Search results for "Networks"

showing 10 items of 3260 documents

Correlation Analysis of Node and Edge Centrality Measures in Artificial Complex Networks

2021

The role of an actor in a social network is identified through a set of measures called centrality. Degree centrality, betweenness centrality, closeness centrality, and clustering coefficient are the most frequently used metrics to compute the node centrality. Their computational complexity in some cases makes unfeasible, when not practically impossible, their computations. For this reason, we focused on two alternative measures, WERW-Kpath and Game of Thieves, which are at the same time highly descriptive and computationally affordable. Our experiments show that a strong correlation exists between WERW-Kpath and Game of Thieves and the classical centrality measures. This may suggest the po…

Theoretical computer scienceSettore INF/01 - InformaticaComputational complexity theorySocial networkComputer sciencebusiness.industryNode (networking)Complex networksComplex networkSocial network analysisK-pathBetweenness centralityCentrality measuresCorrelation coefficientsCentralitybusinessSocial network analysisClustering coefficient
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Game of Thieves and WERW-Kpath: Two Novel Measures of Node and Edge Centrality for Mafia Networks

2021

Real-world complex systems can be modeled as homogeneous or heterogeneous graphs composed by nodes connected by edges. The importance of nodes and edges is formally described by a set of measures called centralities which are typically studied for graphs of small size. The proliferation of digital collection of data has led to huge graphs with billions of nodes and edges. For this reason, we focus on two new algorithms, Game of Thieves and WERW-Kpath which are computationally-light alternatives to the canonical centrality measures such as degree, node and edge betweenness, closeness and clustering. We explore the correlation among these measures using the Spearman’s correlation coefficient …

Theoretical computer scienceSettore INF/01 - InformaticaDegree (graph theory)Computer scienceClosenessComplex networksMafia networksComplex networkCorrelationComputational complexityBetweenness centralityNode (computer science)CentralityRank (graph theory)Cluster analysisCentrality
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Artificial Intelligence + Distributed Systems = Agents

2009

The connection with Wirth’s book goes beyond the title, albeit confining the area to modern Artificial Intelligence (AI). Whereas thirty years ago, to devise effective programs, it became necessary to enhance the classical algorithmic framework with approaches applied to limited and focused subdomains, in the context of broad-band technology and semantic web, applications - running in open, heterogeneous, dynamic and uncertain environments-current paradigms are not enough, because of the shift from programs to processes. Beside the structure as position paper, to give more weight to some basic assertions, results of recent research are abridged and commented upon in line with new paradigms.…

Theoretical computer scienceSpeedupComputer Networks and CommunicationsComputer sciencebusiness.industryDesign elements and principlesBounded rationalityComputer Science ApplicationsSoftwareComputational Theory and MathematicsPosition paperArtificial intelligencebusinessSemantic WebMerge (version control)International Journal of Computers Communications & Control
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Social network analysis: the use of graph distances to compare artificial and criminal networks

2021

Aim: Italian criminal groups become more and more dangerous spreading their activities into new sectors. A criminal group is made up of networks of hundreds of family gangs which extended their influence across the world, raking in billions from drug trafficking, extortion and money laundering. We focus in particular on the analysis of the social structure of two Sicilian crime families and we used a Social Network Analysis approach to study the social phenomena. Starting from a real criminal network extracted from meetings emerging from the police physical surveillance during 2000s, we here aim to create artificial models that present similar properties. Methods: We use specific tools of s…

Theoretical computer sciencesocial network analysisSpectral distanceSettore INF/01 - InformaticaComputer sciencegraph theorySocial network analysis (criminology)social network analysiGraph theoryspectral distancenetwork modelCriminal networksCriminal networkGraph (abstract data type)Criminal networks social network analysis graph theory spectral distance network modelNetwork model
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The computational power of continuous time neural networks

1997

We investigate the computational power of continuous-time neural networks with Hopfield-type units. We prove that polynomial-size networks with saturated-linear response functions are at least as powerful as polynomially space-bounded Turing machines.

