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From epidemics to information propagation: Striking differences in structurally similar adaptive network models

Physical Review E 2015年第3期92卷 030801(R)-030801(R)页

作者： Stojan Trajanovski Dongchao Guo Piet Van Mieghem Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology P.O. Box 5031 2600 GA Delft The Netherlands Big Data and Network Engineering Research Center RIIT Tsinghua University Beijing People's Republic of China

The continuous-time adaptive susceptible-infected-susceptible (ASIS) epidemic model and the adaptive information diffusion (AID) model are two adaptive spreading processes on networks, in which a link in the network changes depending on the infectious state of its end nodes, but in opposite ways: (i) In the ASIS model a link is removed between two nodes if exactly one of the nodes is infected to suppress the epidemic, while a link is created in the AID model to speed up the information diffusion; (ii) a link is created between two susceptible nodes in the ASIS model to strengthen the healthy part of the network, while a link is broken in the AID model due to the lack of interest in informationless nodes. The ASIS and AID models may be considered as first-order models for cascades in real-world networks. While the ASIS model has been exploited in the literature, we show that the AID model is realistic by obtaining a good fit with Facebook data. Contrary to the common belief and intuition for such similar models, we show that the ASIS and AID models exhibit different but not opposite properties. Most remarkably, a unique metastable state always exists in the ASIS model, while there an hourglass-shaped region of instability in the AID model. Moreover, the epidemic threshold is a linear function in the effective link-breaking rate in the AID model, while it is almost constant but noisy in the AID model.

关键词： Continuous time systems Discrete-time systems Hebbian memory Metastable states Topology

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Efficient mining of class association rules with the itemset constraint

Efficient mining of class association rules with the itemset...

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作者： Nguyen, Dang Nguyen, Loan T.T. Vo, Bay Pedrycz, Witold Division of Data Science Ton Duc Thang University Ho Chi Minh City Viet Nam Division of Knowledge and System Engineering for ICT Ton Duc Thang University Ho Chi Minh City Viet Nam Faculty of Information Technology Ton Duc Thang University Ho Chi Minh City Viet Nam Faculty of Information Technology Ho Chi Minh City University of Technology Viet Nam College of Electronics and Information Engineering Sejong University Seoul Korea Republic of Department of Electrical and Computer Engineering University of Alberta EdmontonABT6R 2V4 Canada Department of Electrical and Computer Engineering Faculty of Engineering King Abdulaziz University Jeddah21589 Saudi Arabia Systems Research Institute Polish Academy of Sciences Warsaw Poland

Mining class association rules (CARs) with the itemset constraint is concerned with the discovery of rules, which contain a set of specific items in the rule antecedent and a class label in the rule consequent. This task is commonly encountered in mining medical data. For example, when classifying which section of the population is at high risk for the HIV infection, epidemiologists often concentrate on rules which include demographic information such as gender, age, and marital status in the rule antecedent, and HIV-Positive in the rule consequent. There are two naive strategies to solve this problem, namely pre-processing and post-processing. The post-processing methods have to generate and consider a huge number of candidate CARs while the performance of the pre-processing methods depend on the number of records filtered out. Therefore, such approaches are time consuming. This study proposes an efficient method for mining CARs with the itemset constraint based on a lattice structure and the difference between two sets of object identifiers (diffset). Firstly, a lattice structure is built to store all frequent itemsets in the dataset. To reduce memory usage, instead of the entire set of object identifiers, the diffset is used. Secondly, the lattice is traversed to generate only rules which satisfy the itemset constraint. The experimental results show that the proposed algorithm outperforms existing methods in terms of both the mining time and memory usage. © 2016 Elsevier B.V. All rights reserved.

关键词： data mining

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Category of isotone bonds between L-fuzzy contexts over different structures of truth degrees 12

Category of isotone bonds between L-fuzzy contexts over diff...

