Search results for "STING"

showing 10 items of 3756 documents

The Challenge of Feedback Personalization to Learning Styles in a Web-Based Learning System

2006

Feedback is information that is provided to a user to inform him/her about the result of his/her action and to motivate him/her to further interact with the system. In web-based learning systems (WBLS), feedback is particularly important in test and evaluation tasks. The main objective of the paper is twofold: (1) to encourage WBLS designers and specialists to pay more attention to the problem of feedback adaptation, and (2) to analyze suggestions for feedback personalization to learning styles in a WBLS.

Multimediabusiness.industryComputer scienceSystem testingcomputer.software_genreTest (assessment)PersonalizationLearning stylesMoodAction (philosophy)Adaptive systemThe InternetbusinessAdaptation (computer science)computerSixth IEEE International Conference on Advanced Learning Technologies (ICALT'06)
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Multiscale microstructural characterization of particulate-reinforced composite with non-destructive X-ray micro- and nanotomography

2018

Abstract Methods based on X-ray tomography are developed to study the relevant statistical quantities describing the microstructural inhomogeneity of particulate reinforced composites. The developed methods are applied in estimating microstructural inhomogeneity parameters of composites containing metallic glass particles in metal matrix, extruded in varying pressure loads. This study indicates that the critical characteristics with regard to the effect of particle clustering are cluster size and shape, local volume fraction of particles in the cluster and the distance between clusters. The results demonstrate that the spatial distribution of reinforcement is very uneven and the amount of p…

MultiscaleMaterials scienceComposite numberNon-destructive testing02 engineering and technology010402 general chemistry01 natural sciencesNondestructive testingCluster (physics)Composite materialta216Civil and Structural EngineeringAmorphous metalta114business.industryMicrostructural analysis021001 nanoscience & nanotechnology0104 chemical sciencesCharacterization (materials science)Particle-reinforcementVolume fractionrikkomaton aineenkoetusCeramics and CompositesParticleExtrusion0210 nano-technologybusinessComposite Structures
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Association between climate and new daily diagnoses of COVID-19

2020

AbstractBackgroundAlthough evidence is accumulating that climate conditions may positively or negatively influence the scale of coronavirus disease 2019 (COVID-19) outbreaks, uncertainty remains concerning the real impact of climate factors on viral transmission. Methods. The number of new daily cases of COVID-19 diagnosed in Verona (Italy) was retrieved from the official website of Veneto Region, while information on daily weather parameters in the same area was downloaded from IlMeteo website, a renowned Italian technological company specialized in weather forecasts. The search period ranged between March 1 to November 11, 2020. The number of new daily COVID-19 cases and meteorological da…

Multivariate analysisCoronavirus disease 2019 (COVID-19)Leadership and ManagementStrategy and Management2020. The number of new daily COVID-19 cases and meteorological data in Verona were correlated using both univariate and multivariate analysis. Results: The number of daily COVID-19 diagnoses in Verona was positively associated with the number of days in lockdown and humidity1% decrease in humidityWind speedmin and max temperatureand influence the likelihood or course of local COVID-19 outbreaks. Preventive measuresHealth Information Managementa renowned Italian technological company specialized in weather forecasts. The search period ranged between March 1 and November 11mean air temperature1.2% and 5.4% reduction in new COVID-19 daily diagnoses. A significant difference was observed in values of all-weather parameters recorded in Verona between days with &ltHealth Policy1 km/h increase in wind speed and day with rainfall were independently associated with 1.0%Significant differencehumidityUnivariateOutbreakHumidityand inversely correlated with meanmean wind speed and number of days with rainfall. Days of lockdownwhile information on daily weather parameters in the same area was downloaded from IlMeteo websitetesting policies and hospital preparedness should be reinforced during periods of higher meteorological risk and in local environments with adverse climate conditions.Background: Although evidence is accumulating that climate conditions may positively or negatively influence the scale of coronavirus disease 2019 (COVID-19) outbreaks0.3%uncertainty remains concerning the real impact of climate factors on viral transmission. Methods: The number of new daily cases of COVID-19 diagnosed in Verona (Italy) was retrieved from the official website of Veneto RegionGeography100 or ≥100 new daily COVID-19 diagnoses. Conclusions: Climate conditions may play an essential role in conditions of viral transmissionAir temperaturemean wind speed and number of days with rainfall remained significantly associated in multivariate analysis. The four weather parameters contributed to explaining 61% of variance in new daily COVID-19 diagnoses. Each 1% increase in air temperatureBackground: Although evidence is accumulating that climate conditions may positively or negatively influence the scale of coronavirus disease 2019 (COVID-19) outbreaks uncertainty remains concerning the real impact of climate factors on viral transmission. Methods: The number of new daily cases of COVID-19 diagnosed in Verona (Italy) was retrieved from the official website of Veneto Region while information on daily weather parameters in the same area was downloaded from IlMeteo website a renowned Italian technological company specialized in weather forecasts. The search period ranged between March 1 and November 11 2020. The number of new daily COVID-19 cases and meteorological data in Verona were correlated using both univariate and multivariate analysis. Results: The number of daily COVID-19 diagnoses in Verona was positively associated with the number of days in lockdown and humidity and inversely correlated with mean min and max temperature mean wind speed and number of days with rainfall. Days of lockdown mean air temperature humidity mean wind speed and number of days with rainfall remained significantly associated in multivariate analysis. The four weather parameters contributed to explaining 61% of variance in new daily COVID-19 diagnoses. Each 1% increase in air temperature 1% decrease in humidity 1 km/h increase in wind speed and day with rainfall were independently associated with 1.0% 0.3% 1.2% and 5.4% reduction in new COVID-19 daily diagnoses. A significant difference was observed in values of all-weather parameters recorded in Verona between days with <100 or ≥100 new daily COVID-19 diagnoses. Conclusions: Climate conditions may play an essential role in conditions of viral transmission and influence the likelihood or course of local COVID-19 outbreaks. Preventive measures testing policies and hospital preparedness should be reinforced during periods of higher meteorological risk and in local environments with adverse climate conditions.DemographyJournal of Hospital Management and Health Policy
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Visitor arrivals forecasts amid COVID-19: A perspective from the Africa team

