob Jespersen R. Gonzalo Parra Bart Cuypers Dan DeBlasio Alexander Junge Anupama Jigisha Farzana Rahman Griet Laenen Sander Willems Lieven Thorrez Yves Moreau Nagarajan Raju Sonia Pankaj Chothani C. Ramakrishnan Masakazu Sekijima M. Michael Gromiha Paddy J Slator Nigel J Burroughs Przemysław Szałaj Zhonghui Tang Paul Michalski Oskar Luo Xingwang Li Yijun Ruan Dariusz Plewczynski Giulia Fiscon Emanuel Weitschek Massimo Ciccozzi Paola Bertolazzi Giovanni Felici Pieter Meysman Manu Vanaerschot Maya Berg Hideo Imamura Jean-Claude Dujardin Kris Laukens Westa Domanova James R. Krycer Rima Chaudhuri Pengyi Yang Fatemeh Vafaee Daniel J. Fazakerley Sean J. Humphrey David E. James Zdenka Kuncic Plant Pathology and Plant-Microbe Biology Section School of Integrative Plant Science Cornell University Ithaca USA Graduate Field of Computational Biology Cornell University Ithaca USA School of Computing & Mathematics University of South Wales Cardiff UK Department of Genome Biology for Neurodegenerative Diseases German Center for Neurodegenerative Diseases (DZNE) within the Helmholtz Association ᅟ Germany Department of Surgery Massachusetts General Hospital The Broad Institute of MIT and Harvard Boston USA Department of Systems Biology Technical University of Denmark Kemitorvet Denmark Protein Physiology Lab Facultad de Ciencias Exactas y Naturales Universidad de Buenos Aires Buenos Aires Argentina Molecular Parasitology Unit (MPU) Institute of Tropical Medicine Antwerp Belgium Advanced Database Research and Modeling (ADReM) research group University of Antwerp Antwerpen Belgium Department of Computer Science University of Arizona Tucson USA Department of Veterinary Clinical and Animal Sciences Center for non-coding RNA in Technology and Health University of Copenhagen Copenhagen Denmark University College Dublin Dublin Ireland Department of Electrical Engineering (ESAT) STADIUS Center for Dynamical Systems Signal Processing and Data Analytics KU Leuven Leuven Belgium Minds Medical IT Department Leuven Belgium Scientific Institute of Public Health (WIV-ISP) Platform of Biotechnology and Molecular Biology (PBB) Brussels Belgium Department of Development and Regeneration @ Kulak KU Leuven Kortrijk Belgium Department of Biotechnology Bhupat and Jyoti Metha School of Biosciences Indian Institute of Technology Madras Chennai India Philips Research North America Briarcliff Manor USA Global Scientific Information and Computing Center (GSIC) Tokyo Institute of Technology Tokyo Japan Systems Biology Centre University of Warwick Senate House Coventry UK Systems Biology Doctoral Training Centre University of Warwick Senate House Coventry UK Center for B

A1 Highlights from the eleventh ISCB Student Council Symposium 2015 Katie Wilkins, Mehedi Hassan, Margherita Francescatto, Jakob Jespersen, R. Gonzalo Parra, Bart Cuypers, Dan DeBlasio, Alexander Junge, Anupama Jigisha, Farzana Rahman O1 Prioritizing a drug’s targets using both gene expression and structural similarity Griet Laenen, Sander Willems, Lieven Thorrez, Yves Moreau O2 Organism specific protein-RNA recognition: A computational analysis of protein-RNA complex structures from different organisms Nagarajan Raju, Sonia Pankaj Chothani, C. Ramakrishnan, Masakazu Sekijima; M. Michael Gromiha O3 Detection of Heterogeneity in Single Particle Tracking Trajectories Paddy J Slator, Nigel J Burroughs O4 3D-NOME: 3D NucleOme Multiscale Engine for data-driven modeling of three-dimensional genome architecture Przemysław Szałaj, Zhonghui Tang, Paul Michalski, Oskar Luo, Xingwang Li, Yijun Ruan, Dariusz Plewczynski O5 A novel feature selection method to extract multiple adjacent solutions for viral genomic sequences classification Giulia Fiscon, Emanuel Weitschek, Massimo Ciccozzi, Paola Bertolazzi, Giovanni Felici O6 A systems Biology Compendium for Leishmania donovani Bart Cuypers, Pieter Meysman, Manu Vanaerschot, Maya Berg, Hideo Imamura, Jean-Claude Dujardin, Kris Laukens O7 Unravelling signal coordination from large scale phosphorylation kinetic data Westa Domanova, James R. Krycer, Rima Chaudhuri, Pengyi Yang, Fatemeh Vafaee, Daniel J. Fazakerley, Sean J. Humphrey, David E. James, Zdenka Kuncic