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12th International Conference on Concept Lattices and Their Applications, CLA 2015

作者： Konecny, Jan Krídlo, Ondrej Data Analysis and Modeling Lab Dept. Computer Science Palacky University Olomouc 17. listopadu 12 OlomoucCZ-77146 Czech Republic Institute of Computer Science Faculty of Science Pavol Jozef Šafárik University in Košice Jesenná 5 Košice040 01 Slovakia

We describe properties of compositions of isotone bonds between L-fuzzy contexts over different complete residuated lattices and we show that L-fuzzy contexts as objects and isotone bonds as arrows form a category. &#... 详细信息

ISBN: (纸本)9782954494807

关键词： computer circuits

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Axle bearing condition monitoring, diagnosis and maintenance: The MAXBE project

Axle bearing condition monitoring, diagnosis and maintenance...

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作者： Vale, C. Bonifácio, C. Seabra, J. Calçada, R. Mazzino, N. Elis, M. Terribile, S. Anguita, D. Fumeo, E. Saborido, C. Vanhonacker, T. De Donder, E. Laeremans, M. Vermeulen, F. Grimes, D. Dias, D. Construct-LESE Faculty of Engineering of University of Porto Portugal Ansaldo STS S.p.A. Genoa Italy Polytechnic School of University of Genoa Italy COMSA EMTE Barcelona Spain Dynamics Structures and Systems International Leuven Belgium Vlaamse Vervoermaatschappij de Lijn Antwerp Belgium I-MOSS N.V. Bertem Belgium Insight Center for Data Analytics Dept. of Computer Science University College Cork Ireland NOMADTECH Portugal

The reliability of axle bearings has significant safety and economic implications on rail operations. The MAXBE project, an FP7 project funded by the European Commission appeared in this context. The project focuses on the development of novel wayside and on-board monitoring systems for an early detection of axle bearings faults and for defining a condition-based maintenance model for axle bearings. Different wayside monitoring systems were developed based on diverse approaches as well as two on-board monitoring systems. To support the decision making of the responsible stakeholders synchronized measurements from the onboard and the wayside monitoring systems were integrated into a platform. The wayside monitoring systems were tested in several locations in Europe. The onboard systems were tested in one train that circulate in the Portuguese Northern Railway Line. The research has been complemented through extensive laboratory tests and multibody dynamic modelling used to correlate the in-situ measurements with the status of the axle bearing life. A condition-based maintenance model for axle bearings was also developed as well as a smart diagnostics for an early detection of faults and a software tool for the optimal physical distribution of the diagnostic systems. This paper presents the main results and findings of the project. © Civil-Comp Press, 2016.

关键词： Condition based maintenance

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Erratum to: Meaurement of ϒ production in pp colliion at = 13 TeV

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Journal of High Energy Physics 2019年第5期2019卷 76-76页

