Results 21 to 30 of about 25,267,562 (240)
Agriculture, 2022 The overelevation of the water table in surface irrigation plots is one of the main factors affecting salinization in agricultural soils. Therefore, it is necessary to develop simulation models that consider the effect of a shallow water table in the ...
Sebastián Fuentes, Carlos Chávez
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Modeling Indirect Illumination for Inverse Rendering [PDF]
Computer Vision and Pattern Recognition, 2022 Recent advances in implicit neural representations and differentiable rendering make it possible to simultaneously recover the geometry and materials of an object from multi-view RGB images captured under unknown static illumination.
Yuanqing Zhang +5 more
semanticscholar +1 more source
Atmosphere, 2023 Among air toxics, formaldehyde (HCHO) is an important contributor to urban cancer risk. Emissions of HCHO in the United States are systematically under-reported and may enhance atmospheric ozone and particulate matter, intensifying their impacts on human
Eduardo P. Olaguer
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Models with inverse-square exchange [PDF]
Physical Review B, 1992 26 ...
Ha, Z. N. C., Haldane, F. D. M.
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Stochastic modeling error reduction using Bayesian approach coupled with an adaptive kriging based model [PDF]
, 2012 Magnetic material properties of an electromagnetic device can be recovered by solving an inverse problem where measurements are adequately interpreted by a mathematical forward model.
Dupré, Luc +1 more
core +4 more sources
Physics Constrained Learning for Data-driven Inverse Modeling from Sparse Observations [PDF]
Journal of Computational Physics, 2020 Deep neural networks (DNN) have been used to model nonlinear relations between physical quantities. Those DNNs are embedded in physical systems described by partial differential equations (PDE) and trained by minimizing a loss function that measures the ...
Kailai Xu, Eric F Darve
semanticscholar +1 more source
Nuclear Physics B, 2020 We propose a minimal predictive inverse seesaw model based on two right-handed neutrinos and two additional singlets, leading to the same low energy neutrino mass matrix as in the Littlest Seesaw (LS) (type I) model. In order to implement such a Littlest Inverse Seesaw (LIS) model, we have used an $S_{4}$ family symmetry, together with other various ...
Cárcamo Hernández, A.E., King, S.F.
openaire +6 more sources
Estimating Watershed Subsurface Permeability From Stream Discharge Data Using Deep Neural Networks
Frontiers in Earth Science, 2021 Subsurface permeability is a key parameter in watershed models that controls the contribution from the subsurface flow to stream flows. Since the permeability is difficult and expensive to measure directly at the spatial extent and resolution required by
Erol Cromwell +7 more
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An Inverse Modeling Constrained Multi-Objective Evolutionary Algorithm Based on Decomposition [PDF]
IEEE International Conference on Systems, Man and CyberneticsThis paper introduces the inverse modeling constrained multi-objective evolutionary algorithm based on decomposition (IM-C-MOEA/D) for addressing constrained real-world optimization problems. Our research builds upon the advancements made in evolutionary
L. R. Farias, Aluízio F. R. Araújo
semanticscholar +1 more source
Spatial coherence control and analysis via micromirror-based mixed-state ptychography
New Journal of Physics, 2021 Flexible and fast control of the phase and amplitude of coherent light, enabled by digital micromirror devices (DMDs) and spatial light modulators, has been a driving force for recent advances in optical tweezers, nonlinear microscopy, and wavefront ...
Ruslan Röhrich +3 more
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