关键词： Visceral Leishmaniasis Feature Selection Method Frequent Itemset Mining Leishmania Donovani Student Council

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Semantic interpretation of mobile phone records exploiting background knowledge 12

Semantic interpretation of mobile phone records exploiting b...

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12th International Semantic Web Conference, ISWC 2013

作者： Dashdorj, Zolzaya Serafini, Luciano Semantic and Knowledge Innovation Lab. Telecom Italia Italy Department of Information Engineering and Computer Science University of Trento Italy Data and Knowledge Management Unit Fondazione Bruno Kessler Italy

The increasing availability of massive mobile phone call data records (CDR) has opened new opportunities for analyzing and understanding real-life social phenomena and human dynamics. In order to better interpret this enormous amount of data it is useful to contextualize them with information about the circumstances under which they has been generated. Nowadays, linked open data initiative provide access to a huge amount of geo-time referenced knowledge about territory and events that happen in the territory. These informations can be used to characterize the aforementioned context. The aim of this Ph.D is to investigate on the intercorrelations between CDR, contexts, and human behaviors. The ultimate goal is to build a stochastic model, that can be used to predict semantic (qualitative) behavioral patterns on the basis of CDR traffic and context and identify and explain anomalous situations on the basis of deviations from standard CDR patterns.

关键词： knowledge management

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Mining user interests from information sharing behaviors in social media

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17th Pacific-Asia Conference on knowledge Discovery and data Mining, PAKDD 2013

作者： Wang, Tingting Liu, Hongyan He, Jun Du, Xiaoyong Key Labs. of Data Engineering and Knowledge Engineering China School of Information Renmin University of China 100872 China Department of Management Science and Engineering Tsinghua University 100084 China

ISBN: (纸本)9783642374555

Mining user interests and preference plays an important role for many applications such as information retrieval and recommender systems. This paper intends to study how to infer interests for new users and inactive users from social media. Although some recently proposed methods can mine user interests efficiently, these works cannot make full use of relationship between users in their social network. In this paper, we propose a novel approach to infer interests of new users or inactive users based on social connections between users. A random-walk based mutual reinforcement model combining both text and link information is developed in the approach. More importantly, we compare the contribution of different social connections such as "follow", "retweet", "mention", and "comment" to interest sharing. Experiments conducted on real dataset show that our method is effective and outperforms existing algorithms, and different social connections have different impacts on mining user interests. © Springer-Verlag 2013.