作者： The LHCb collaboration R. Aaij B. Adeva M. Adinolfi Z. Ajaltouni S. Akar J. Albrecht F. Alessio M. Alexander A. Alfonso Albero S. Ali G. Alkhazov P. Alvarez Cartelle A. A. Alves S. Amato S. Amerio Y. Amhis L. An L. Anderlini G. Andreassi M. Andreotti J. E. Andrews R. B. Appleby F. Archilli P. d’Argent J. Arnau Romeu A. Artamonov M. Artuso E. Aslanides M. Atzeni G. Auriemma S. Bachmann J. J. Back C. Baesso S. Baker V. Balagura W. Baldini A. Baranov R. J. Barlow S. Barsuk W. Barter F. Baryshnikov V. Batozskaya V. Battista A. Bay J. Beddow F. Bedeschi I. Bediaga A. Beiter L. J. Bel N. Beliy V. Bellee N. Belloli K. Belous I. Belyaev E. Ben-Haim G. Bencivenni S. Benson S. Beranek A. Berezhnoy R. Bernet D. Berninghoff E. Bertholet A. Bertolin C. Betancourt F. Betti M. O. Bettler M. van Beuzekom Ia. Bezshyiko S. Bifani P. Billoir A. Birnkraut A. Bizzeti M. Bjørn T. Blake F. Blanc S. Blusk V. Bocci T. Boettcher A. Bondar N. Bondar S. Borghi M. Borisyak M. Borsato F. Bossu M. Boubdir T. J. V. Bowcock E. Bowen C. Bozzi S. Braun M. Brodski J. Brodzicka D. Brundu E. Buchanan C. Burr A. Bursche J. Buytaert W. Byczynski S. Cadeddu H. Cai R. Calabrese R. Calladine M. Calvi M. Calvo Gomez A. Camboni P. Campana D. H. Campora Perez L. Capriotti A. Carbone G. Carboni R. Cardinale A. Cardini P. Carniti L. Carson K. Carvalho Akiba G. Casse L. Cassina M. Cattaneo G. Cavallero R. Cenci D. Chamont M. G. Chapman M. Charles Ph. Charpentier G. Chatzikonstantinidis M. Chefdeville S. Chen S.-G. Chitic V. Chobanova M. Chrzaszcz A. Chubykin P. Ciambrone X. Cid Vidal G. Ciezarek P. E. L. Clarke M. Clemencic H. V. Cliff J. Closier V. Coco J. Cogan E. Cogneras V. Cogoni L. Cojocariu P. Collins T. Colombo A. Comerma-Montells A. Contu G. Coombs S. Coquereau G. Corti M. Corvo C. M. Costa Sobral B. Couturier G. A. Cowan D. C. Craik A. Crocombe M. Cruz Torres R. Currie C. D’Ambrosio F. Da Cunha Marinho C. L. Da Silva E. Dall’Occo J. Dalseno A. Davis O. De Aguiar Francisco K. De Bruyn S. De Capua M. De Cian J. M. De Miranda L. De Paula M. De Serio P. D Nikhef National Institute for Subatomic Physics Universidade de Santiago de Compostela University of Bristol Clermont Université Université Blaise Pascal CNRS/IN2P3 LPC University of Cincinnati Technische Universität Dortmund European Organization for Nuclear Research (CERN) University of Glasgow Universitat de Barcelona Petersburg Nuclear Physics Institute (PNPI) Imperial College London Universidade Federal do Rio de Janeiro (UFRJ) Sezione INFN di Padova LAL Univ. Paris-Sud CNRS/IN2P3 Université Paris-Saclay Tsinghua University Sezione INFN di Firenze Institute of Physics Ecole Polytechnique Fédérale de Lausanne (EPFL) Sezione INFN di Ferrara Università di Ferrara University of Maryland University of Manchester Ruprecht-Karls-Universität Heidelberg Aix Marseille Univ CNRS/IN2P3 CPPM Institute for High Energy Physics (IHEP) Syracuse University Universität Zürich Sezione INFN di Roma La Sapienza University of Warwick Pontifícia Universidade Católica do Rio de Janeiro (PUC-Rio) Laboratoire Leprince-Ringuet Yandex School of Data Analysis Institute of Theoretical and Experimental Physics (ITEP) National Center for Nuclear Research (NCBJ) Sezione INFN di Pisa Centro Brasileiro de Pesquisas Físicas (CBPF) University of Chinese Academy of Sciences Sezione INFN di Milano Bicocca Università di Milano Bicocca LPNHE Université Pierre et Marie Curie Université Paris Diderot CNRS/IN2P3 Laboratori Nazionali dell’INFN di Frascati RWTH Aachen University Institute of Nuclear Physics Moscow State University (SINP MSU) Sezione INFN di Bologna University of Cambridge University of Birmingham Università di Modena e Reggio Emilia University of Oxford Massachusetts Institute of Technology Budker Institute of Nuclear Physics (SB RAS) Novosibirsk State University University of Liverpool Henryk Niewodniczanski Institute of Nuclear Physics Polish Academy of Sciences Sezione INFN di Cagliari Wuhan University Universitat Ramon Llull Università di Bologna Sezione INFN di Roma Tor Vergata Sezione INFN di Genova Università di Genov

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Pattern-based linked data publication: The linked chess dataset case 6

Pattern-based linked data publication: The linked chess data...