2021

Abstract COVID-19 disrupted international tourism worldwide, subsequently presenting forecasters with a challenging conundrum. In this competition, we predict international arrivals for 20 destinations in two phases: (i) Ex post forecasts pre-COVID; (ii) Ex ante forecasts during and after the pandemic up to end 2021. Our results show that univariate combined with cross-sectional hierarchical forecasting techniques (THieF-ETS) outperform multivariate models pre-COVID. Scenarios were developed based on judgemental adjustment of the THieF-ETS baseline forecasts. Analysts provided a regional view on the most likely path to normal, based on country-specific regulations, macroeconomic conditions,…

Multivariate statisticsEx-ante[QFIN]Quantitative Finance [q-fin]Visitor pattern05 social sciencesUnivariateCOVID-19Hierarchical forecastsVisitor arrivalsDevelopmentDestinationsSettore SECS-P/06 - Economia ApplicataCompetition (economics)Settore SECS-S/06 -Metodi Mat. dell'Economia e d. Scienze Attuariali e Finanz.Tourism Leisure and Hospitality Management0502 economics and businessEconomicsEconometrics050211 marketingScenario forecastingBaseline (configuration management)050212 sport leisure & tourismTourismComputingMilieux_MISCELLANEOUSForecasting
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Stochastic Nonlinear Time Series Forecasting Using Time-Delay Reservoir Computers: Performance and Universality

2014

International audience; Reservoir computing is a recently introduced machine learning paradigm that has already shown excellent performances in the processing of empirical data. We study a particular kind of reservoir computers called time-delay reservoirs that are constructed out of the sampling of the solution of a time-delay diFFerential equation and show their good performance in the forecasting of the conditional covariances associated to multivariate discrete-time nonlinear stochastic processes of VEC-GARCH type as well as in the prediction of factual daily market realized volatilities computed with intraday quotes, using as training input daily log-return series of moderate size. We …

Multivariate statisticsMathematical optimizationTime FactorsRealized varianceDifferential equationComputer scienceCognitive NeuroscienceMathematicsofComputing_NUMERICALANALYSIS02 engineering and technologyComputer Communication NetworksArtificial Intelligence0502 economics and business0202 electrical engineering electronic engineering information engineeringHumansTime seriesSimulation050205 econometrics Stochastic Processes[PHYS.PHYS.PHYS-OPTICS]Physics [physics]/Physics [physics]/Optics [physics.optics]Series (mathematics)Artificial neural networkComputersStochastic process05 social sciencesReservoir computingSampling (statistics)Universality (dynamical systems)Nonlinear systemNonlinear DynamicsData Interpretation Statistical020201 artificial intelligence & image processingNeural Networks ComputerForecastingSSRN Electronic Journal
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On Mardia’s Tests of Multinormality

