Search results for "network [detector]"

showing 10 items of 496 documents

Thermal analysis and new insights to support decision making in retrofit and relaxation of heat exchanger networks

2011

International audience; Pinch analysis offers a rational framework for identifying energy saving targets and designing efficient heat recovery networks, especially in process industry. Several scientists have contributed to improve and automate the original pinch method over the last decades, increasing its capability to deal with a number of specific issues; the expertise of the analyst, however, remains determinant in achieving optimal results. In this paper a procedure for retrofit of existing networks is proposed, based on an integrate use of several techniques (either existing or innovative). The diagnosis of the existing network and of a "Minimum Energy Requirement" configuration emer…

ExergyEngineering drawingEngineeringretrofit020209 energyEnergy Engineering and Power Technology02 engineering and technologyNetwork topologyIndustrial and Manufacturing Engineeringrelaxation020401 chemical engineeringHeat recovery ventilationSettore ING-IND/10 - Fisica Tecnica Industriale0202 electrical engineering electronic engineering information engineeringInstrumentation (computer programming)exergy destruction0204 chemical engineeringbusiness.industryheat exchanger networksHeat exchanger networkWork in processThermal analysiIndustrial engineeringEnergy conservation[SPI.MECA.THER]Engineering Sciences [physics]/Mechanics [physics.med-ph]/Thermics [physics.class-ph][PHYS.MECA.THER]Physics [physics]/Mechanics [physics]/Thermics [physics.class-ph]Pinch analysisRelaxation (approximation)businessthermal analysisApplied Thermal Engineering
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AIOC2: A deep Q-learning approach to autonomic I/O congestion control in Lustre

2021

Abstract In high performance computing systems, I/O congestion is a common problem in large-scale distributed file systems. However, the current implementation mainly requires administrator to manually design low-level implementation and optimization, we proposes an adaptive I/O congestion control framework, named AIOC 2 , which can not only adaptively tune the I/O congestion control parameters, but also exploit the deep Q-learning method to start the training parameters and optimize the tuning for different types of workloads from the server and the client at the same time. AIOC 2 combines the feedback-based dynamic I/O congestion control and deep Q-learning parameter tuning technology to …

ExploitComputer Networks and CommunicationsComputer sciencebusiness.industryQ-learningInterference (wave propagation)SupercomputerComputer Graphics and Computer-Aided DesignTheoretical Computer ScienceNetwork congestionArtificial IntelligenceHardware and ArchitectureEmbedded systemLustre (file system)Latency (engineering)businessThroughput (business)SoftwareParallel Computing
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Notice of Violation of IEEE Publication Principles: Distributed Multimedia Digital Libraries on Peer-to-Peer Networks

2007

This paper presents an original approach to image sharing in large, distributed digital libraries, in which a user is able to interactively search interesting resources by means of content-based image retrieval techniques. The approach described here addresses the issues arising when the content is managed through a peer-to-peer architecture. In this case, the retrieval facilities are likely to be limited to queries based on unique identifiers or small sets of keywords, which may be quite inadequate, so we propose a novel algorithm for routing user queries that exploits compact representations of multimedia resources shared by each peer in order to dynamically adapt the network topology to …

ExploitMultimediabusiness.industryComputer scienceImage sharingPeer-to-peercomputer.software_genreDigital libraryNetwork topologyUnique identifierWorld Wide WebbusinesscomputerImage retrievalContent management14th International Conference of Image Analysis and Processing - Workshops (ICIAPW 2007)
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Core of communities in bipartite networks

2017

We use the information present in a bipartite network to detect cores of communities of each set of the bipartite system. Cores of communities are found by investigating statistically validated projected networks obtained using information present in the bipartite network. Cores of communities are highly informative and robust with respect to the presence of errors or missing entries in the bipartite network. We assess the statistical robustness of cores by investigating an artificial benchmark network, the co-authorship network, and the actor-movie network. The accuracy and precision of the partition obtained with respect to the reference partition are measured in terms of the adjusted Ran…

FOS: Computer and information sciencesAccuracy and precisionPhysics - Physics and SocietyBipartite systemRand indexFOS: Physical sciencesPhysics and Society (physics.soc-ph)computer.software_genre01 natural sciences010104 statistics & probabilityRobustness (computer science)0103 physical sciences01.02. Számítás- és információtudomány0101 mathematics010306 general physicsMathematicsSocial and Information Networks (cs.SI)Probability and statisticsComputer Science - Social and Information NetworksSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)network theory community detectionPhysics - Data Analysis Statistics and ProbabilityBipartite graphData miningcomputerData Analysis Statistics and Probability (physics.data-an)
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Capture Aware Sequential Waterfilling for LoraWAN Adaptive Data Rate