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6th International Workshop on Consuming Linked data, COLD 2015 - co-located with 14th International Semantic Web Conference, ISWC 2105

作者： Rodriguez-Doncel, Victor Krisnadhi, Adila A. Hitzler, Pascal Cheatham, Michelle Karima, Nazifa Amini, Reihaneh Ontology Engineering Group Universidad Politecnica de Madrid Spain Data Semantics Lab Wright State University United States Faculty of Computer Science Universitas Indonesia Indonesia

This paper discusses the relationship between ontology de- sign patterns (ODPs), data models and linked data, proposing a method that simplifies the task of publishing linked data while adhering to good modeling practices that reuse well-studied ODPs. The method consists of providing the pattern along with a simplified view of it, the conversion queries to transform one into the other and the constraints to verify pattern conformance. The proposed process simplifies the tasks of the domain experts but preserves the integrity of the design patterns, favoring a well-designed and well documented data model which fosters data reuse. The work is illustrated with a linked dataset of chess games with the key information mapped to other linked datasets and supported by formalized design patterns. A chess dataset is presented as linked data.

关键词： Linked data

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An ontology design pattern for chess games 6

An ontology design pattern for chess games

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6th Workshop on Ontology and Semantic Web Patterns, WOP 2015

作者： Krisnadhi, Adila Rodríguez-Doncel, Víctor Hitzler, Pascal Cheatham, Michelle Karima, Nazifa Amini, Reihaneh Coleman, Ashley Data Semantics Lab Wright State University United States Faculty of Computer Science Universitas Indonesia Indonesia Ontology Engineering Group Universidad Politécnica de Madrid Spain

We present an ontology pattern describing records of chess games. Besides being an interesting modeling problem by itself, the fact that chess is one of the most popular game in the world with hundreds of millions of active players, including several millions online players led to a huge amount of chess game data available from various online chess databases. Furthermore, these data are becoming available as linked data with links to prominent datasets, such as DBPedia or GeoNames. However, there is still a lack of a well-designed schema that can ease linked data publishing of chess games. Our pattern is hoped to fill that gap.

关键词： Linked data

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Authorship Correction: International Changes in COVID-19 Clinical Trajectories Across 315 Hospitals and 6 Countries: Retrospective Cohort Study

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Journal of medical Internet research 2021年第11期23卷 e34625页

作者： Griffin M Weber Harrison G Zhang Sehi L'Yi Clara-Lea Bonzel Chuan Hong Paul Avillach Alba Gutiérrez-Sacristán Nathan P Palmer Amelia Li Min Tan Xuan Wang William Yuan Nils Gehlenborg Anna Alloni Danilo F Amendola Antonio Bellasi Riccardo Bellazzi Michele Beraghi Mauro Bucalo Luca Chiovato Kelly Cho Arianna Dagliati Hossein Estiri Robert W Follett Noelia García Barrio David A Hanauer Darren W Henderson Yuk-Lam Ho John H Holmes Meghan R Hutch Ramakanth Kavuluru Katie Kirchoff Jeffrey G Klann Ashok K Krishnamurthy Trang T Le Molei Liu Ne Hooi Will Loh Sara Lozano-Zahonero Yuan Luo Sarah Maidlow Adeline Makoudjou Alberto Malovini Marcelo Roberto Martins Bertrand Moal Michele Morris Danielle L Mowery Shawn N Murphy Antoine Neuraz Kee Yuan Ngiam Marina P Okoshi Gilbert S Omenn Lav P Patel Miguel Pedrera Jiménez Robson A Prudente Malarkodi Jebathilagam Samayamuthu Fernando J Sanz Vidorreta Emily R Schriver Petra Schubert Pablo Serrano Balazote Byorn Wl Tan Suzana E Tanni Valentina Tibollo Shyam Visweswaran Kavishwar B Wagholikar Zongqi Xia Daniela Zöller Isaac S Kohane Tianxi Cai Andrew M South Gabriel A Brat Department of Biomedical Informatics Harvard Medical School Boston MA United States. BIOMERIS (BIOMedical Research Informatics Solutions) Pavia Italy. Clinical Research Unit Botucatu Medical School São Paulo State University Botucatu Brazil. Division of Nephrology Department of Medicine Ente Ospedaliero Cantonale Lugano Switzerland. Department of Electrical Computer and Biomedical Engineering University of Pavia Pavia Italy. Information Technology Department Azienda Socio-Sanitaria Territoriale di Pavia Pavia Italy. Unit of Internal Medicine and Endocrinology Istituti Clinici Scientifici Maugeri SpA SB IRCCS Pavia Italy. Massachusetts Veterans Epidemiology Research and Information Center Veterans Affairs Boston Healthcare System Boston MA United States. Department of Electrical Computer and Biomedical Engineering University of Pavia Pavia Italy. Department of Medicine Massachusetts General Hospital Boston MA United States. Department of Medicine David Geffen School of Medicine University of California Los Angeles Los Angeles CA United States. Health Informatics Hospital Universitario 12 de Octubre Madrid Spain. Department of Learning Health Sciences University of Michigan Medical School Ann Arbor MI United States. Department of Biomedical Informatics University of Kentucky Lexington KY United States. Department of Biostatistics Epidemiology and Informatics University of Pennsylvania Perelman School of Medicine Philadelphia PA United States. Institute for Biomedical Informatics University of Pennsylvania Perelman School of Medicine Philadelphia PA United States. Department of Preventive Medicine Northwestern University Chicago IL United States. Institute for Biomedical Informatics University of Kentucky Lexington KY United States. Medical University of South Carolina Charleston SC United States. Department of Computer Science Renaissance Computing Institute University of North Carolina at Chapel Hill Chapel Hill NC United States. Departm

