Search results for "Statistical"

showing 10 items of 4960 documents

An Effective Double Sampling Scheme for the c Control Chart

2015

In the present paper is developed a statistical process control inspection procedure based on a new simple-to-implement and effective double sampling scheme for the c control chart, aimed at the minimization of the number of inspected observation units and warranting fixed levels for the type I and II error risks. In particular, the formulations of the false alarm risk α, the power P of the chart, and the expected number of inspected observation units for the developed inspection procedure are given, whereas a macro of Microsoft Excel is adopted to solve the tackled problem. In order to illustrate the application of the developed approach and to investigate on the influence of several opera…

control chart for attributeexpected number of inspected observation unitstatistical process controlc control chartadaptive c control chart
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Comparing the Economic Effectiveness of Various Adaptive Schemes for the c Chart

2014

In an attempt to improve the effectiveness of statistical process control (SPC) procedures, a variety of adaptive schemes has been developed in the last decades. However, considering control charts for attributes, relatively few works about adaptive schemes have been proposed, and most of them were proposed only recently. The common characteristic of those schemes is that one or more chart parameters are allowed to adaptively vary during the SPC operations according to the sampling information history, typically the current point plotted on the chart. In this way, the adaptive schemes are smarter than the related static ones, but they are also more complicated in terms of implementation. Th…

control chart for attributelabor resourcestatistical process controlnon-linear mathematical programming modelTaguchi’s loss functionSettore ING-IND/16 - Tecnologie E Sistemi Di Lavorazione
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Economic design approach for a SPC inspection procedure implementing the adaptive c chart

2014

The present paper proposes a design approach for a statistical process control (SPC) procedure implementing a c control chart for non-conformities, with the aim to minimize the hourly total quality-related costs. The latter take into account the costs arising from the non-conforming products while the process is in-control and out-of-control, for false alarms, for assignable cause locations and system repairs, for sampling and inspection activities and for the system downtime. The proposed economic optimization approach is constrained by the expected hourly false alarms frequency, as well as the available labor resource level. A mixed integer non-linear constrained mathematical model is dev…

control chart for attributelabor resourcestatistical process controlnon-linear mathematical programming modelTaguchi’s loss functionSettore ING-IND/16 - Tecnologie E Sistemi Di Lavorazione
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Korpusavusteinen virheanalyysi tarkkuuden kehityksestä EVK:n taitotasoilla A2–B2

2020

Artikkelissa tarkastellaan kielitaidon taitotasoittaista kehittymistä potentiaalisten esiintymien analyysin (Potential Occasion Analysis, Thewissen, 2015) avulla. Kehittymistä analysoidaan tarkkuuden näkökulmasta, ja sitä mitataan kohdekielen muoto- ja käyttökonventioista poikkeavien muotojen määrällä. Tutkimus on korpuspohjaista virheanalyysia (Corpus-aided Error Analysis, Dagneaux, Dennes & Granger, 1998), ja se perustuu taitotasoilla havaittujen, yhdeksään virheluokkaan sijoittuvien virheiden määrien tilastolliseen testaukseen. Aineistona on Kansainvälinen oppijansuomen korpus(ICLFI). Analyysi osoittaa, että merkittävintä kehitys on tasojen B1 ja B2 välillä; tasojen A2 ja B1 välillä tark…

corpus-aided error analysispotential occasion analysisaccuracytarkkuusPoint (typography)Computer sciencepotentiaalisten esiintymien analyysidevelopment of language proficiencykielitaitoLinguisticsRegressionCulminationkielitaidon kehittyminenError analysisPhraseologyGeneral Earth and Planetary SciencesLanguage proficiencykehityskorpusavusteinen virheanalyysiGeneral Environmental ScienceStatistical hypothesis testingPuhe ja kieli
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Modeling long-range memory with stationary Markovian processes

