A system for recognizing IADL using brightness-distribution sensors

2014 ◽  
pp. 55-58
Keyword(s):  
Brightness Distribution

Simulated synchrotron emission for the Tycho’s supernova remnants: an asymmetric initial mass model

2020 ◽  
Vol 494 (2) ◽  
pp. 1531-1538
Author(s):  
A Moranchel-Basurto ◽  
P F Velázquez ◽  
G Ares de Parga ◽  
E M Reynoso ◽  
E M Schneiter ◽  
...  
Keyword(s):  
Supernova Remnants ◽  
Brightness Distribution ◽  
Radio Continuum ◽  
Initial Mass ◽  
Continuum Emission ◽  
Synchrotron Emission ◽  
Mass Model ◽  
Mhd Simulations ◽  
Tycho’S Snr ◽  
Good Agreement

ABSTRACT We have performed 3D magnetohydrodynamics (MHD) numerical simulations with the aim of exploring the scenario in which the initial mass distribution of a supernova (SN) explosion is anisotropic. The purpose is to analyse if this scenario can also explain the radio-continuum emission and the expansion observed in young supernova remnants (SNRs). To study the expansion, synthetic polarized synchrotron emission maps were computed from the MHD simulations. We found a good agreement (under a number of assumptions) between this expansion study and previous observational results applied to Tycho’s SNR, which represents a good example of asymmetric young SNRs. Additionally, both the observed morphology and the brightness distribution are qualitatively reproduced.

Slit Type One-Dimensional Brightness Distribution Sensor

2014 ◽  
Author(s):  
Shota Nakashima ◽  
Shenglin Mu ◽  
Shintaro Okabe ◽  
Tatsuya Ichikawa ◽  
Kanya Tanaka ◽  
...  
Keyword(s):  
Brightness Distribution ◽  
One Dimensional

The radius of the Sun at centimeter waves and the brightness distribution across the disk

Solar Physics ◽  
1979 ◽  
Vol 63 (2) ◽  
Author(s):  
E. F�rst ◽  
W. Hirth ◽  
P. Lantos
Keyword(s):  
Brightness Distribution ◽  
The Sun

scholarly journals When Darwin Met Einstein: Gravitational Lens Inversion with Genetic Algorithms

2005 ◽  
Vol 22 (2) ◽  
pp. 128-135 ◽  
Author(s):  
Brendon J. Brewer ◽  
Geraint F. Lewis
Keyword(s):  
Genetic Algorithms ◽  
Gravitational Lensing ◽  
Surface Brightness ◽  
Initial Study ◽  
Brightness Distribution ◽  
Gravitational Lens ◽  
Atmospheric Effects ◽  
Lens Model ◽  
New Approach ◽  
Genetic Algorithm Approach

AbstractGravitational lensing can magnify a distant source, revealing structural detail which is normally unresolvable. Recovering this detail through an inversion of the influence of gravitational lensing, however, requires optimisation of not only lens parameters, but also of the surface brightness distribution of the source. This paper outlines a new approach to this inversion, utilising genetic algorithms to reconstruct the source profile. In this initial study, the effects of image degradation due to instrumental and atmospheric effects are neglected and it is assumed that the lens model is accurately known, but the genetic algorithm approach can be incorporated into more general optimisation techniques, allowing the optimisation of both the parameters for a lensing model and the surface brightness of the source.

Brightness distribution at λ = 3 and 21 cm near the solar north pole

Solar Physics ◽  
1974 ◽  
Vol 37 (2) ◽  
pp. 403-408 ◽  
Author(s):  
Franca Chiuderi Drago ◽  
Patrizio Patriarchi
Keyword(s):  
Brightness Distribution ◽  
North Pole

Brightness distribution at the base of a coronal hole

2006 ◽  
Vol 32 (2) ◽  
pp. 120-127 ◽  
Author(s):  
R. B. Teplitskaya ◽  
O. A. Ozhogina ◽  
I. P. Turova
Keyword(s):  
Coronal Hole ◽  
Brightness Distribution

DCT Coefficients Weighting (DCTCW)-Based Gray Wolf Optimization (GWO) for Brightness Preserving Image Contrast Enhancement

2021 ◽  
Author(s):  
Saorabh Kumar Mondal ◽  
Arpitam Chatterjee ◽  
Bipan Tudu
Keyword(s):  
Contrast Enhancement ◽  
Objective Evaluation ◽  
Brightness Distribution ◽  
Image Contrast ◽  
Optimization Techniques ◽  
Biological Behavior ◽  
Gray Wolf ◽  
Original Image ◽  
Image Characteristics ◽  
Image Contrast Enhancement

Image contrast enhancement (CE) is a frequent image enhancement requirement in diverse applications. Histogram equalization (HE), in its conventional and different further improved ways, is a popular technique to enhance the image contrast. The conventional as well as many of the later versions of HE algorithms often cause loss of original image characteristics particularly brightness distribution of original image that results artificial appearance and feature loss in the enhanced image. Discrete Cosine Transform (DCT) coefficient mapping is one of the recent methods to minimize such problems while enhancing the image contrast. Tuning of DCT parameters plays a crucial role towards avoiding the saturations of pixel values. Optimization can be a possible solution to address this problem and generate contrast enhanced image preserving the desired original image characteristics. Biological behavior-inspired optimization techniques have shown remarkable betterment over conventional optimization techniques in different complex engineering problems. Gray wolf optimization (GWO) is a comparatively new algorithm in this domain that has shown promising potential. The objective function has been formulated using different parameters to retain original image characteristics. The objective evaluation against CEF, PCQI, FSIM, BRISQUE and NIQE with test images from three standard databases, namely, SIPI, TID and CSIQ shows that the presented method can result in values up to 1.4, 1.4, 0.94, 19 and 4.18, respectively, for the stated metrics which are competitive to the reported conventional and improved techniques. This paper can be considered a first-time application of GWO towards DCT-based image CE.

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