Search results for "construct"

showing 10 items of 3723 documents

Search for sterile neutrino mixing using three years of IceCube DeepCore data

2017

Physical review / D 95(11), 112002(2017). doi:10.1103/PhysRevD.95.112002

FLUXSterile neutrinoParticle physicsPhysics and Astronomy (miscellaneous)Physics::Instrumentation and DetectorsSolar neutrinoAstrophysics::High Energy Astrophysical PhenomenaFOS: Physical sciences01 natural sciences530High Energy Physics - ExperimentOSCILLATION EXPERIMENTSHigh Energy Physics - Experiment (hep-ex)High Energy Physics - Phenomenology (hep-ph)0103 physical sciencesTRACK RECONSTRUCTIONddc:530010306 general physicsNeutrino oscillationPhysics010308 nuclear & particles physicsHigh Energy Physics::PhenomenologyAstronomySolar neutrino problemLINE-EXPERIMENT-SIMULATORMODELHigh Energy Physics - PhenomenologyNeutrino detectorPhysics and AstronomyMeasurements of neutrino speedHigh Energy Physics::ExperimentNeutrino astronomyNeutrino
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Adaptive learning of compressible strings

2020

Suppose an oracle knows a string $S$ that is unknown to us and that we want to determine. The oracle can answer queries of the form "Is $s$ a substring of $S$?". In 1995, Skiena and Sundaram showed that, in the worst case, any algorithm needs to ask the oracle $\sigma n/4 -O(n)$ queries in order to be able to reconstruct the hidden string, where $\sigma$ is the size of the alphabet of $S$ and $n$ its length, and gave an algorithm that spends $(\sigma-1)n+O(\sigma \sqrt{n})$ queries to reconstruct $S$. The main contribution of our paper is to improve the above upper-bound in the context where the string is compressible. We first present a universal algorithm that, given a (computable) compre…

FOS: Computer and information sciencesCentroid decompositionGeneral Computer ScienceString compressionAdaptive learningKolmogorov complexityContext (language use)Data_CODINGANDINFORMATIONTHEORYString reconstructionTheoretical Computer ScienceCombinatoricsString reconstruction; String learning; Adaptive learning; Kolmogorov complexity; String compression; Lempel-Ziv; Centroid decomposition; Suffix treeSuffix treeIntegerComputer Science - Data Structures and AlgorithmsOrder (group theory)Data Structures and Algorithms (cs.DS)Adaptive learning; Centroid decomposition; Kolmogorov complexity; Lempel-Ziv; String compression; String learning; String reconstruction; Suffix treeTime complexityComputer Science::DatabasesMathematicsLempel-ZivSettore INF/01 - InformaticaLinear spaceString (computer science)SubstringBounded functionString learningTheoretical Computer Science
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Structured query construction via knowledge graph embedding

2020

In order to facilitate the accesses of general users to knowledge graphs, an increasing effort is being exerted to construct graph-structured queries of given natural language questions. At the core of the construction is to deduce the structure of the target query and determine the vertices/edges which constitute the query. Existing query construction methods rely on question understanding and conventional graph-based algorithms which lead to inefficient and degraded performances facing complex natural language questions over knowledge graphs with large scales. In this paper, we focus on this problem and propose a novel framework standing on recent knowledge graph embedding techniques. Our…

FOS: Computer and information sciencesComputer Science - Machine LearningComputer Science - Computation and LanguageComputer Science - Artificial Intelligenceknowledge graph embeddingnatural language question answeringkyselykieletMachine Learning (cs.LG)luonnollinen kieliArtificial Intelligence (cs.AI)knowledge graphquery constructionComputation and Language (cs.CL)tietomallit
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Deep Non-Line-of-Sight Reconstruction

2020

The recent years have seen a surge of interest in methods for imaging beyond the direct line of sight. The most prominent techniques rely on time-resolved optical impulse responses, obtained by illuminating a diffuse wall with an ultrashort light pulse and observing multi-bounce indirect reflections with an ultrafast time-resolved imager. Reconstruction of geometry from such data, however, is a complex non-linear inverse problem that comes with substantial computational demands. In this paper, we employ convolutional feed-forward networks for solving the reconstruction problem efficiently while maintaining good reconstruction quality. Specifically, we devise a tailored autoencoder architect…

FOS: Computer and information sciencesComputer Science - Machine Learningbusiness.industryComputer scienceComputer Vision and Pattern Recognition (cs.CV)Image and Video Processing (eess.IV)Computer Science - Computer Vision and Pattern RecognitionNonlinear optics020207 software engineering02 engineering and technologyIterative reconstructionInverse problemElectrical Engineering and Systems Science - Image and Video ProcessingAutoencoderRendering (computer graphics)Machine Learning (cs.LG)Non-line-of-sight propagation0202 electrical engineering electronic engineering information engineeringFOS: Electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingComputer visionArtificial intelligencebusiness
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A novel approach to integration by parts reduction

2015

Integration by parts reduction is a standard component of most modern multi-loop calculations in quantum field theory. We present a novel strategy constructed to overcome the limitations of currently available reduction programs based on Laporta's algorithm. The key idea is to construct algebraic identities from numerical samples obtained from reductions over finite fields. We expect the method to be highly amenable to parallelization, show a low memory footprint during the reduction step, and allow for significantly better run-times.

