Search results for "binary [black hole]"

showing 10 items of 170 documents

The Average State Complexity of the Star of a Finite Set of Words Is Linear

2008

We prove that, for the uniform distribution over all sets Xof m(that is a fixed integer) non-empty words whose sum of lengths is n, $\mathcal{D}_X$, one of the usual deterministic automata recognizing X*, has on average $\mathcal{O}(n)$ states and that the average state complexity of X*is i¾?(n). We also show that the average time complexity of the computation of the automaton $\mathcal{D}_X$ is $\mathcal{O}(n\log n)$, when the alphabet is of size at least three.

Uniform distribution (continuous)ComputationStar (game theory)0102 computer and information sciences02 engineering and technology[INFO.INFO-DM]Computer Science [cs]/Discrete Mathematics [cs.DM]01 natural sciencesCombinatoricsInteger0202 electrical engineering electronic engineering information engineeringTime complexityFinite setMathematicsstar operationDiscrete mathematicsaverage case analysistate complexity16. Peace & justiceBinary logarithm[INFO.INFO-DM] Computer Science [cs]/Discrete Mathematics [cs.DM]automatonState complexity010201 computation theory & mathematicsfinite language020201 artificial intelligence & image processingComputer Science::Formal Languages and Automata Theory
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2021

In COVID-19 related infodemic, social media becomes a medium for wrongdoers to spread rumors, fake news, hoaxes, conspiracies, astroturf memes, clickbait, satire, smear campaigns, and other forms of deception. It puts a tremendous strain on society by damaging reputation, public trust, freedom of expression, journalism, justice, truth, and democracy. Therefore, it is of paramount importance to detect and contain unreliable information. Multiple techniques have been proposed to detect fake news propagation in tweets based on tweets content, propagation on the network of users, and the profile of the news generators. Generating human-like content allows deceiving content-based methods. Networ…

User profileBoosting (machine learning)Information retrievalGeneral Computer ScienceComputer sciencebusiness.industryDeep learningmedia_common.quotation_subjectNode (networking)Feature extractionGeneral EngineeringComplex networkBinary classificationGeneral Materials ScienceArtificial intelligenceElectrical and Electronic EngineeringbusinessReputationmedia_commonIEEE Access
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Efficient on-the-fly Web bot detection

2021

Abstract A large fraction of traffic on present-day Web servers is generated by bots — intelligent agents able to traverse the Web and execute various advanced tasks. Since bots’ activity may raise concerns about server security and performance, many studies have investigated traffic features discriminating bots from human visitors and developed methods for automated traffic classification. Very few previous works, however, aim at identifying bots on-the-fly, trying to classify active sessions as early as possible. This paper proposes a novel method for binary classification of streams of Web server requests in order to label each active session as “bot” or “human”. A machine learning appro…

Web serverInformation Systems and ManagementComputer scienceInternet robot02 engineering and technologyMachine learningcomputer.software_genreUsage dataManagement Information SystemsIntelligent agentEarly decision; Internet robot; Machine learning; Neural network; Real-time bot detection; Sequential analysis; Web botArtificial IntelligenceReal-time bot detection020204 information systemsMachine learning0202 electrical engineering electronic engineering information engineeringFalse positive paradoxSequential analysisSession (computer science)business.industryWeb botNeural networkEarly decisionTraffic classificationBinary classification020201 artificial intelligence & image processingArtificial intelligencebusinesscomputerClassifier (UML)SoftwareKnowledge-Based Systems
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Extending CSG with projections: Towards formally certified geometric modeling

2015

We extend traditional Constructive Solid Geometry (CSG) trees to support the projection operator. Existing algorithms in the literature prove various topological properties of CSG sets. Our extension readily allows these algorithms to work on a greater variety of sets, in particular parametric sets, which are extensively used in CAD/CAM systems. Constructive Solid Geometry allows for algebraic representation which makes it easy for certification tools to apply. A geometric primitive may be defined in terms of a characteristic function, which can be seen as the zero-set of a corresponding system along with inequality constraints. To handle projections, we exploit the Disjunctive Normal Form,…