2009

In this paper we give explicit examples of power-law correlated stationary Markovian processes y(t) where the stationary pdf shows tails which are gaussian or exponential. These processes are obtained by simply performing a coordinate transformation of a specific power-law correlated additive process x(t), already known in the literature, whose pdf shows power-law tails 1/x^a. We give analytical and numerical evidence that although the new processes (i) are Markovian and (ii) have gaussian or exponential tails their autocorrelation function still shows a power-law decay =1/T^b where b grows with a with a law which is compatible with b=a/2-c, where c is a numerical constant. When a<2(1+c) th…

correlation methodMarkov processeMathematical optimizationStationary distributionStatistical Mechanics (cond-mat.stat-mech)LogarithmStochastic processdiffusionAutocorrelationFOS: Physical sciencesProbability density functionContext (language use)White noiseExponential functionStatistical physicswhite noiseCondensed Matter - Statistical MechanicsMathematics
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Disease dispersion as a spatial interaction: The case of Flavescence Dorée

2020

International audience; Flavescence dorée is a serious and incurable vine disease transmitted by an insect vector. Focusing on its spatial diffusion and on its control with pesticides, this paper investigates the private strategies of wine producers and their socially optimal counterparts. The socially optimal regulation has to address two externalities regarding private treatment decisions: (a) the insufficient consideration of collective benefits from controlling the vector populations; (b) the failure to take into account environmental damage related to pesticide application. The probability of infection is estimated on French data from a spatial econometric specification. Three alternat…

cost‐benefit analysisMandatory treatmentJEL: Q - Agricultural and Natural Resource Economics • Environmental and Ecological Economics/Q.Q1 - Agriculture/Q.Q1.Q12 - Micro Analysis of Farm Firms Farm Households and Farm Input MarketsCompulsory treatmentEnvironmental Science (miscellaneous)environmental externalityAnalyse cout-benefice0502 economics and businessEconometricsStatistical dispersion050207 economicsExternalité environnementaleMathematicsGestion des nuisibles2. Zero hungercompulsory treatmentJEL: H - Public Economics/H.H2 - Taxation Subsidies and Revenue/H.H2.H21 - Efficiency • Optimal Taxation[QFIN]Quantitative Finance [q-fin]Spatial interactioncost-benefit analysis05 social sciencesTraitement obliatoire[SHS.ECO]Humanities and Social Sciences/Economics and Financespatial spilloverspest management13. Climate actionModeling and SimulationFlavescence doréeJEL: Q - Agricultural and Natural Resource Economics • Environmental and Ecological Economics/Q.Q5 - Environmental Economics/Q.Q5.Q51 - Valuation of Environmental Effects050202 agricultural economics & policy
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Computational Techniques for the Analysis of Small Signals in High-Statistics Neutrino Oscillation Experiments

2020

The current and upcoming generation of Very Large Volume Neutrino Telescopes – collecting unprecedented quantities of neutrino events – can be used to explore subtle effects in oscillation physics, such as (but not restricted to) the neutrino mass ordering. The sensitivity of an experiment to these effects can be estimated from Monte Carlo simulations. With the high number of events that will be collected, there is a trade-off between the computational expense of running such simulations and the inherent statistical uncertainty in the determined values. In such a scenario, it becomes impractical to produce and use adequately-sized sets of simulated events with traditional methods, such as M…

data analysis methodNuclear and High Energy PhysicsMonte Carlo methodFVLV nu TData analysis; Detector; KDE; MC; Monte Carlo; Neutrino; Neutrino mass ordering; Smoothing; Statistics; VLVνTData analysisKDEFOS: Physical sciences01 natural sciencesIceCubeHigh Energy Physics - ExperimentHigh Energy Physics - Experiment (hep-ex)statistical analysisnumerical methods0103 physical sciencesStatisticsNeutrinoddc:530Sensitivity (control systems)MC010306 general physicsNeutrino oscillationInstrumentation and Methods for Astrophysics (astro-ph.IM)InstrumentationMonte CarloPhysicsVLVνT010308 nuclear & particles physicsOscillationStatisticsoscillation [neutrino]ObservableDetectorMonte Carlo [numerical calculations]WeightingNeutrino mass orderingPhysics and AstronomyPhysics - Data Analysis Statistics and ProbabilityPhysique des particules élémentairesNeutrinoAstrophysics - Instrumentation and Methods for AstrophysicsMATTERData Analysis Statistics and Probability (physics.data-an)SmoothingSmoothing
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Socio-emotional Problems Experienced by Deaf and Hard of Hearing Students in Ethiopia