关键词： Recommender systems

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Detecting event rumors on Sina Weibo automatically

Detecting event rumors on Sina Weibo automatically

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15th Asia-Pacific Web Conference on Web Technologies and Applications, APWeb 2013

作者： Sun, Shengyun Liu, Hongyan He, Jun Du, Xiaoyong Key Labs. of Data Engineering and Knowledge Engineering China School of Information Renmin University of China 100872 China Department of Management Science and Engineering Tsinghua University 100084 China

ISBN: (纸本)9783642374005

Sina Weibo has become one of the most popular social networks in China. In the meantime, it also becomes a good place to spread various spams. Unlike previous studies on detecting spams such as ads, pornographic messages and phishing, we focus on identifying event rumors (rumors about social events), which are more harmful than other kinds of spams especially in China. To detect event rumors from enormous posts, we studied the characteristics of event rumors and extracted features which can distinguish rumors from ordinary posts. The experiments conducted on real dataset show that the new features are effective to improve the rumor classifier. Further analysis of the event rumors reveals that they can be classified into 4 different types. We propose an approach for detecting one major type, text-picture unmatched event rumors. The experiment demonstrates that this approach is well-performed. © 2013 Springer-Verlag.

关键词： Social networking (online)

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A MODIFIED BROADCAST STRATEGY FOR DISTRIBUTED SIGNAL ESTIMATION IN A WIRELESS SENSOR NETWORK WITH A TREE TOPOLOGY

A MODIFIED BROADCAST STRATEGY FOR DISTRIBUTED SIGNAL ESTIMAT...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Joseph Szurley Alexander Bertrand Marc Moonen Ingrid Moerman KU Leuven-Dept. Electrical Engineering ESAT STADIUS Center for Dynamical Systems Signal Processing and Data Analytics Kasteelpark Arenberg 10 3001 Leuven Belgium Ghent University Department of Information Technology (INTEC) iMinds Future Health Department Gaston Crommenlaan 8 Bus 201 9050 Ghent Belgium

ISBN: (纸本)9781479928941

We envisage a wireless sensor network (WSN) where each node is tasked with estimating a set of node-specific desired signals that has been corrupted by additive noise. The nodes accomplish this estimation by means of the distributed adaptive node-specific estimation (DANSE) algorithm in a tree topology (T-DANSE). In this paper, we consider a network where there is at least one node with a large (virtually infinite) energy budget, which we select as the root node. We propose a modification to the signal flow of the T-DANSE algorithm where instead of each node having two-way signal communication, there is a single signal flow toward the root node of the tree topology which then broadcasts a single signal to all other nodes. We demonstrate that the modified algorithm is equivalent to the original T-DANSE algorithm in terms of the signal estimation performance, shifts a large part of the communication burden toward the high-power root node to reduce the energy consumption in the low-power nodes and reduces the input-output delay.

关键词： Wireless sensor networks signal flow Tree Topology Line of nodes single signal Radio topology signals Sensors

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Efficient querying of correlated uncertain data with cached results

Efficient querying of correlated uncertain data with cached ...

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18th International Conference on database systems for Advanced Applications, DASFAA 2013

作者： Chen, Jinchuan Zhang, Min Xie, Xike Du, Xiaoyong Key Laboratory of Data Engineering and Knowledge Engineering Renmin University of China MOE China School of Information Renmin University of China China Department of Computer Science Aalborg University Denmark

ISBN: (纸本)9783642374869

Although there have been many efforts for management of uncertain data, evaluating probabilistic inference queries, a known NP-hard problem, is still a big challenge, especially for querying data with highly correlations. The state-of-art exact algorithms for accelerating the evaluation of inference queries are based on special indices. Besides, with the observation of the existence of many frequent queries, some researchers try to improve efficiency by reusing previously queried results. Indexing depends on the static properties like data distributions, whereas caching is in favor of the dynamic features like query workload. In this paper we propose a new approach for speeding up the evaluation of inference queries by caching frequent results in a junction tree-based hierarchical index. To the best of our knowledge, this is the first effort on utilizing both the static (data) and dynamic (query workload) properties to efficiently evaluate probabilistic inference queries. Moreover, according to our experience, different caching strategies may significantly affect the query performance. Basically a good caching strategy needs to have high cache hit ratio with limited space *** on these considerations, we propose a novel caching approach, called FVEC, and present corresponding algorithms for efficiently querying correlated uncertain data. We further conduct a series of extensive experiments on large uncertain datasets in order to illustrate the effectiveness and efficiency of our proposed approaches. As illustrated by the results, compared with previous solutions, our method could greatly improve the query performance. © Springer-Verlag 2013.