[ INFO ] Computer Science [cs]Disjoint setsDisjunctive normal formIndustrial and Manufacturing EngineeringProjection (linear algebra)Interval arithmeticConstructive solid geometryConstructive solid geometry[INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI][INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO]Homotopy equivalenceGeometric primitiveBinary expression tree[INFO]Computer Science [cs]ProjectionComputingMilieux_MISCELLANEOUSMathematicsDiscrete mathematics[INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB]HomotopyFormal methodsDisjunctive normal formComputer Graphics and Computer-Aided Design[INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR]Computer Science ApplicationsAlgebra[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV][INFO.INFO-DC]Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC]
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GW170814: A Three-Detector Observation of Gravitational Waves from a Binary Black Hole Coalescence

2017

On August 14, 2017 at 10 30:43 UTC, the Advanced Virgo detector and the two Advanced LIGO detectors coherently observed a transient gravitational-wave signal produced by the coalescence of two stellar mass black holes, with a false-alarm rate of 1 in 27 000 years. The signal was observed with a three-detector network matched-filter signal-to-noise ratio of 18. The inferred masses of the initial black holes are 30.5-3.0+5.7M and 25.3-4.2+2.8M (at the 90% credible level). The luminosity distance of the source is 540-210+130 Mpc, corresponding to a redshift of z=0.11-0.04+0.03. A network of three detectors improves the sky localization of the source, reducing the area of the 90% credible regio…

[ PHYS.ASTR ] Physics [physics]/Astrophysics [astro-ph]AstronomyCredible regionsGeneral Physics and Astronomyadvanced ligoADVANCED LIGOAstrophysicsdetector: network01 natural sciencesGeneral Relativity and Quantum CosmologylocalizationVIRGO detectorFilter signalsGW170814TOOLLIGOInterferometerGeneralLiterature_REFERENCE(e.g.dictionariesencyclopediasglossaries)010303 astronomy & astrophysicsQCchoiceQBHigh Energy Astrophysical Phenomena (astro-ph.HE)PhysicsSignal to noise ratioSettore FIS/01 - Fisica SperimentaleGravitational effectstoolFalse alarm rateCHOICEAntenna responseGravitational-wave signalsDetector networks[PHYS.GRQC]Physics [physics]/General Relativity and Quantum Cosmology [gr-qc]Astrophysics - High Energy Astrophysical Phenomenagravitational radiation: polarizationSignal processingAstrophysics::High Energy Astrophysical Phenomenablack hole: binary: coalescenceFOS: Physical sciencesGeneral Relativity and Quantum Cosmology (gr-qc)Astrophysics::Cosmology and Extragalactic Astrophysicsgravitational radiation: direct detectionGravitational-wave astronomy[ PHYS.GRQC ] Physics [physics]/General Relativity and Quantum Cosmology [gr-qc]General Relativity and Quantum CosmologyPhysics and Astronomy (all)Binary black hole0103 physical sciencesGW151226ddc:530KAGRASTFCGw150914GW170814 Virgo LIGO010308 nuclear & particles physicsGravitational wavePhysiqueVirgogravitational radiationAstronomyRCUKMatched filtersblack hole: massStarsLIGOgravitational radiation detectorBlack holeradiationVIRGOPhysics and AstronomyTesting Relativistic Gravitygravitationgravitational radiation: emissionStellar-mass black holesRADIATIONStellar black holeHigh Energy Physics::ExperimentAntennasDewey Decimal Classification::500 | Naturwissenschaften::530 | Physik[PHYS.ASTR]Physics [physics]/Astrophysics [astro-ph]
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ORNAMENTAL SIGN LANGUAGE IN THE FIRST ORDER TRACERY BELTS