2004

Classical multivariate analysis is based on the assumption that the data come from a multivariate normal distribution. The tests of multinormality have therefore received very much attention. Several tests for assessing multinormality, among them Mardia’s popular multivariate skewness and kurtosis statistics, are based on standardized third and fourth moments. In Mardia’s construction of the affine invariant test statistics, the data vectors are first standardized using the sample mean vector and the sample covariance matrix. In this paper we investigate whether, in the test construction, it is advantageous to replace the regular sample mean vector and sample covariance matrix by their affi…

Multivariate statisticsMultivariate analysisScatter matrixStatisticsKurtosisMultivariate normal distributionAffine transformationBivariate analysisMathematicsStatistical hypothesis testing
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Locally optimal invariant detector for testing equality of two power spectral densities

2018

This work addresses the problem of determining whether two multivariate random time series have the same power spectral density (PSD), which has applications, for instance, in physical-layer security and cognitive radio. Remarkably, existing detectors for this problem do not usually provide any kind of optimality. Thus, we study here the existence under the Gaussian assumption of optimal invariant detectors for this problem, proving that the uniformly most powerful invariant test (UMPIT) does not exist. Thus, focusing on close hypotheses, we show that the locally most powerful invariant test (LMPIT) only exists for univariate time series. In the multivariate case, we prove that the LMPIT do…

Multivariate statisticsSeries (mathematics)Computer scienceGaussianDetectorUnivariateSpectral density020206 networking & telecommunications02 engineering and technologyUniformly most powerful invariant test (UMPIT)01 natural sciencesMatrix decomposition010104 statistics & probabilitysymbols.namesakePower spectral density (PSD)0202 electrical engineering electronic engineering information engineeringsymbols0101 mathematicsInvariant (mathematics)Time seriesHypothesis testGeneralized likelihood ratio test (GLRT)AlgorithmLocally most powerful invariant test (LMPIT)Statistical hypothesis testing
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Statistical Techniques for Validation of Simulation and Analytic Stochastic Models

2014

In this paper, we consider the problem of statistical validation of multivariate stationary response simulation and analytic stochastic models of observed systems (say, transportation or service systems), which have p response variables. The problem is reduced to testing the equality of the mean vectors for two multivariate normal populations. Without assuming equality of the covariance matrices, it is referred to as the Behrens–Fisher problem. The main purpose of this paper is to bring to the attention of applied researchers the satisfactory tests that can be used for testing the equality of two normal mean vectors when the population covariance matrices are unknown and arbitrary. To illus…

Multivariate statisticsService (systems architecture)education.field_of_studyStochastic modellingStatistical validationPopulationApplied mathematicsMultivariate normal distributionCovarianceeducationStatistical hypothesis testingMathematics
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Comparison of differences in resolution and sources of controlling factors for gully erosion susceptibility mapping

2018

Abstract Gully erosion has been identified as an important soil degradation process and sediment source, especially in arid and semiarid areas. Thus, it is useful to identify the spatial occurrence of this form of water erosion in the landscape and the most vulnerable areas. In this study, we explored the effects of different pixel sizes on some controlling factors extracted from a digital elevation model and remote sensing data when producing a gully erosion susceptibility map (GESM) of Ekbatan Dam Basin, Hamadan, Iran. An inventory map of the gully landforms was prepared based on global positioning system routes of the gullies, extensive field surveys, and visual interpretations of satell…

Multivariate statisticsTopographic Wetness IndexRemote sensing data010504 meteorology & atmospheric sciencesPixelTopographic attributeSettore GEO/04 - Geografia Fisica E Geomorfologia0208 environmental biotechnologySoil Science02 engineering and technology01 natural sciencesNormalized Difference Vegetation Index020801 environmental engineeringData setGully erosionMachine learning modelSoil retrogression and degradationRobustneEnvironmental scienceDigital elevation model0105 earth and related environmental sciencesRemote sensingStatistical hypothesis testingGeoderma
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Rank scores tests of multivariate independence

2004

New rank scores test statistics are proposed for testing whether two random vectors are independent. The tests are asymptotically distribution-free for elliptically symmetric marginal distributions. Recently, Gieser and Randles (1997), Taskinen, Kankainen and Oja (2003) and Taskinen, Oja and Randles (2005) introduced and discussed different multivariate extensions of the quadrant test, Kendall's tau and Spearman's rho statistics. In this paper, standardized multivariate spatial signs and the (univariate) ranks of the Mahalanobis-type distances of the observations from the origin are combined to construct ranks cores tests of independence. The limiting distributions of the test statistics ar…

Multivariate statisticsWilcoxon signed-rank testStatisticsUnivariateVan der Waerden's theoremrank scores testsMarginal distributionNull hypothesisParametric statisticsMathematicsStatistical hypothesis testing
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