Search results for " Integra"

showing 10 items of 2527 documents

STRUCTURAL AND ARCHITECTURAL DESIGN OF AN INTEGRAL STEEL FOOTBRIDGE

2011

FOOTBRIDGE INTEGRAL ABUTMENTS STEEL BOX COMPOSITE STRUCTURE COR-TEN STEEL
researchProduct

La formazione nell’ospedalizzazione pediatrica. L’esperienza del Progetto “Prometeo”

2008

FORMAZIONE INTEGRATA OPERATORI SANITARI
researchProduct

RationalizeRoots: Software Package for the Rationalization of Square Roots

2019

The computation of Feynman integrals often involves square roots. One way to obtain a solution in terms of multiple polylogarithms is to rationalize these square roots by a suitable variable change. We present a program that can be used to find such transformations. After an introduction to the theoretical background, we explain in detail how to use the program in practice.

FOS: Computer and information sciencesComputer Science - Symbolic ComputationHigh Energy Physics - TheoryHigh energy particleFeynman integralComputationGeneral Physics and AstronomyFOS: Physical sciencesengineering.materialSymbolic Computation (cs.SC)Rationalization (economics)01 natural sciences010305 fluids & plasmasHigh Energy Physics - Phenomenology (hep-ph)Square root0103 physical sciencesComputingMethodologies_SYMBOLICANDALGEBRAICMANIPULATIONAlgebraic number010306 general physicsMathematical PhysicsVariable (mathematics)MapleMathematical Physics (math-ph)AlgebraHigh Energy Physics - PhenomenologyHigh Energy Physics - Theory (hep-th)Hardware and ArchitectureengineeringComputer Science - Mathematical SoftwareMathematical Software (cs.MS)
researchProduct

On resampling schemes for particle filters with weakly informative observations

2022

We consider particle filters with weakly informative observations (or `potentials') relative to the latent state dynamics. The particular focus of this work is on particle filters to approximate time-discretisations of continuous-time Feynman--Kac path integral models -- a scenario that naturally arises when addressing filtering and smoothing problems in continuous time -- but our findings are indicative about weakly informative settings beyond this context too. We study the performance of different resampling schemes, such as systematic resampling, SSP (Srinivasan sampling process) and stratified resampling, as the time-discretisation becomes finer and also identify their continuous-time l…

FOS: Computer and information sciencesHidden Markov modelparticle filterStatistics and ProbabilityProbability (math.PR)Markovin ketjutStatistics - ComputationMethodology (stat.ME)resamplingFOS: Mathematicsotantanumeerinen analyysiPrimary 65C35 secondary 65C05 65C60 60J25Statistics Probability and UncertaintyFeynman–Kac modeltilastolliset mallitComputation (stat.CO)path integralMathematics - ProbabilityStatistics - Methodologystokastiset prosessit
researchProduct

Symbolic integration of hyperexponential 1-forms

2019

Let $H$ be a hyperexponential function in $n$ variables $x=(x_1,\dots,x_n)$ with coefficients in a field $\mathbb{K}$, $[\mathbb{K}:\mathbb{Q}] <\infty$, and $\omega$ a rational differential $1$-form. Assume that $H\omega$ is closed and $H$ transcendental. We prove using Schanuel conjecture that there exist a univariate function $f$ and multivariate rational functions $F,R$ such that $\int H\omega= f(F(x))+H(x)R(x)$. We present an algorithm to compute this decomposition. This allows us to present an algorithm to construct a basis of the cohomology of differential $1$-forms with coefficients in $H\mathbb{K}[x,1/(SD)]$ for a given $H$, $D$ being the denominator of $dH/H$ and $S\in\mathbb{K}[x…

FOS: Computer and information sciencesMathematics - Differential GeometryComputer Science - Symbolic ComputationPure mathematicsMathematics::Commutative Algebra010102 general mathematics68W30Field (mathematics)010103 numerical & computational mathematicsFunction (mathematics)[MATH] Mathematics [math]Symbolic Computation (cs.SC)16. Peace & justiceFunctional decomposition01 natural sciencesDifferential Geometry (math.DG)FOS: MathematicsComputer Science::Symbolic Computation0101 mathematics[MATH]Mathematics [math]Symbolic integrationMathematics
researchProduct

Semantic HMC for Big Data Analysis

2014

International audience; Analyzing Big Data can help corporations to im-prove their efficiency. In this work we present a new vision to derive Value from Big Data using a Semantic Hierarchical Multi-label Classification called Semantic HMC based in a non-supervised Ontology learning process. We also proposea Semantic HMC process, using scalable Machine-Learning techniques and Rule-based reasoning.