2010

18 pages; We consider ornamental sign language of first order where principles of sieve displacement, of asymmetric building blocks as base of ornament symmetry, color exchangeability and side equivalence principles work. The generic aspects of sieve and genesis of ornamental pattern and ornament sign in it are discussed. The hemiolia principle for ornamental genesis is introduced. The discoverer of most of these principles were artist Modris Tenisons [4, 5, 6, 7 (refs. 23, 24), 8 (ref. 65)]. Here we apply systematical research using simplest mathematical arguments. We come to conclusions that mathematical argument in arising ornament is of much more significance than simply symmetries in i…

binary codingBH Aesthetics[MATH.MATH-GM] Mathematics [math]/General Mathematics [math.GM][SHS.ART]Humanities and Social Sciences/Art and art historyhemiolia principlefirst order complexitysieve in ornamental pattern[MATH.MATH-GM]Mathematics [math]/General Mathematics [math.GM]binary matricesQA75 Computer scienceQA Mathematics (General)[SHS.ART] Humanities and Social Sciences/Art and art historysign codingornamentsasymmetryNX Arts in general
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Normal, Abby Normal, Prefix Normal

2014

A prefix normal word is a binary word with the property that no substring has more 1s than the prefix of the same length. This class of words is important in the context of binary jumbled pattern matching. In this paper we present results about the number \(\textit{pnw}(n)\) of prefix normal words of length n, showing that \(\textit{pnw}(n) =\Omega\left(2^{n - c\sqrt{n\ln n}}\right)\) for some c and \(\textit{pnw}(n) = O \left(\frac{2^n (\ln n)^2}{n}\right)\). We introduce efficient algorithms for testing the prefix normal property and a “mechanical algorithm” for computing prefix normal forms. We also include games which can be played with prefix normal words. In these games Alice wishes t…

binary jumbled pattern matchingEfficient algorithmmembership testBinary numberContext (language use)Prefix Normal Word AlgorithmData_CODINGANDINFORMATIONTHEORYprefix normal wordsOmegaSubstringenumerationCombinatoricsPrefixprefix normal words; binary jumbled pattern matching; normal forms; enumeration; membership test; binary languagesEnumerationnormal formsbinary languagesWord (group theory)Mathematics
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Search for intermediate mass black hole binaries in the first and second observing runs of the Advanced LIGO and Virgo network

2019

Gravitational wave astronomy has been firmly established with the detection of gravitational waves from the merger of ten stellar mass binary black holes and a neutron star binary. This paper reports on the all-sky search for gravitational waves from intermediate mass black hole binaries in the first and second observing runs of the Advanced LIGO and Virgo network. The search uses three independent algorithms: two based on matched filtering of the data with waveform templates of gravitational wave signals from compact binaries, and a third, model-independent algorithm that employs no signal model for the incoming signal. No intermediate mass black hole binary event was detected in this sear…