2020

LoRaWAN (Long Range Wide Area Network) is emerging as an attractive network infrastructure for ultra low power Internet of Things devices. Even if the technology itself is quite mature and specified, the currently deployed wireless resource allocation strategies are still coarse and based on rough heuristics. This paper proposes an innovative "sequential waterfilling" strategy for assigning Spreading Factors (SF) to End-Devices (ED). Our design relies on three complementary approaches: i) equalize the Time-on-Air of the packets transmitted by the system's EDs in each spreading factor's group; ii) balance the spreading factors across multiple access gateways, and iii) keep into account the c…

FOS: Computer and information sciencesComputer scienceDistributed computingInternet of ThingsWireless communicationresource allocationServers02 engineering and technologyNetwork topologyspreading factorsinter-SF interferenceComputer Science - Networking and Internet Architecturechannel captureBandwidthServerLPWAN0202 electrical engineering electronic engineering information engineeringWirelessComputer architectureElectrical and Electronic Engineeringinternet of t6hingsNetworking and Internet Architecture (cs.NI)Network packetbusiness.industryApplied MathematicsResource managementinternet of t6hings; LoRaWAN; spreading factors; resource allocation; adaptive data rate; channel capture; inter-SF interference020206 networking & telecommunicationsComputer Science ApplicationsLoRaWANadaptive data rateWide area networkScalabilityHeuristicsbusinessInterferenceUplinkCommunication channel
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Multi-scale analysis of the European airspace using network community detection

2014

We show that the European airspace can be represented as a multi-scale traffic network whose nodes are airports, sectors, or navigation points and links are defined and weighted according to the traffic of flights between the nodes. By using a unique database of the air traffic in the European airspace, we investigate the architecture of these networks with a special emphasis on their community structure. We propose that unsupervised network community detection algorithms can be used to monitor the current use of the airspaces and improve it by guiding the design of new ones. Specifically, we compare the performance of three community detection algorithms, also by using a null model which t…

FOS: Computer and information sciencesDatabases FactualDistributed computingSocial SciencesPoison controllcsh:MedicineSociologycommunity detectionData Mininglcsh:SciencePhysicsMultidisciplinaryMathematical modelApplied MathematicsPhysicsCommunity structureComputer Science - Social and Information NetworksAir traffic controlAir TravelSocial NetworksPhysical SciencesInterdisciplinary PhysicsSocial SystemsEngineering and TechnologyFree flightInformation TechnologyNetwork AnalysisAlgorithmsResearch ArticlePhysics - Physics and SocietyComputer and Information SciencesControl (management)FOS: Physical sciencesComputerApplications_COMPUTERSINOTHERSYSTEMSPhysics and Society (physics.soc-ph)Statistical MechanicsDatabasescomplex networkHumansArchitectureNetworks network communities socio-technical system complex systems Air Traffic ManagementSocial and Information Networks (cs.SI)Null modellcsh:RModels TheoreticalSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Computational SociologySignal ProcessingAir trafficlcsh:QMathematics
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Disrupting resilient criminal networks through data analysis: The case of Sicilian Mafia

2020

Compared to other types of social networks, criminal networks present hard challenges, due to their strong resilience to disruption, which poses severe hurdles to law-enforcement agencies. Herein, we borrow methods and tools from Social Network Analysis to (i) unveil the structure of Sicilian Mafia gangs, based on two real-world datasets, and (ii) gain insights as to how to efficiently disrupt them. Mafia networks have peculiar features, due to the links distribution and strength, which makes them very different from other social networks, and extremely robust to exogenous perturbations. Analysts are also faced with the difficulty in collecting reliable datasets that accurately describe the…

FOS: Computer and information sciencesEconomicsComputer science0211 other engineering and technologiesSocial SciencesCriminology02 engineering and technologycomputer.software_genreSocial NetworkingSociologyStatistics - Machine LearningCentralityCriminals; Humans; Sicily; Social NetworkingSicilySocial network analysisHuman CapitalMultidisciplinarySettore INF/01 - InformaticaQ05 social sciencesRComputer Science - Social and Information NetworksPoliceProfessionsSocial NetworksMedicineCrimeNetwork AnalysisResearch ArticleNetwork analysisComputer and Information SciencesScienceMachine Learning (stat.ML)Computer securityNetwork ResilienceHuman capitalBetweenness centralityHumansResilience (network)0505 lawBlock (data storage)Social and Information Networks (cs.SI)021110 strategic defence & security studiesSocial networkbusiness.industryNode (networking)CriminalsCommunicationsPeople and Places050501 criminologyPopulation GroupingsCentralitybusinesscomputer
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The network of global corporate control.