[This corrects the article DOI: 10.2196/31400.].

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Fast updated frequent-itemset lattice for transaction deletion

Fast updated frequent-itemset lattice for transaction deleti...

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作者： Vo, Bay Le, Tuong Hong, Tzung-Pei Le, Bac Faculty of Information Technology Ho Chi Minh City University of Technology Viet Nam Division of Data Science Ton Duc Thang University Ho Chi Minh City Viet Nam Faculty of Information Technology Ton Duc Thang University Ho Chi Minh City Viet Nam Department of Computer Science and Information Engineering National University of Kaohsiung Kaohsiung Taiwan Department of Computer Science and Engineering National Sun Yat-sen University Kaohsiung Taiwan Department of Computer Science University of Science VNU-Ho Chi Minh Viet Nam

The frequent-itemset lattice (FIL) is an effective structure for mining association rules. However, building an FIL for a modified database requires a lot of time and memory. Currently, there is no approach for updating an FIL with deleted transactions. Therefore, this paper proposes an approach for maintaining FILs for transaction deletion without rescanning the original database if the number of eliminated transactions is smaller than the threshold determined based on the pre-large and diffset concepts. A diffset-based approach is first used for fast building an FIL. Then, two proposed approaches (tidset-based and diffset-based) are used for updating the FIL with transaction deletion. The experiment was conducted to show that the diffset-based approach outperforms the tidset-based and the batch-mode approaches. © 2015 Elsevier B.V.

关键词： data mining

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Guest Editorial Measuring and Troubleshooting the Internet: Algorithms, Tools and Applications

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IEEE Journal on Selected Areas in Communications 2016年第6期34卷 1805-1806页

作者： Maurizio Dusi Alessandro Finamore Kimberly Claffy Nevil Brownlee Darryl Veitch Copan Diagnostics Inc. Murrieta CA USA Telefonica Research Distrito Telefonica Madrid Spain Center for Applied Internet Data Analysis San Diego Supercomputer Center La Jolla CA USA Department of Computer Science The University of Auckland Auckland New Zealand School of Computing and Communications Faculty of Engineering and Information Technology University of Technology Sydney Ultimo NSW Australia

The ubiquity of Internet access and the wide variety of Internet-enabled devices and applications have made the Internet a principal pillar of the Information Society. Decentralized and diverse, the Internet is resilient and universal. However, its distributed nature leads to operational brittleness and difficulty in identifying and tracking the root causes of performance and availability issues.

关键词： Special issues and sections Internet Algorithm design and analysis Performance analysis Quality of service

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