Search results for "Sampling"

showing 10 items of 788 documents

Adaptive Finite Temperature String Method in Collective Variables.

2017

Here we present a modified version of the on-the-fly string method for the localization of the minimum free energy path in a space of arbitrary collective variables. In the proposed approach the shape of the biasing potential is controlled by only two force constants, defining the width of the potential along the string and orthogonal to it. The force constants and the distribution of the string nodes are optimized during the simulation, improving the convergence. The optimized parameters can be used for umbrella sampling with a path CV along the converged string as the reaction coordinate. We test the new method with three fundamentally different processes: chloride attack to chloromethane…

010304 chemical physicsChemistryString (computer science)Mathematical analysis010402 general chemistry01 natural sciences0104 chemical sciencesReaction coordinateDistribution (mathematics)0103 physical sciencesPath (graph theory)Convergence (routing)Range (statistics)Physical and Theoretical ChemistryUmbrella samplingPotential of mean forceThe journal of physical chemistry. A
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Analytical Process

2016

010504 meteorology & atmospheric sciencesChemistrybusiness.industryScientific methodEnvironmental chemistry010401 analytical chemistrySampling (statistics)Process engineeringbusiness01 natural sciences0104 chemical sciences0105 earth and related environmental sciences
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Automatic emulator and optimized look-up table generation for radiative transfer models

2017

This paper introduces an automatic methodology to construct emulators for costly radiative transfer models (RTMs). The proposed method is sequential and adaptive, and it is based on the notion of the acquisition function by which instead of optimizing the unknown RTM underlying function we propose to achieve accurate approximations. The Automatic Gaussian Process Emulator (AGAPE) methodology combines the interpolation capabilities of Gaussian processes (GPs) with the accurate design of an acquisition function that favors sampling in low density regions and flatness of the interpolation function. We illustrate the good capabilities of the method in toy examples and for the construction of an…

010504 meteorology & atmospheric sciencesComputer scienceFlatness (systems theory)0211 other engineering and technologiesAtmospheric correctionSampling (statistics)02 engineering and technologyFunction (mathematics)Atmospheric model01 natural sciencessymbols.namesakeKernel (statistics)Lookup tableRadiative transfersymbolsGaussian process emulatorGaussian processAlgorithm021101 geological & geomatics engineering0105 earth and related environmental sciencesInterpolation2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
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Multioutput Automatic Emulator for Radiative Transfer Models

2018

This paper introduces a methodology to construct emulators of costly radiative transfer models (RTMs). The proposed methodology is sequential and adaptive, and it is based on the notion of acquisition functions in Bayesian optimization. Here, instead of optimizing the unknown underlying RTM function, one aims to achieve accurate approximations. The Automatic Multi-Output Gaussian Process Emulator (AMO-GAPE) methodology combines the interpolation capabilities of Gaussian processes (GPs) with the accurate design of an acquisition function that favors sampling in low density regions and flatness of the interpolation function. We illustrate the promising capabilities of the method for the const…

010504 meteorology & atmospheric sciencesComputer scienceFlatness (systems theory)Bayesian optimizationSampling (statistics)02 engineering and technologyFunction (mathematics)Atmospheric model01 natural sciencessymbols.namesakeSampling (signal processing)0202 electrical engineering electronic engineering information engineeringsymbolsRadiative transfer020201 artificial intelligence & image processingGaussian process emulatorGaussian processAlgorithm0105 earth and related environmental sciencesInterpolationIGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium
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Efficient remote sensing image classification with Gaussian processes and Fourier features

2017

This paper presents an efficient methodology for approximating kernel functions in Gaussian process classification (GPC). Two models are introduced. We first include the standard random Fourier features (RFF) approximation into GPC, which largely improves the computational efficiency and permits large scale remote sensing data classification. In addition, we develop a novel approach which avoids randomly sampling a number of Fourier frequencies, and alternatively learns the optimal ones using a variational Bayes approach. The performance of the proposed methods is illustrated in complex problems of cloud detection from multispectral imagery.

