Search results for "Number"

showing 10 items of 3939 documents

A Constructive Arboricity Approximation Scheme

2020

The arboricity \(\varGamma \) of a graph is the minimum number of forests its edge set can be partitioned into. Previous approximation schemes were nonconstructive, i.e., they approximate the arboricity as a value without computing a corresponding forest partition. This is because they operate on pseudoforest partitions or the dual problem of finding dense subgraphs.

PseudoforestArboricityApproximation algorithm0102 computer and information sciences02 engineering and technology01 natural sciencesConstructiveCombinatoricsSet (abstract data type)Computer Science::Discrete Mathematics010201 computation theory & mathematics0202 electrical engineering electronic engineering information engineeringGraph (abstract data type)Partition (number theory)020201 artificial intelligence & image processingMatroid partitioningComputer Science::Data Structures and AlgorithmsGeneralLiterature_REFERENCE(e.g.dictionariesencyclopediasglossaries)Computer Science::Distributed Parallel and Cluster ComputingMathematicsofComputing_DISCRETEMATHEMATICSMathematics
researchProduct

Graphical metric space: a generalized setting in fixed point theory

2016

Building on recent ideas of Jachymski, we work on the notion of graphical metric space and prove an analogous result for the contraction mapping principle. In particular, the triangular inequality is replaced by a weaker one, which is satisfied by only those points which are situated on some path included in the graphical structure associated with the space. Some consequences, examples and an application to integral equations are presented to confirm the significance and unifying power of obtained generalizations.

Pseudometric space01 natural sciencesGraphIntrinsic metricOrdered metric spaceSettore MAT/05 - Analisi MatematicaGraphical metric spaceContraction mapping0101 mathematicsMathematicsDiscrete mathematicsAlgebra and Number TheoryApplied MathematicsInjective metric space010102 general mathematicsFixed pointConvex metric space010101 applied mathematicsAlgebraComputational MathematicsMetric spaceGeometry and TopologySettore MAT/03 - GeometriaMetric differentialAnalysisFisher information metric
researchProduct

On the collision property of chaotic iterations based post-treatments over cryptographic pseudorandom number generators

2018

International audience; There is not a proper mathematical definition of chaos, we have instead a quite big amount of definitions, each of one describes chaos in a more or less general context. Taking in account this, it is clear why it is hard to design an algorithm that produce random numbers, a kind of algorithm that could have plenty of concrete appliceautifat (anul)d bions. However we must use a finite state machine (e.g. a laptop) to produce such a sequence of random numbers, thus it is convenient, for obvious reasons, to redefine those aimed sequences as pseudorandom; also problems arise with floating point arithmetic if one wants to recover some real chaotic property (i.e. propertie…

Pseudorandom number generator020203 distributed computingSequenceFinite-state machineDynamical systems theoryComputer science010102 general mathematicsChaotic[INFO.INFO-SE]Computer Science [cs]/Software Engineering [cs.SE]02 engineering and technology[INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation01 natural sciences[INFO.INFO-IU]Computer Science [cs]/Ubiquitous Computing[INFO.INFO-CR]Computer Science [cs]/Cryptography and Security [cs.CR][INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA]0202 electrical engineering electronic engineering information engineering[INFO.INFO-ET]Computer Science [cs]/Emerging Technologies [cs.ET][INFO.INFO-DC]Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC]0101 mathematicsBoolean functionAlgorithmRandomnessGenerator (mathematics)2018 IEEE Middle East and North Africa Communications Conference (MENACOMM)
researchProduct

Domain Generation Algorithm Detection Using Machine Learning Methods

2018

A botnet is a network of private computers infected with malicious software and controlled as a group without the knowledge of the owners. Botnets are used by cybercriminals for various malicious activities, such as stealing sensitive data, sending spam, launching Distributed Denial of Service (DDoS) attacks, etc. A Command and Control (C&C) server sends commands to the compromised hosts to execute those malicious activities. In order to avoid detection, recent botnets such as Conficker, Zeus, and Cryptolocker apply a technique called Domain-Fluxing or Domain Name Generation Algorithms (DGA), in which the infected bot periodically generates and tries to resolve a large number of pseudorando…

Pseudorandom number generatorDomain generation algorithmAlphanumericComputer sciencebusiness.industryDomain Name SystemComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKSBotnetDenial-of-service attackMachine learningcomputer.software_genreComputingMilieux_MANAGEMENTOFCOMPUTINGANDINFORMATIONSYSTEMSCryptoLockerMalwareArtificial intelligencebusinesscomputer
researchProduct