TheoryofComputation_COMPUTATIONBYABSTRACTDEVICESQuantitative Biology::Neurons and CognitionComputational complexity theoryArtificial neural networkComputer sciencebusiness.industryComputer Science::Neural and Evolutionary ComputationNSPACEComputational resourcePower (physics)Turing machinesymbols.namesakeCellular neural networksymbolsArtificial intelligenceTypes of artificial neural networksbusiness
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Some Afterthoughts on Hopfield Networks

1999

In the present paper we investigate four relatively independent issues, which complete our knowledge regarding the computational aspects of popular Hopfield nets. In Section 2 of the paper, the computational equivalence of convergent asymmetric and Hopfield nets is shown with respect to network size. In Section 3, the convergence time of Hopfield nets is analyzed in terms of bit representations. In Section 4, a polynomial time approximate algorithm for the minimum energy problem is shown. In Section 5, the Turing universality of analog Hopfield nets is studied. peerReviewed

TheoryofComputation_COMPUTATIONBYABSTRACTDEVICESQuantitative Biology::Neurons and CognitionComputer scienceParallel algorithmHopfield netsApproximation algorithmSection (fiber bundle)Hopfield networknetworksHopfieldAlgorithmTime complexityEquivalence (measure theory)Energy (signal processing)
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Heterogeneous network games: Conflicting preferences

2013

Proceeding at: 2nd Annual UECE Lisbon Meeting: Game Theory and Applications, took place 2010, November, 4-6, in Lisbon (Portugal). The event Web site http://pascal.iseg.utl.pt/~uece/lisbonmeetings2010/ In many economic situations, a player pursues coordination or anti-coordination with her neighbors on a network, but she also has intrinsic preferences among the available options. We here introduce a model which allows to analyze this issue by means of a simple framework in which players endowed with an idiosyncratic identity interact on a social network through strategic complements or substitutes. We classify the possible types of Nash equilibria under complete information, finding two thr…

TheoryofComputation_MISCELLANEOUSComputer Science::Computer Science and Game Theoryjel:Z13Economics and EconometricsMatemáticasjel:D85Heterogeneity Networks Nash Equilibrium StabilitySocial networksjel:D03MicroeconomicsCOMPLEMENTARITIESsymbols.namesakeBayesian gameEconomicsCoordination gameStrategic complementsjel:C72ComputingMilieux_PERSONALCOMPUTINGTheoryofComputation_GENERALNetwork formationNash equilibriumEquilibrium selectionBest responsejel:L14Bayesian equilibriumsymbolsHeterogeneityEpsilon-equilibriumMathematical economicsFinanceIncomplete informationGames and Economic Behavior
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ChemInform Abstract: Relaxation Phenomena of a Triplet Spin Probe in Glassy and Crystalline o-Terphenyl.

2010

The authors used quinoxaline in its photoexcited triplet state as a spin probe in order to measure the spin-lattice relaxation rate in o-terphenyl glass as a function of temperature. They found a power law with an exponent close to 2. Since o-terphenyl can easily be crystallized, they investigated the crystal, too. Below 3.5 K the spin is highly polarized, contrary to the behavior in the glass, where it reaches thermal equilibrium down to the lowest temperatures of their experiment (1.4 K). Around 3.5 K the polarization in the crystal vanishes. Above it appears with opposite sign due to thermal equilibration.