010504 meteorology & atmospheric sciencesContextual image classificationComputer scienceMultispectral imageData classification0211 other engineering and technologiesSampling (statistics)02 engineering and technology01 natural sciencessymbols.namesakeBayes' theoremFourier transformKernel (statistics)symbolsGaussian process021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensing
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GIGJ: a crustal gravity model of the Guangdong Province for predicting the geoneutrino signal at the JUNO experiment

2019

Gravimetric methods are expected to play a decisive role in geophysical modeling of the regional crustal structure applied to geoneutrino studies. GIGJ (GOCE Inversion for Geoneutrinos at JUNO) is a 3D numerical model constituted by ~46 x 10$^{3}$ voxels of 50 x 50 x 0.1 km, built by inverting gravimetric data over the 6{\deg} x 4{\deg} area centered at the Jiangmen Underground Neutrino Observatory (JUNO) experiment, currently under construction in the Guangdong Province (China). The a-priori modeling is based on the adoption of deep seismic sounding profiles, receiver functions, teleseismic P-wave velocity models and Moho depth maps, according to their own accuracy and spatial resolution. …

010504 meteorology & atmospheric sciencesGeoneutrinogeophysical uncertaintieInverse transform samplingFOS: Physical sciences01 natural sciencesBayesian methodUpper middle and lower crustStandard deviationNOSouth China BlockmiddlePhysics - GeophysicsMonte Carlo stochastic optimizationGOCE data gravimetric inversionGeophysical uncertaintiesGeochemistry and PetrologyEarth and Planetary Sciences (miscellaneous)Bayesian method; geophysical uncertainties; GOCE data gravimetric inversion; Monte Carlo stochastic optimization; South China Block; upper middle and lower crustImage resolution0105 earth and related environmental sciencesSubdivisionJiangmen Underground Neutrino Observatoryupper and middle and lower crustbusiness.industrySettore FIS/01 - Fisica SperimentaleCrustupperGeodesy[PHYS.PHYS.PHYS-GEN-PH]Physics [physics]/Physics [physics]/General Physics [physics.gen-ph]Geophysics (physics.geo-ph)and lower crustDepth soundingGeophysics13. Climate actionSpace and Planetary SciencebusinessGeologyBayesian method geophysical uncertainties GOCE data gravimetric inversion Monte Carlo stochastic optimization South China Blockupper and middle and lower crust
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Microbiology and atmospheric processes: biological, physical and chemical characterization of aerosol particles

2008

Abstract. The interest in bioaerosols has traditionally been linked to health hazards for humans, animals and plants. However, several components of bioaerosols exhibit physical properties of great significance for cloud processes, such as ice nucleation and cloud condensation. To gain a better understanding of their influence on climate, it is therefore important to determine the composition, concentration, seasonal fluctuation, regional diversity and evolution of bioaerosols. In this paper, we will review briefly the existing techniques for detection, quantification, physical and chemical analysis of biological particles, attempting to bridge physical, chemical and biological methods for …

010504 meteorology & atmospheric sciencesIndoor bioaerosollcsh:LifeBiological particles[SDU.STU]Sciences of the Universe [physics]/Earth SciencesNanotechnology[SDU.ASTR] Sciences of the Universe [physics]/Astrophysics [astro-ph]01 natural sciences[PHYS.ASTR.CO]Physics [physics]/Astrophysics [astro-ph]/Cosmology and Extra-Galactic Astrophysics [astro-ph.CO]03 medical and health scienceslcsh:QH540-549.5[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces environmentEcology Evolution Behavior and Systematics0105 earth and related environmental sciencesEarth-Surface Processes[SDU.OCEAN]Sciences of the Universe [physics]/Ocean Atmosphere0303 health sciences[SDU.ASTR]Sciences of the Universe [physics]/Astrophysics [astro-ph][SDU.OCEAN] Sciences of the Universe [physics]/Ocean Atmosphere030306 microbiologyChemistrylcsh:QE1-996.5[SDU.ENVI] Sciences of the Universe [physics]/Continental interfaces environmentAerosolCharacterization (materials science)lcsh:Geologylcsh:QH501-531[PHYS.ASTR.CO] Physics [physics]/Astrophysics [astro-ph]/Cosmology and Extra-Galactic Astrophysics [astro-ph.CO]13. Climate action[SDU.STU] Sciences of the Universe [physics]/Earth SciencesIce nucleuslcsh:EcologyBiochemical engineeringAerosol sampling
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Enhancing the retrieval of stream surface temperature from Landsat data

