Results 11 to 20 of about 1,301,987 (287)

Multi-scale bullseye antennas

open access: yesPhilosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2022
We design, simulate and experimentally characterize a multi-scale bullseye antenna for the broadband manipulation of microwaves. The device achieves far-field beam-forming via tailored diffraction at the interface between two concentric bullseye geometries, with near-field energy concentration resulting from the overlap of the diffracted beams.
G. J. Chaplain   +2 more
openaire   +3 more sources

Multi-scale Classification for Electrosensing [PDF]

open access: yesSIAM Journal on Imaging Sciences, 2021
This paper introduces premier and innovative (real-time) multi-scale method for target classification in electro-sensing. The intent is that of mimicking the behavior of the weakly electric fish, which is able to retrieve much more information about the target by approaching it.
Baldassari, Lorenzo, Scapin, Andrea
openaire   +3 more sources

Multi-scale polarisation phenomena [PDF]

open access: yesLight: Science & Applications, 2016
AbstractMulti-scale methods that separate different time or spatial scales are among the most powerful techniques in physics, especially in applications that study nonlinear systems with noise. When the time scales (noise and perturbation) are of the same order, the scales separation becomes impossible. Thus, the multi-scale approach has to be modified
Kalashnikov, Vladimir   +4 more
openaire   +2 more sources

Multi-scale link prediction [PDF]

open access: yesProceedings of the 21st ACM international conference on Information and knowledge management, 2012
20 pages, 10 ...
Shin, Donghyuk   +2 more
openaire   +2 more sources

Multi-Scale Surface Descriptors [PDF]

open access: yesIEEE Transactions on Visualization and Computer Graphics, 2009
Local shape descriptors compactly characterize regions of a surface, and have been applied to tasks in visualization, shape matching, and analysis. Classically, curvature has be used as a shape descriptor; however, this differential property characterizes only an infinitesimal neighborhood. In this paper, we provide shape descriptors for surface meshes
Gregory, Cipriano   +2 more
openaire   +2 more sources

Multi-scale lung modeling

open access: yesJournal of Applied Physiology, 2011
Multi-scale modeling of biological systems has recently become fashionable due to the growing power of digital computers as well as to the growing realization that integrative systems behavior is as important to life as is the genome. While it is true that the behavior of a living organism must ultimately be traceable to all its components and their ...
Merryn H, Tawhai, Jason H T, Bates
openaire   +3 more sources

Multi-scale Discrete Surfaces [PDF]

open access: yes, 2002
In this article, we first propose a method to discretize a surface represented by a polyhedron. Then, we define a data structure used to work on such a discrete surface and that allows us to consider multi-scale discrete surfaces. Then, we explain how to perform easily and quickly boolean set operations on this data structure.
Burguet, Jasmine, Malgouyres, Rémy
openaire   +2 more sources

Steady state rheology from homogeneous and locally averaged simple shear simulations

open access: yesEPJ Web of Conferences, 2017
Granular materials and particulate matter are ubiquitous in our daily life and they display interesting bulk behaviors from static to dynamic, solid to fluid or gas like states, or even all these states together. To understand how the micro structure and
Shi Hao   +2 more
doaj   +1 more source

Multi-scale theory of rotating turbulence [PDF]

open access: yes, 2007
We consider turbulence induced by an arbitrary forcing and derive turbulence amplitude and turbulent transport coefficients, first by using a quasi-linear theory and then by using a multi-scale renormalisation analysis.
Balbus   +25 more
core   +5 more sources

Multi-Scale Learned Iterative Reconstruction

open access: yesIEEE Transactions on Computational Imaging, 2020
Model-based learned iterative reconstruction methods have recently been shown to outperform classical reconstruction algorithms. Applicability of these methods to large scale inverse problems is however limited by the available memory for training and extensive training times, the latter due to computationally expensive forward models.
Andreas Hauptmann   +3 more
openaire   +5 more sources

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