Thermal equilibriumCondensed matter physicsGeneral MedicinePolarization (waves)Condensed Matter::Disordered Systems and Neural NetworksSpin probeCrystalchemistry.chemical_compoundchemistryTerphenylOrganic chemistryTriplet stateLuminescenceSpin (physics)ChemInform
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Serine- and Threonine/Valine-Dependent Activation of PDK and Tor Orthologs Converge on Sch9 to Promote Aging

2014

Dietary restriction extends longevity in organisms ranging from bacteria to mice and protects primates from a variety of diseases, but the contribution of each dietary component to aging is poorly understood. Here we demonstrate that glucose and specific amino acids promote stress sensitization and aging through the differential activation of the Ras/cAMP/PKA, PKH1/2 and Tor/S6K pathways. Whereas glucose sensitized cells through a Ras-dependent mechanism, threonine and valine promoted cellular sensitization and aging primarily by activating the Tor/S6K pathway and serine promoted sensitization via PDK1 orthologs Pkh1/2. Serine, threonine and valine activated a signaling network in which Sch…

ThreonineCancer ResearchAgingSerineMice0302 clinical medicineSettore BIO/13 - Biologia ApplicataGene Expression Regulation FungalMolecular Cell BiologySerineSignaling in Cellular ProcessesThreonineGenetics (clinical)Cellular Stress Responses0303 health sciencesageing longevity Sch9 Tor Pkhs nutrients amino acidssurvival stress resistanceMechanisms of Signal TransductionValineCell biologyBiochemistryPhosphorylationSignal transductionResearch ArticleSignal TransductionSaccharomyces cerevisiae Proteinslcsh:QH426-470Adenylyl Cyclase Signaling PathwayLongevityP70-S6 Kinase 1Ras SignalingSaccharomyces cerevisiaeBiologyMicrobiologySignaling Pathways3-Phosphoinositide-Dependent Protein Kinases03 medical and health sciencesModel OrganismsStress PhysiologicalGeneticsAnimalsGene NetworksProtein kinase AMolecular BiologyTranscription factorBiologyEcology Evolution Behavior and Systematics030304 developmental biologySerine/threonine-specific protein kinase[SDV.GEN]Life Sciences [q-bio]/GeneticsCyclic AMP-Dependent Protein Kinaseslcsh:GeneticsGlucoseFoodTor SignalingProtein Kinases030217 neurology & neurosurgeryTranscription Factors
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Computational evidence that frequency trajectory theory does not oppose but emerges from age-of-acquisition theory.

2012

International audience; According to the age-of-acquisition hypothesis, words acquired early in life are processed faster and more accurately than words acquired later. Connectionist models have begun to explore the influence of the age/order of acquisition of items (and also their frequency of encounter). This study attempts to reconcile two different methodological and theoretical approaches (proposed by Lambon Ralph & Ehsan, 2006 and Zevin & Seidenberg, 2002) to age-limited learning effects. The current simulations extend the findings reported by Zevin and Seidenberg (2002) that have shown that frequency trajectories (FTs) have limited and specific effects on word-reading tasks. Using th…

Time FactorsComputer scienceTask (project management)Learning effect0302 clinical medicineMESH: Models PsychologicalComputingMilieux_MISCELLANEOUSMESH : Models PsychologicalCognitive sciencePsycholinguisticsMESH : Neural Networks (Computer)05 social sciencesAge FactorsContrast (statistics)MESH : Artificial IntelligenceLanguage acquisition[SCCO.PSYC]Cognitive science/Psychology[SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]MESH : PsycholinguisticsCognitive psychologyMESH : Time FactorsOrder of acquisitionCognitive NeuroscienceExperimental and Cognitive PsychologyMESH: ReadingModels PsychologicalLanguage Development050105 experimental psychologyMESH: Psycholinguistics03 medical and health sciencesMESH: Neural Networks (Computer)ConnectionismArtificial IntelligenceMESH: Language DevelopmentMESH: Artificial IntelligenceHumans0501 psychology and cognitive sciencesMESH: Age FactorsMESH : Language DevelopmentMESH: HumansMESH: Time FactorsMESH : HumansMESH : ReadingWord lists by frequencyAge of AcquisitionReading[ SDV.NEU ] Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]MESH : Age FactorsNeural Networks Computer030217 neurology & neurosurgeryCognitive science
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