2015

This study compares the socio-emotional problems experienced by deaf and hard of hearing (DHH) students with those of hearing students in Ethiopia. The research involved a sample of 103 grade 4 students attending a special school for the deaf, a special class for the deaf and a regular school. Socio-emotional problems were measured using Goodman's self-report measure, the Strengths and Difficulties Questionnaire for children and adolescents. Participants were selected from seven towns in Ethiopia. The results show that, compared to the hearing sample, the DHH students experienced more severe socio-emotional problems across all dimensions, regardless of whether they were in special classes o…

deaf studentssocio-emotional problemsSocio emotionaleducationkuurousGeneral educationStrengths and Difficulties Questionnairehearing impairmentSocial issuesSpecial educationSpecial classEducationDevelopmental psychologySpeech and HearingdeafnessAfricaotorhinolaryngologic diseasesStatistical analysista516deaf educationhard of hearing studentsEthiopiaPsychologyDeaf educationDeafness and Education International
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Search for heavy neutrinos with the T2K near detector ND280

2019

This paper reports on the search for heavy neutrinos with masses in the range 140<MN<493  MeV/c2 using the off-axis near detector ND280 of the T2K experiment. These particles can be produced from kaon decays in the standard neutrino beam and then subsequently decay in ND280. The decay modes under consideration are N→ℓ±απ∓ and N→ℓ+αℓ−β(−)ν(α,β=e,μ). A search for such events has been made using the Time Projection Chambers of ND280, where the background has been reduced to less than two events in the current dataset in all channels. No excess has been observed in the signal region. A combined Bayesian statistical approach has been applied to extract upper limits on the mixing elements of heav…

decay modes [neutrino]GENERAL-THEORYmixing [neutrino]Physics::Instrumentation and Detectorsneutrino: heavy: search forKAMIOKANDE01 natural sciencesHigh Energy Physics - ExperimentPhysics Particles & FieldsHigh Energy Physics - Experiment (hep-ex)LIMITSsecondary beam [neutrino/mu]neutrino: decay modes[PHYS.HEXP]Physics [physics]/High Energy Physics - Experiment [hep-ex]Particle Physics Experimentsneutrino: massmedia_commonPhysicsVMSMJ-PARC LabPhysicsstatistical analysis: BayesianK: decayheavy neutrinos T2K Experiment Time Projection Chambersmass dependenceGeneral theoryT2K ExperimentTime Projection ChambersPhysical SciencesChristian ministrydata analysis methodFOS: Physical sciencesLibrary scienceheavy: search for [neutrino]Astronomy & AstrophysicsBayesian [statistical analysis]530near detector0103 physical sciencesDARK-MATTERmedia_common.cataloged_instanceddc:530Early careerEuropean unionS077A00010306 general physicsS077A01heavy neutrinosScience & Technology010308 nuclear & particles physicsbackgroundhep-exHigh Energy Physics::PhenomenologyFísicaneutrino/mu: secondary beamtime projection chamberdecay [K]mass [neutrino]Hypothetical particle physics models Particle phenomenaHigh Energy Physics::Experimentneutrino: mixingstatisticalexperimental resultsPhysical Review D
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Performance of $b$-Jet Identification in the ATLAS Experiment