FOS: Computer and information sciencesComputer Science - Symbolic ComputationHigh Energy Physics - TheoryPhysicsNuclear and High Energy Physics010308 nuclear & particles physicsFOS: Physical sciencesConstruct (python library)Symbolic Computation (cs.SC)01 natural scienceslcsh:QC1-999Computational scienceReduction (complexity)High Energy Physics - PhenomenologyHigh Energy Physics - Phenomenology (hep-ph)Finite fieldHigh Energy Physics - Theory (hep-th)Component (UML)0103 physical sciencesKey (cryptography)Memory footprintIntegration by partsAlgebraic number010306 general physicslcsh:PhysicsPhysics Letters B
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A Two-Stage Reconstruction of Microstructures with Arbitrarily Shaped Inclusions

2020

The main goal of our research is to develop an effective method with a wide range of applications for the statistical reconstruction of heterogeneous microstructures with compact inclusions of any shape, such as highly irregular grains. The devised approach uses multi-scale extended entropic descriptors (ED) that quantify the degree of spatial non-uniformity of configurations of finite-sized objects. This technique is an innovative development of previously elaborated entropy methods for statistical reconstruction. Here, we discuss the two-dimensional case, but this method can be generalized into three dimensions. At the first stage, the developed procedure creates a set of black synthetic …

FOS: Computer and information sciencesComputer science02 engineering and technologylcsh:Technology01 natural sciencesArticleComputational Engineering Finance and Science (cs.CE)0103 physical sciencesCluster (physics)Effective methodGeneral Materials ScienceComputer Science - Computational Engineering Finance and Sciencelcsh:Microscopy010306 general physicslcsh:QC120-168.85lcsh:QH201-278.5Pixellcsh:Tmulti-scale entropic descriptorsrandom heterogeneous materials021001 nanoscience & nanotechnologyMicrostructureStandard techniqueCement pastetwo-stage reconstructionlcsh:TA1-2040simulated annealing for clustersSimulated annealinglcsh:Descriptive and experimental mechanicslcsh:Electrical engineering. Electronics. Nuclear engineeringlcsh:Engineering (General). Civil engineering (General)0210 nano-technologylcsh:TK1-9971AlgorithmMaterials
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Validation of the Virtual Reality Neuroscience Questionnaire: Maximum Duration of Immersive Virtual Reality Sessions Without the Presence of Pertinen…

2019

Research suggests that the duration of a VR session modulates the presence and intensity of VRISE, but there are no suggestions regarding the appropriate maximum duration of VR sessions. The implementation of high-end VR HMDs in conjunction with ergonomic VR software seems to mitigate the presence of VRISE substantially. However, a brief tool does not currently exist to appraise and report both the quality of software features and VRISE intensity quantitatively. The VRNQ was developed to assess the quality of VR software in terms of user experience, game mechanics, in-game assistance, and VRISE. Forty participants aged between 28 and 43 years were recruited (18 gamers and 22 non-gamers) for…

FOS: Computer and information sciencesJ.4Computer Science - Human-Computer InteractionB.8neuropsychologyneuroscienceComputer Science - Computers and Society[SCCO]Cognitive scienceBehavioral Neuroscience0302 clinical medicineSoftwareUser experience designB.8; C.4; D.0; J.4Original Research05 social sciencesVirtual RealityNeuropsychologyVR sicknessMultimedia (cs.MM)Psychiatry and Mental healthNeuropsychology and Physiological Psychologymotion sicknessNeurology[SCCO.PSYC]Cognitive science/Psychologycybersicknessvirtual realityPsychologyC.4psychologyVirtual realityCognitive neuroscience050105 experimental psychologylcsh:RC321-571Human-Computer Interaction (cs.HC)03 medical and health sciencesComputers and Society (cs.CY)Immersion (virtual reality)0501 psychology and cognitive sciences[INFO.INFO-HC]Computer Science [cs]/Human-Computer Interaction [cs.HC]lcsh:Neurosciences. Biological psychiatry. NeuropsychiatryBiological PsychiatryGame mechanicsbusiness.industry[SCCO.NEUR]Cognitive science/NeuroscienceVRISEConstruct validityD.0businessNeuroscienceComputer Science - Multimedia030217 neurology & neurosurgeryFrontiers in Human Neuroscience
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Catalan words avoiding pairs of length three patterns