Backoff Hardware Architecture for Inter-FPGA Traffic Management

2017

International audience; Multi-FPGA platforms are considered to be the mostappropriate experimental way to emulate a large Multi-ProcessorSystem-on-Chip based on a Network-on-Chip. However, theuse of a Network-on-Chip in several FPGAs requires inter-FPGA communication links to replace intra-FPGA links betweenrouters. As the ratio of the logic capacity to the number of IOsonly increases slowly with each generation of FPGA, IOs inFPGA are becoming a scare resource. And as there are morerouters than IOs, using a Network-on-Chip requires sharinginter-FPGA links between routers, and sharing an external linkcan lead to bottlenecks. Here, we evaluate the inter-FPGA trafficmanagement using a backoff…

Pseudorandom number generatorHardware architecturebusiness.industryComputer science020206 networking & telecommunications02 engineering and technology020202 computer hardware & architecture[INFO.INFO-ES] Computer Science [cs]/Embedded SystemsResource (project management)Network on a chipPRNGEmbedded system0202 electrical engineering electronic engineering information engineeringHardware_INTEGRATEDCIRCUITS[INFO.INFO-ES]Computer Science [cs]/Embedded Systems[ INFO.INFO-ES ] Computer Science [cs]/Embedded SystemsRouting (electronic design automation)ArchitecturebusinessField-programmable gate arrayinter-FPGA linkBackOff architectureNoC
researchProduct

Compact and Field Portable Biophotonic Sensors for Automated Cell Identification (Plenary Address)

2021

In this Plenary address paper, we overview recently published work for automated cell identification using 3D optical imaging in compact and field portable biophotonic sensors. Digital holographic microscopy systems and lensless pseudorandom phase encoding systems capture 3D information of biological cells and make highly accurate automated cell identification possible. Overviewed systems include sickle cell disease diagnosis based on spatio-temporal cell dynamics in a field-portable 3D-printed shearing digital holography as well as lensless cell identification of both single and multicell samples using pseudorandom phase encoding.

Pseudorandom number generatorIdentification (information)Optical imagingbusiness.industryComputer scienceEncoding (memory)Digital holographic microscopybusinessComputer hardwareField (computer science)Digital holography
researchProduct

Multidimensional pseudo-random pulse signals and their coincidence properties

1996

Pseudorandom number generatorPhysicsNuclear and High Energy PhysicsInstrumentationCoincidenceComputational physicsPulse (physics)Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment
researchProduct

Study on the Effects of Pseudorandom Generation Quality on the Performance of Differential Evolution

2011

Experiences in the field of Monte Carlo methods indicate that the quality of a random number generator is exceedingly significant for obtaining good results. This result has not been demonstrated in the field of evolutionary optimization, and many practitioners of the field assume that the choice of the generator is superfluous and fail to document this aspect of their algorithm. In this paper, we demonstrate empirically that the requirement of high quality generator does not hold in the case of Differential Evolution.

Pseudorandom number generatorRandom number generationLinear congruential generatormedicine.medical_treatmentRandom seedPseudorandomnessmedicinePseudorandom generators for polynomialsPseudorandom generatorPseudorandom generator theoremAlgorithmMathematics
researchProduct

Considerations on correlations in shift-register pseudorandom number generators and their removal

1997

Abstract We present a simple calculation quantitatively explaining the triplet correlations in the popular shift-register random number generator “R250”, which were recently observed numerically by Schmid and Wilding, and are known from general analysis of this type of generator. Starting from these considerations, we discuss various methods to remove these correlations by combining different shift-register generators. We implement and test a particularly simple and fast version, based on an XOR combination of two independent shift-register generators with different time lags. The results indicate that this generator has much better statistical properties than R250, while being only a facto…

Pseudorandom number generatorRandom number generationmedicine.medical_treatmentPseudorandomnessGeneral Physics and AstronomyPseudorandom generatorPseudorandom generator theoremLagged Fibonacci generatorHardware and ArchitectureLinear congruential generatormedicinePseudorandom generators for polynomialsAlgorithmMathematicsComputer Physics Communications
researchProduct

Parallelization of the Wolff single-cluster algorithm.

2010

A parallel [open multiprocessing (OpenMP)] implementation of the Wolff single-cluster algorithm has been developed and tested for the three-dimensional (3D) Ising model. The developed procedure is generalizable to other lattice spin models and its effectiveness depends on the specific application at hand. The applicability of the developed methodology is discussed in the context of the applications, where a sophisticated shuffling scheme is used to generate pseudorandom numbers of high quality, and an iterative method is applied to find the critical temperature of the 3D Ising model with a great accuracy. For the lattice with linear size L=1024, we have reached the speedup about 1.79 times …

Pseudorandom number generatorSpeedupShufflingIterative methodSpin modelIsing modelMultiprocessingParallel computingSerial codeAlgorithmMathematicsPhysical review. E, Statistical, nonlinear, and soft matter physics
researchProduct