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Nonuniform Fourier data are routinely collected in applications such as magnetic resonance imaging, synthetic aperture radar, and synthetic imaging in radio astronomy. To acquire a fast reconstruction that does not require an online inverse…

Numerical Analysis · Mathematics 2016-10-05 Anne Gelb , Guohui Song

Seismogenic plate boundaries are presumed to behave in a similar manner to a densely packed granular medium, where fault and blocks systems rapidly rearrange the distribution of forces within themselves, as particles do in slowly sheared…

In large-scale regression problems, random Fourier features (RFFs) have significantly enhanced the computational scalability and flexibility of Gaussian processes (GPs) by defining kernels through their spectral density, from which a finite…

Machine Learning · Computer Science 2024-06-05 Houston Warren , Rafael Oliveira , Fabio Ramos

In this study, radar signals were analyzed to classify grain surface types by using machine learning methods. Radar backscatter signals were recorded using a vector network analyzer between 18-40 GHz. A total of 5681 measurements of A scan…

Signal Processing · Electrical Eng. & Systems 2020-09-28 Hüseyin Duysak , Umut Özkaya , Enes Yiğit

Granular operator spaces and variants had been introduced and used in theoretical investigations on the foundations of general rough sets by the present author over the last few years. In this research, higher order versions of these are…

Logic in Computer Science · Computer Science 2019-10-15 A. Mani

Jamming is a common feature of out of equilibrium systems showing slow relaxation dynamics. Here we review our efforts in understanding jamming in granular materials using experiments and computer simulations. We first obtain an estimation…

Soft Condensed Matter · Physics 2009-11-11 Chaoming Song , Ping Wang , Fabricio Potiguar , Hernan A. Makse

Inverse problems in granular flows, such as landslides and debris flows, involve estimating material parameters or boundary conditions based on target runout profile. Traditional high-fidelity simulators for these inverse problems are…

Geophysics · Physics 2024-04-29 Yongjin Choi , Krishna Kumar

Reverse Monte Carlo (RMC) is an algorithm that incorporates stochastic modification of the action as part of the process that updates the fields in a Monte Carlo simulation. Such update moves have the potential of lowering or eliminating…

High Energy Physics - Lattice · Physics 2015-06-22 Arjun Singh Gambhir , Kostas Orginos

New concepts of rough natural number systems, recently introduced by the present author, are used to improve most rough set-theoretical measures in general Rough Set theory (\textsf{RST}) and measures of mutual consistency of multiple…

Logic · Mathematics 2011-02-15 A. Mani

Over the last two decades, scanning tunnelling microscopy (STM) has become one of the most important ways to investigate the structure of crystal surfaces. STM has helped achieve remarkable successes in surface science such as finding the…

Materials Science · Physics 2009-11-10 Cristian V. Ciobanu , Cristian Predescu

The aim of this paper is to develop and analyze numerical schemes for approximately solving the backward problem of subdiffusion equation involving a fractional derivative in time with order $\alpha\in(0,1)$. After using quasi-boundary…

Numerical Analysis · Mathematics 2020-10-28 Zhengqi Zhang , Zhi Zhou

Rough set theory is a new method that deals with vagueness and uncertainty emphasized in decision making. Data mining is a discipline that has an important contribution to data analysis, discovery of new meaningful knowledge, and autonomous…

Databases · Computer Science 2013-11-19 Thabet Slimani

Reticular materials, including metal-organic frameworks and covalent organic frameworks, combine relative ease of synthesis and an impressive range of applications in various fields, from gas storage to biomedicine. Diverse properties arise…

Materials Science · Physics 2024-03-11 Vadim Korolev , Artem Mitrofanov

In the domain of machine learning, least square twin support vector machine (LSTSVM) stands out as one of the state-of-the-art models. However, LSTSVM suffers from sensitivity to noise and outliers, overlooking the SRM principle and…

Machine Learning · Computer Science 2025-02-11 M. Tanveer , R. K. Sharma , A. Quadir , M. Sajid

Grazing incidence X-ray fluorescence is a non-destructive technique for analyzing the geometry and compositional parameters of nanostructures appearing e.g. in computer chips. In this paper, we propose to reconstruct the posterior parameter…

Machine Learning · Computer Science 2021-02-08 Anna Andrle , Nando Farchmin , Paul Hagemann , Sebastian Heidenreich , Victor Soltwisch , Gabriele Steidl

The large time and length scales and, not least, the vast number of particles involved in industrial-scale simulations inflate the computational costs of the Discrete Element Method (DEM) excessively. Coarse grain models can help to lower…

Computational Physics · Physics 2017-05-11 Daniel Queteschiner , Thomas Lichtenegger , Simon Schneiderbauer , Stefan Pirker

In this paper, a non-uniform rational B-spline based iso-geometric finite element method is used to study the static and dynamic characteristics of functionally graded material (FGM) plates. The material properties are assumed to be graded…

The amount of data available in the world is growing faster than our ability to deal with it. However, if we take advantage of the internal \emph{structure}, data may become much smaller for machine learning purposes. In this paper we focus…

Machine Learning · Computer Science 2016-11-07 Zeyuan Allen-Zhu , Yang Yuan , Karthik Sridharan

The general and practical inversion of diffraction data-producing a computer model correctly representing the material explored - is an important unsolved problem for disordered materials. Such modeling should proceed by using our full…

Materials Science · Physics 2016-07-05 Anup Pandey , Parthapratim Biswas , David A. Drabold

In this study we characterize the rheology of fluidized granular matter subject to secondary forcing. Our approach consists of first fluidizing granular matter in a drum half filled with grains via simple rotation, and then superimposing…

Soft Condensed Matter · Physics 2011-07-05 Kenneth W. Desmond , Umberto Villa , Mike Newey , Wolfgang Losert