2021

Catalan words are particular growth-restricted words counted by the eponymous integer sequence. In this article we consider Catalan words avoiding a pair of patterns of length 3, pursuing the recent initiating work of the first and last authors and of S. Kirgizov where (among other things) the enumeration of Catalan words avoiding a patterns of length 3 is completed. More precisely, we explore systematically the structural properties of the sets of words under consideration and give enumerating results by means of recursive decomposition, constructive bijections or bivariate generating functions with respect to the length and descent number. Some of the obtained enumerating sequences are kn…

FOS: Computer and information sciencesMathematics::CombinatoricsDiscrete Mathematics (cs.DM)General Computer ScienceInteger sequenceBivariate analysisConstructivelanguage.human_languageTheoretical Computer ScienceCombinatorics[MATH.MATH-CO] Mathematics [math]/Combinatorics [math.CO]FOS: MathematicsEnumerationlanguageDiscrete Mathematics and CombinatoricsMathematics - CombinatoricsCatalanCombinatorics (math.CO)Recursive decompositionBijection injection and surjectionMathematicsDescent (mathematics)Computer Science - Discrete Mathematics
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Real-time computation of parameter fitting and image reconstruction using graphical processing units

2016

Abstract In recent years graphical processing units (GPUs) have become a powerful tool in scientific computing. Their potential to speed up highly parallel applications brings the power of high performance computing to a wider range of users. However, programming these devices and integrating their use in existing applications is still a challenging task. In this paper we examined the potential of GPUs for two different applications. The first application, created at Paul Scherrer Institut (PSI), is used for parameter fitting during data analysis of μ SR (muon spin rotation, relaxation and resonance) experiments. The second application, developed at ETH, is used for PET (Positron Emission T…

FOS: Computer and information sciencesMulti-core processorSpeedup010308 nuclear & particles physicsComputer scienceComputationFOS: Physical sciencesGeneral Physics and AstronomyIterative reconstructionComputational Physics (physics.comp-ph)Supercomputer01 natural sciences030218 nuclear medicine & medical imagingComputational science03 medical and health sciencesRange (mathematics)CUDA0302 clinical medicineComputer Science - Distributed Parallel and Cluster ComputingHardware and Architecture0103 physical sciencesSingle-coreDistributed Parallel and Cluster Computing (cs.DC)Physics - Computational PhysicsComputer Physics Communications
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Multispectral image denoising with optimized vector non-local mean filter

2016

Nowadays, many applications rely on images of high quality to ensure good performance in conducting their tasks. However, noise goes against this objective as it is an unavoidable issue in most applications. Therefore, it is essential to develop techniques to attenuate the impact of noise, while maintaining the integrity of relevant information in images. We propose in this work to extend the application of the Non-Local Means filter (NLM) to the vector case and apply it for denoising multispectral images. The objective is to benefit from the additional information brought by multispectral imaging systems. The NLM filter exploits the redundancy of information in an image to remove noise. A …

FOS: Computer and information sciencesMulti-spectral imaging systemsComputer Vision and Pattern Recognition (cs.CV)Optimization frameworkMultispectral imageComputer Science - Computer Vision and Pattern Recognition02 engineering and technologyWhite noisePixels[SPI]Engineering Sciences [physics][ SPI ] Engineering Sciences [physics]0202 electrical engineering electronic engineering information engineeringComputer visionUnbiased risk estimatorMultispectral imageMathematicsMultispectral imagesApplied MathematicsBilateral FilterNumerical Analysis (math.NA)Non-local meansAdditive White Gaussian noiseStein's unbiased risk estimatorIlluminationComputational Theory and MathematicsRestorationImage denoisingsymbols020201 artificial intelligence & image processingNon-local mean filtersComputer Vision and Pattern RecognitionStatistics Probability and UncertaintyGaussian noise (electronic)Non- local means filtersAlgorithmsNoise reductionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONFace Recognitionsymbols.namesakeNoise RemovalArtificial IntelligenceFOS: MathematicsParameter estimationMedian filterMathematics - Numerical AnalysisElectrical and Electronic EngineeringFusionPixelbusiness.industryVector non-local mean filter020206 networking & telecommunicationsPattern recognitionFilter (signal processing)Bandpass filters[ SPI.TRON ] Engineering Sciences [physics]/Electronics[SPI.TRON]Engineering Sciences [physics]/ElectronicsStein's unbiased risk estimators (SURE)NoiseAdditive white Gaussian noiseComputer Science::Computer Vision and Pattern RecognitionSignal ProcessingArtificial intelligenceReconstructionbusinessModel
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