2019

International audience; Thermal images of water bodies often show a radiance gradient perpendicular to the banks. This effect is frequently due to mixed land and water thermal pixels. In the case of the Landsat images, radiance mixing can also affect pure water pixels due the cubic convolution resampling of the native thermal measurements. Some authors recommended a general-purpose margin of two thermal pixels to the banks or a minimum river width of three pixels, to avoid near bank effects in water temperature retrievals. Given the relatively course spatial resolution of satellite thermal sensors, the three pixel margin severely restricts their application to temperature mapping in many ri…

010504 meteorology & atmospheric sciencesPixel0208 environmental biotechnologySoil ScienceGeologyImage processing02 engineering and technology01 natural sciencesSubpixel rendering6. Clean water020801 environmental engineering[SDE]Environmental SciencesThermalRadianceEnvironmental scienceSatelliteSatellite imageryComputers in Earth SciencesRiver surface temperature Landsat 8 thermal band Thermal spatial resolution Cubic convolution resampling Thermal impact Mequinenza reservoir Ebro river Thermal stratificationImage resolution0105 earth and related environmental sciencesRemote sensingRemote Sensing of Environment
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A Plot-scale uncertainty analysis of saturated hydraulic conductivity of a clay soil

2021

Abstract Simulating soil hydrological processes at the plot or field scale requires using spatially representative values of the saturated soil hydraulic conductivity, Ks. Sampling campaigns should yield a reliable mean of Ks with a sustainable workload since measuring Ks at many points is challenging. Uncertainty analysis can be used to determine the lowest number of measurements that yield a mean Ks value with a specified accuracy level. Potential and limitations of this analysis were tested in this investigation for different extents of the sampled area and sampling densities. A clay soil was sampled intensively on two plots (plot area = 44 m2), two dates and using both small (0.15 m in …

010504 meteorology & atmospheric sciencesScale (ratio)0207 environmental engineeringbootstrap methodSampling (statistics)Soil science02 engineering and technology01 natural sciencesConfidence intervalHydraulic conductivitysaturated soil hydraulic conductivityEnvironmental scienceSettore AGR/08 - Idraulica Agraria E Sistemazioni Idraulico-Forestalifine-textured soilsFine-textured soilsimplified falling head technique020701 environmental engineeringClay soilUncertainty analysissaturated soil hydraulic conductivity fine-textured soils simplified falling head technique bootstrap method0105 earth and related environmental sciencesWater Science and Technology
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Methanotrophy in geothermal soils, an overlooked process: The example of Nisyros island (Greece)

2020

Abstract A multidisciplinary field campaign was carried out at Nisyros Island (Greece). Hydrothermal gases were sampled and analysed, and CH4 and CO2 fluxes from the soils were measured with the accumulation chamber method. The sampling area (Lakki plain) covers an area of about 0.08 km2, and includes the main fumarolic areas of Kaminakia, Stefanos, Ramos, Lofos and Phlegeton. Flux values measured at 130 sites range from −3.4 to 1420 mg m−2 d−1 for CH4 and from 0.1 to 383 g m−2 d−1 for CO2. The fumarolic areas show very different CH4 degassing patterns, Kaminakia showing the highest CH4 output values (about 0.8 t a−1 from an area of about 30,000 m2) and Phlegeton the lowest (about 0.01 t a−…

010504 meteorology & atmospheric sciencesSoil testMethanotrophy Soil degassing Hydrothermal systems Methane output Greenhouse gasesSampling (statistics)GeologySoil scienceMethanotrophy Soil degassing Hydrothermal systems Methane output Greenhouse gases010502 geochemistry & geophysics01 natural sciencesSettore GEO/08 - Geochimica E VulcanologiaFlux (metallurgy)Geochemistry and PetrologyChamber methodSoil waterGeothermal gradientGeologyField campaign0105 earth and related environmental sciencesChemical Geology
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