关键词： Efficiency

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Model predictive 2DOF PID control for heat conduction system

Model predictive 2DOF PID control for heat conduction system

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2013 52nd Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2013

作者： Nakamura, Ko Hagiwara, Yuji Li, Shaobo Kawabe, Tohru Division of Information Engineering Faculty of Engineering Information and Systems University of Tsukuba Ibaraki Japan NTT DATA Corporation Tokyo Japan Department of Computer Science University of Tsukuba Ibaraki Japan

Advanced control is needed to the heat conduction systems for high-quality manufacturing. Although PID controller has been so widely used for such systems conventionally, it shows difficult to realize the high-precision temperature control for the difference of heat conductive property caused by the operating temperature. Moreover, it is unavailable for the control with the constraints of temperature and input. Although MP-PID controller has been proposed in response to those problems, it still leaves room for improving the control performance. In this paper, we propose a MP-2DOF PID controller that applies MPC algorithm to 2DOF PID controller as an extension of MP-PID controller. This can optimize not only PID gains but also 2DOF parameters at beginning of each control period under consideration for the constraints. The effectiveness of the proposed method is verified by the numerical simulations.

关键词： Three term control systems

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11th German Conference on Chemoinformatics (GCC 2015) Abstracts

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JOURNAL OF CHEMINFORMATICS 2016年第SUPPL 1期8卷 1-27页

作者： [Anonymous] GDCh-CIC Division Associated Board Member Beilstein-Institut zur Förderung der Chemischen Wissenschaften Trakehner Str. 7-9 60487 Frankfurt Germany. ufechner@beilstein-institut.de. Division Medicinal Chemistry Amsterdam Institute for Molecules Medicines and Systems (AIMMS) VU University Amsterdam The Netherlands. Centre for Bioinformatics Uni Hamburg Bundesstr. 43 20146 Hamburg Germany. Sanofi-Aventis Deutschland GmbH 65926 Frankfurt am Main Germany. stefan.guessregen@***. Sanofi-Aventis Deutschland GmbH 65926 Frankfurt am Main Germany. GlaxoSmithKline Stevenage SG1 2NY UK. nicola.j.richmond@***. Discngine Paris 75011 France. Organisch-Chemisches Institut Westfälische Wilhelms-Universität Münster Germany. marwin.segler@wwu.de. Organisch-Chemisches Institut Westfälische Wilhelms-Universität Münster Germany. Bundeskriminalamt Wiesbaden Central Analytics II 65173 Wiesbaden Germany. Department of Chemistry and Biochemistry University of California Santa Barbara CA 93111 USA. shea@chem.ucsb.edu. Department of Chemistry and Biochemistry University of California Santa Barbara CA 93111 USA. Chemistry Department Ludwig-Maximilians-Universität München Butenandtstr. 7 81377 Munich Germany. Inorganic Chemistry and Center for Nanointegration University of Duisburg-Essen Essen Germany. CAM-D Technologies Essen Germany. Institute for Bioinformatics and Chemoinformatics Westphalian University of Applied Sciences Recklinghausen Germany. Institute for Bioinformatics and Chemoinformatics Westphalian University of Applied Sciences Recklinghausen Germany. achim.zielesny@w-hs.de. Leiden University Leiden Netherlands. j.fraaije@chem.leidenuniv.nl. Culgi BV Berlin Germany. Physikalische Chemie III TU Dortmund 44227 Dortmund Germany. stefan.kast@tu-dortmund.de. Centre for Molecular Informatics Department of Chemistry University of Cambridge Lensfield Road Cambridge CB2 1EW United Kingdom. kcb27@cam.ac.uk. Centre for Molecular Informatics Department of Chemistry

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