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The elastic properties of a material with spherical voids of equal volume are analysed using a new model, with particular attention paid to the hexagonal close-packed and the face-centred cubic arrangement of voids. Void fractions well…

Materials Science · Physics 2016-11-11 Sascha Heitkam , Wiebke Drenckhan , Denis Weaire , Jochen Froehlich

We investigate the ellipticity of the point-spread function (PSF) produced by imaging an unresolved source with a telescope, subject to the effects of atmospheric turbulence. It is important to quantify these effects in order to understand…

Astrophysics · Physics 2011-02-11 W. H. de Vries , S. S. Olivier , S. J. Asztalos , L. J. Rosenberg , K. L. Baker

Random field and random cluster theory are used to describe certain mathematical results concerning the probability distribution of image pixel intensities characterized as generic $2D$ integer arrays. The size of the smallest bounded…

Image and Video Processing · Electrical Eng. & Systems 2023-04-27 Robert A. Murphy

Crystal Structure Prediction (CSP) is crucial in various scientific disciplines. While CSP can be addressed by employing currently-prevailing generative models (e.g. diffusion models), this task encounters unique challenges owing to the…

Materials Science · Physics 2024-03-08 Rui Jiao , Wenbing Huang , Peijia Lin , Jiaqi Han , Pin Chen , Yutong Lu , Yang Liu

Here an image restoration on the basis of pixel simultaneous detection probabilities (PSDP) is proposed. These probabilities can be precisely determined by means of correlations measurement [NIMA 586 (2008) 314-326]. The proposed image…

Medical Physics · Physics 2009-09-29 V. Grabski

Extending previous studies, we derive generic predictions for lower order cumulants and their correlators for individual tomographic bins as well as between two different bins. We derive the corresponding one- and two-point joint…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-03 Dipak Munshi , Peter Coles , Martin Kilbinger

It is of great concern to produce numerically efficient methods for moisture diffusion through porous media, capable of accurately calculate moisture distribution with a reduced computational effort. In this way, model reduction methods are…

Computational Physics · Physics 2020-02-20 Suelen Gasparin , Julien Berger , Denys Dutykh , Nathan Mendes

We apply machine learning in the form of a nearest neighbor instance-based algorithm (NN) to generate full photometric redshift probability density functions (PDFs) for objects in the Fifth Data Release of the Sloan Digital Sky Survey (SDSS…

Effects of heterogeneity of mineral distribution and reaction rate on the rock dissolution process are investigated using a pore-scale reactive transport model based on the lattice Boltzmann method. Coupled fluid flow, species transport,…

Fluid Dynamics · Physics 2015-11-16 Ting Min , Yimin Gao , Li Chen , Qinjun Kang , Wen-Quan Tao

Biot's theory provides a framework for computing seismic wavefields in fluid saturated porous media. Here we implement a velocity-stress staggered grid 2D finite difference algorithm to model the wave-propagation in poroelastic media. The…

Geophysics · Physics 2019-07-29 Janaki Vamaraju , Mrinal K. Sen

Engineering simulations using boundary-value partial differential equations often implicitly assume that the uncertainty in the location of the boundary has a negligible impact on the output of the simulation. In this work, we develop a…

Tissues and Organs · Quantitative Biology 2024-06-11 S. Gerry Gralton , Farah Alkhatib , Ben Zwick , George Bourantas , Adam Wittek , Karol Miller

Impacts of liquid droplets on wind turbine blade surfaces, for example sea sprays, can result in material damage through erosion. In this study, we derive an explicit, closed-form analytical approximation for droplet impact and subsequent…

In order to better understand the interaction between pore-fluid overpressure and failure patterns in rocks we consider a porous elasto-plastic medium in which a laterally localized overpressure line source is imposed at depth below the…

Geophysics · Physics 2008-01-04 Alexander Rozhko , Yuri Podladchikov , François Renard

We propose an algorithm for segmenting natural images based on texture and color information, which leverages the co-sparse analysis model for image segmentation within a convex multilabel optimization framework. As a key ingredient of this…

Computer Vision and Pattern Recognition · Computer Science 2013-12-18 Claudia Nieuwenhuis , Daniel Cremers , Simon Hawe , Martin Kleinsteuber

Medical image segmentation, particularly in the context of ultrasound data, is a crucial aspect of computer vision and medical imaging. This paper delves into the complexities of uncertainty in the segmentation process, focusing on fetal…

Image and Video Processing · Electrical Eng. & Systems 2024-01-19 Shuge Lei

As posts on social media increase rapidly, analyzing the sentiments embedded in image-text pairs has become a popular research topic in recent years. Although existing works achieve impressive accomplishments in simultaneously harnessing…

Computation and Language · Computer Science 2025-12-04 Daiqing Wu , Dongbao Yang , Yu Zhou , Can Ma

This paper studies the utility of techniques within uncertainty quantification, namely spectral projection and polynomial chaos expansion, in reducing sampling needs for characterizing acoustic metamaterial dispersion band responses given…

The current development of digital image correlation, whose displacement uncertainty is well below the pixel value, enables one to better characterise the behaviour of materials and the response of structures to external loads. A general…

Classical Physics · Physics 2016-08-16 François Hild , Stéphane Roux

Despite the remarkable progress in generative modelling, current diffusion models lack a quantitative approach to assess image quality. To address this limitation, we propose to estimate the pixel-wise aleatoric uncertainty during the…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Michele De Vita , Vasileios Belagiannis

This paper proposes a partition-based functional ridge regression framework to address multicollinearity, overfitting, and interpretability in high-dimensional functional linear models. The coefficient function vector \(…

Methodology · Statistics 2026-03-13 Shaista Ashraf , Ismail Shah , Farrukh Javed
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