2016

We thank CERN for the very successful operation of the LHC, as well as the support staff from our institutions without whom ATLAS could not be operated efficiently. We acknowledge the support of ANPCyT, Argentina; YerPhI, Armenia; ARC, Australia; BMWFW and FWF, Austria; ANAS, Azerbaijan; SSTC, Belarus; CNPq and FAPESP, Brazil; NSERC, NRC and CFI, Canada; CERN; CONICYT, Chile; CAS, MOST and NSFC, China; COLCIENCIAS, Colombia; MSMT CR, MPO CR and VSC CR, Czech Republic; DNRF, DNSRC and Lundbeck Foundation, Denmark; IN2P3-CNRS, CEA-DSM/IRFU, France; GNSF, Georgia; BMBF, HGF, and MPG, Germany; GSRT, Greece; RGC, Hong Kong SAR, China; ISF, I-CORE and Benoziyo Center, Israel; INFN, Italy; MEXT an…

detector-systems performancePerformance of High Energy Physics Detectorsecondary [vertex]Elementary particle01 natural sciencesPARTONlaw.inventionSubatomär fysikCHANNELcluster findingscattering [p p]impact parameterGeneralLiterature_REFERENCE(e.g.dictionariesencyclopediasglossaries)протон-протонные столкновенияQBLarge detector-systems performanceHigh energy physics detectorLarge Hadron ColliderLarge detector systems for particle and astroparticle physics; Large detector-systems performance; Pattern recognition cluster finding calibration and fitting methods; Performance of High Energy Physics Detectors; Instrumentation; Mathematical Physicstrack data analysisQUARK PAIR PRODUCTIONbottom [jet]CERN LHC CollPattern recognition cluster finding calibration and fitting method7000 GeV-cmscolliding beams [p p]performanceHADRONIC COLLISIONSCiências Naturais::Ciências FísicasLarge detectorFitting methodHigh energy physicATLAS LHC High Energy Physics510 MathematicsmuonDISTRIBUTIONSUncertainty analysis Astroparticle physicHigh Energy Physics010306 general physicsSystematic uncertainties AlgorithmsAstroparticle physicsCalibration and fitting methodsScience & Technology010308 nuclear & particles physicsLarge detector systems for particle and astroparticle physicsParticle acceleratorRangingPerformance of High Energy PhysicsCOLLIDERScorrelationExperimental High Energy PhysicsPerformance of High Energy Physics DetectorshadronATLAS детекторБольшой адронный коллайдерcharm [jet]Elementary particleHigh Energy Physics - ExperimentHigh Energy Physics - Experiment (hep-ex)lawSubatomic Physics[PHYS.HEXP]Physics [physics]/High Energy Physics - Experiment [hep-ex]Detectors and Experimental TechniquesInstrumentationUncertainty analysisMathematical PhysicsPhysicsPattern recognition cluster finding calibration and fitting methods4. EducationATLAS experimentSettore FIS/01 - Fisica SperimentaleDetectorsflavor [jet]calibration and fitting methodsATLASLarge Hadron ColliderLarge detector systems for particle and astroparticle physics; Large; detector-systems performance; Pattern recognition cluster finding; calibration and fitting methods; Performance of High Energy Physics; Detectors; PRODUCTION CROSS-SECTION; QUARK PAIR PRODUCTION; ROOT-S=7 TEV; PARTON; DISTRIBUTIONS; HADRONIC COLLISIONS; MATRIX-ELEMENTS; LHC; COLLIDERS; DETECTOR; CHANNEL8. Economic growthCalibrationparticle identification [bottom]LHCImpact parameterParticle Physics - ExperimentParticle physicsdata analysis method530 Physics:Ciências Físicas [Ciências Naturais]FOS: Physical sciences530MATRIX-ELEMENTSparticle identification [charm]on-line [trigger]Pattern recognition0103 physical sciencesComplementary methodddc:610DETECTORROOT-S=7 TEVCluster findingFísicaLarge detector systems for particle and astroparticle physics; Large detector-systems performance; Pattern recognition cluster finding calibration and fitting methods; Performance of High Energy Physics DetectorsPattern recognition systemcalibrationtracksPRODUCTION CROSS-SECTIONefficiencyHadronLarge detector systems for particle and astroparticle physicLargeHigh Energy Physics::ExperimentStatistical correlationstatisticalexperimental results
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