binary: massneutron star: binaryAstronomybinary: angular momentumAstrophysicsdetector: network01 natural sciencesGeneral Relativity and Quantum CosmologyPhysics Particles & FieldsLIMITSclustersLIGOgravitational waveGeneralLiterature_REFERENCE(e.g.dictionariesencyclopediasglossaries)QCQBastro-ph.HEPhysicsHigh Energy Astrophysical Phenomena (astro-ph.HE)Settore FIS/01black hole: spinPhysicsintermediate mass black hole binarieNumerical relativityGeneral relativitygravitational wavesgravitational waves; intermediate mass black hole binaries; Advanced LIGO and VirgoPhysical Sciences[PHYS.GRQC]Physics [physics]/General Relativity and Quantum Cosmology [gr-qc]Astrophysics - High Energy Astrophysical PhenomenastarsGeneral relativitygr-qcAstrophysics::High Energy Astrophysical PhenomenaFOS: Physical sciencesalternative theories of gravitySTARS; CLUSTERS; LIMITSAstrophysics::Cosmology and Extragalactic AstrophysicsGeneral Relativity and Quantum Cosmology (gr-qc)Astronomy & Astrophysicsgravitational radiation: direct detectionGeneral Relativity and Quantum CosmologySettore FIS/05 - Astronomia e AstrofisicaBinary black hole0103 physical sciencesddc:530010306 general physicsAstrophysics::Galaxy AstrophysicsSTFCScience & Technology010308 nuclear & particles physicsGravitational waveAdvanced LIGO and Virgointermediate mass black hole binariesRCUKGravitational Wave Physicsblack hole: massMass ratiobinary: compact04.80.NnLIGOgravitational radiation detectorNeutron starVIRGOblack hole: binaryIntermediate-mass black holerelativity theorygravitational radiation: emission95.55.Ymmass ratioDewey Decimal Classification::500 | Naturwissenschaften::530 | Physik07.05.Kflimits[PHYS.ASTR]Physics [physics]/Astrophysics [astro-ph]CLUSTERSSTARSGravitational waves Black holes (astronomy) Gravitational self force
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Convergence Analysis of Distributed Set-Valued Information Systems

2016

This paper focuses on the convergence of information in distributed systems of agents communicating over a network. The information on which the convergence is sought is not rep- resented by real numbers, as often in the literature, rather by sets. The dynamics of the evolution of information across the net- work is accordingly described by set-valued iterative maps. While the study of convergence of set-valued iterative maps is highly complex in general, this paper focuses on Boolean maps, which are comprised of arbitrary combinations of unions, intersections, and complements of sets. For these important class of systems, we provide tools to study both global and local convergence. A distr…

boolean dynamic systems0209 industrial biotechnologyClass (set theory)Geographic information systemTheoretical computer scienceBinary encoding boolean dynamic systems con- sensus algorithms convergence cooperative systems distributed information systems set-valued dynamic maps.consensus algorithms02 engineering and technologyBoolean algebraSet (abstract data type)symbols.namesakecooperative systems020901 industrial engineering & automationSettore ING-INF/04 - AutomaticaConvergence (routing)0202 electrical engineering electronic engineering information engineeringInformation systemElectrical and Electronic EngineeringMathematicsReal numberconvergencebusiness.industryset-valued dynamic mapsComputer Science Applications1707 Computer Vision and Pattern Recognitiondistributed information systemsComputer Science ApplicationsLocal convergenceControl and Systems EngineeringsymbolsBinary encoding; boolean dynamic systems; consensus algorithms; convergence; cooperative systems; distributed information systems; set-valued dynamic maps; Electrical and Electronic Engineering; Control and Systems Engineering; Computer Science Applications1707 Computer Vision and Pattern RecognitionBinary encoding020201 artificial intelligence & image processingbusinessIEEE Transactions on Automatic Control
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Multi-dimensional pattern matching with dimensional wildcards

1995

We introduce a new multi-dimensional pattern matching problem, which is a natural generalization of the on-line search in string matching. We are given a text matrix A[1: n1, ..., 1:n d ] of size N= n1×n2×...×n d , which we may preprocess. Then, we are given, online, an r-dimensional pattern matrix B[1:m1,...,1:m r ] of size M= m1×m2×...×m r , with 1≤r≤d. We would like to know whether B*=B*[*, 1:m1,*, ...,1: mr, *] occurs in A, where * is a dimensional wildcard such that B* is any d-dimensional matrix having size 1 × ... × m1×...1×m r ×...1 and containing the same elements as B. Notice that there might be (d/r)≤2d occurrences of B* for each position of A. We give CRCW-PRAM algorithms for pr…

business.industryGeneralizationCommentz-Walter algorithmPattern recognitionWildcard characterString searching algorithmcomputer.file_formatApproximate string matchingBinary logarithmCombinatoricsMatrix (mathematics)Artificial intelligencePattern matchingbusinesscomputerMathematics
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