FOS: Computer and information sciences[ INFO.INFO-TT ] Computer Science [cs]/Document and Text Processingmulti-classifyComputer scienceComputer Science - Artificial IntelligenceBig data[ INFO.INFO-WB ] Computer Science [cs]/Websemantic technologies02 engineering and technologyOntology (information science)Semantic data model[ INFO.INFO-DC ] Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC]Semantic similarity020204 information systemsSemantic computing0202 electrical engineering electronic engineering information engineeringontologyInformation retrievalOntology learningbusiness.industryOntology-based data integration[INFO.INFO-WB]Computer Science [cs]/WebBig-Data[INFO.INFO-TT]Computer Science [cs]/Document and Text ProcessingArtificial Intelligence (cs.AI)machine learningOntologySemantic technologyIndex Terms—classification020201 artificial intelligence & image processing[INFO.INFO-DC]Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC]business
researchProduct

Bayesian Analysis of Population Health Data

2021

The analysis of population-wide datasets can provide insight on the health status of large populations so that public health officials can make data-driven decisions. The analysis of such datasets often requires highly parameterized models with different types of fixed and random effects to account for risk factors, spatial and temporal variations, multilevel effects and other sources on uncertainty. To illustrate the potential of Bayesian hierarchical models, a dataset of about 500,000 inhabitants released by the Polish National Health Fund containing information about ischemic stroke incidence for a 2-year period is analyzed using different types of models. Spatial logistic regression and…

FOS: Computer and information sciencesmedicine.medical_specialtyComputer scienceGeneral MathematicsBayesian probabilitydisease mappingPopulation healthbayesian inference; disease mapping; integrated nested Laplace approximation; spatial models; survival modelsBayesian inferenceLogistic regressionStatistics - Applications01 natural sciences010104 statistics & probability03 medical and health sciences0302 clinical medicineStatisticsComputer Science (miscellaneous)medicineApplications (stat.AP)spatial models0101 mathematicsEngineering (miscellaneous)Socioeconomic statusbayesian inferencesurvival modelslcsh:MathematicsPublic healthintegrated nested Laplace approximationlcsh:QA1-939Random effects modelSpatial variability030217 neurology & neurosurgeryMathematics
researchProduct

Multiscale partial information decomposition of dynamic processes with short and long-range correlations: theory and application to cardiovascular co…

2022

Abstract Objective. In this work, an analytical framework for the multiscale analysis of multivariate Gaussian processes is presented, whereby the computation of Partial Information Decomposition measures is achieved accounting for the simultaneous presence of short-term dynamics and long-range correlations. Approach. We consider physiological time series mapping the activity of the cardiac, vascular and respiratory systems in the field of Network Physiology. In this context, the multiscale representation of transfer entropy within the network of interactions among Systolic arterial pressure (S), respiration (R) and heart period (H), as well as the decomposition into unique, redundant and s…

FOS: Computer and information sciencesmultivariate time seriesPhysiologyEntropyRespirationBiomedical EngineeringBiophysicsheart rate variabilitytransfer entropyredundancy and synergyBlood PressureHeartQuantitative Biology - Quantitative MethodsCardiovascular SystemMethodology (stat.ME)Heart RatePhysiology (medical)FOS: Biological sciencesCardiovascular controlSettore ING-INF/06 - Bioingegneria Elettronica E Informaticavector autoregressive fractionally integrated (VARFI) modelsHumansQuantitative Methods (q-bio.QM)Statistics - MethodologyPhysiological measurement
researchProduct

Granice zewnętrzne Unii Europejskiej a bezpieczeństwo narodowe państw członkowskich w kontekście współczesnego kryzysu migracyjnego

2016

Unia Europejska jest miejscem, w którym swoboda obywateli wyrażona jest poprzez możliwość przemieszania się, podróżowania, pracy,nauki lub życia w wybranym kraju UE. Realizacja tej wolności była wynikiem zniesienia kontroli na granicach wewnętrznych Unii. Jednak dla członka UE ceną tej wolności jest konieczność zapewnienia bezpieczeństwa narodowego, co sprawia, że ochronę granic zewnętrznych postrzega się jako specjalne zadanie. Unia Europejska, za pośrednictwem układu z Schengen, tworzy instytucje w zakresie ochrony granic zewnętrznych, w zakresie zapewnienia bezpieczeństwa narodowego państw członkowskich. Obecny kryzys migracyjny jest weryfikacją skuteczności tych instytucji.

FRONTEXEuropejska Sieć Patroli (EPN)Schengen Borders CodePolicy of integrated border managementKonwencja DublińskaRapid Border Intcrvention Tcams (RABIT)Układ z SchengenEuropean Border Surveillance System (EUROSUR)Prum Conventionthe Schengen ConventionKodeks Graniczny SchengenPolityka zintegrowanego zarządzania granicamiEuropean Patrols Network (EPN)Konwencja SchengenZespoły szybkiej interwencji na granicy (RAB1T)Schengen AgreementKonwencja z PrumEuropejski System Nadzoru Granicznego (EUROSUR)Dublin ConventionFRONTEX Agency
researchProduct

A fully adaptive wavelet algorithm for parabolic partial differential equations

2001

We present a fully adaptive numerical scheme for the resolution of parabolic equations. It is based on wavelet approximations of functions and operators. Following the numerical analysis in the case of linear equations, we derive a numerical algorithm essentially based on convolution operators that can be efficiently implemented as soon as a natural condition on the space of approximation is satisfied. The algorithm is extended to semi-linear equations with time dependent (adapted) spaces of approximation. Numerical experiments deal with the heat equation as well as the Burgers equation.

FTCS schemeNumerical AnalysisDifferential equationIndependent equationApplied MathematicsMathematical analysisMathematicsofComputing_NUMERICALANALYSISExponential integratorParabolic partial differential equationComputational MathematicsMultigrid methodAlgorithmMathematicsNumerical stabilityNumerical partial differential equationsApplied Numerical Mathematics
researchProduct