2011

The structure of the control network of transnational corporations affects global market competition and financial stability. So far, only small national samples were studied and there was no appropriate methodology to assess control globally. We present the first investigation of the architecture of the international ownership network, along with the computation of the control held by each global player. We find that transnational corporations form a giant bow-tie structure and that a large portion of control flows to a small tightly-knit core of financial institutions. This core can be seen as an economic “super-entity” that raises new important issues both for researchers and policy make…

FOS: Computer and information sciencesInternationalityFinancial ManagementEconomicsFinancial intermediarylcsh:MedicineNetwork theorySocial and Behavioral Sciences01 natural sciences010305 fluids & plasmasMicroeconomics050207 economicslcsh:ScienceMutual fundIndustrial organizationProfessional CorporationsMultidisciplinaryCorporate governanceApplied MathematicsPhysics05 social sciencesCommerceComputer Science - Social and Information NetworksComplex SystemsSocial Control PoliciesCore (game theory)Interdisciplinary PhysicsGeneral Finance (q-fin.GN)Quantitative Finance - General FinanceResearch ArticlePhysics - Physics and SocietyControl (management)FOS: Physical sciencesSpatial Economic AnalysisPhysics and Society (physics.soc-ph)BiologyStatistical MechanicsFOS: Economics and businessFinancial management0502 economics and business0103 physical sciencesownership corporate control network theoryStructure of MarketsSocial and Information Networks (cs.SI)business.industryFinancial marketlcsh:RIndustrial Organizationlcsh:QbusinessMathematicsPloS one
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Epidemic spreading and aging in temporal networks with memory

2018

Time-varying network topologies can deeply influence dynamical processes mediated by them. Memory effects in the pattern of interactions among individuals are also known to affect how diffusive and spreading phenomena take place. In this paper we analyze the combined effect of these two ingredients on epidemic dynamics on networks. We study the susceptible-infected-susceptible (SIS) and the susceptible-infected-removed (SIR) models on the recently introduced activity-driven networks with memory. By means of an activity-based mean-field approach we derive, in the long time limit, analytical predictions for the epidemic threshold as a function of the parameters describing the distribution of …

FOS: Computer and information sciencesPhysics - Physics and SocietyComputer scienceAnalytical predictionsEpidemic dynamicsFOS: Physical sciencesPhysics and Society (physics.soc-ph)Network topology01 natural sciences010305 fluids & plasmasNetworks and Complex Systems0103 physical sciencesQuantitative Biology::Populations and EvolutionStatistical physicsLimit (mathematics)010306 general physicsQuantitative Biology - Populations and EvolutionEpidemic controlSocial and Information Networks (cs.SI)Populations and Evolution (q-bio.PE)Computer Science - Social and Information NetworksFunction (mathematics)Computer Science::Social and Information NetworksArticlesDynamic modelsEpidemic thresholdEpidemic spreadingFOS: Biological sciencesMean field approachPhysical Review. E
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Centrality measures for networks with community structure

2016

Understanding the network structure, and finding out the influential nodes is a challenging issue in the large networks. Identifying the most influential nodes in the network can be useful in many applications like immunization of nodes in case of epidemic spreading, during intentional attacks on complex networks. A lot of research is done to devise centrality measures which could efficiently identify the most influential nodes in the network. There are two major approaches to the problem: On one hand, deterministic strategies that exploit knowledge about the overall network topology in order to find the influential nodes, while on the other end, random strategies are completely agnostic ab…

FOS: Computer and information sciencesStatistics and ProbabilityPhysics - Physics and SocietyExploitComplex networksFOS: Physical sciencesNetwork sciencePhysics and Society (physics.soc-ph)Network theoryMachine learningcomputer.software_genreNetwork topologyImmunization strategies01 natural sciences010305 fluids & plasmas0103 physical sciences010306 general physicsMathematicsSocial and Information Networks (cs.SI)Structure (mathematical logic)[PHYS.PHYS]Physics [physics]/Physics [physics]business.industryCommunity structureComputer Science - Social and Information NetworksComplex networkEpidemic dynamicsCondensed Matter Physics[ PHYS.PHYS ] Physics [physics]/Physics [physics]Community structureArtificial intelligenceData miningbusinessCentralitycomputer
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