Study on The Prediction Method of Characteristic Parameters of Solar X-ray Flares

2013 ◽  
Vol 37 (3) ◽  
pp. 255-265 ◽  
Author(s):  
Guo Ce ◽  
Xue Bing-sen ◽  
Lin Zhao-xiang
Author(s):  
В.Т. Аванесян ◽  
И.В. Писковатскова ◽  
В.М. Стожаров

AbstractThe results of investigations of the optical-absorption spectra of bismuth-silicate (Bi_12SiO_20) single crystals are presented. The band-gap width and the characteristic Urbach energy are determined. The effect of preliminary X -ray irradiation on the behavior of the experimental spectral dependences and the values of the characteristic parameters induced by the bismuth-silicate defect structure is established.


2021 ◽  
Vol 54 (6) ◽  
Author(s):  
Hiroki Ogawa ◽  
Shunsuke Ono ◽  
Yuki Watanabe ◽  
Yukihiro Nishikawa ◽  
Shotaro Nishitsuji ◽  
...  

Small-angle X-ray scattering (SAXS) coupled with computed tomography (CT), denoted SAXS-CT, has enabled the spatial distribution of the characteristic parameters (e.g. size, shape, surface, length) of nanoscale structures inside samples to be visualized. In this work, a new scheme with Tikhonov regularization was developed to remove the effects of artifacts caused by streak scattering originating from the reflection of the incident beam in the contour regions of the sample. The noise due to streak scattering was successfully removed from the sinogram image and hence the CT image could be reconstructed free from artifacts in the contour regions.


2020 ◽  
Author(s):  
S Sai Thejeshwar ◽  
Chaitanya Chokkareddy ◽  
K Eswaran

The novel coronavirus (COVID-19) pandemic is pressurizing the healthcare systems across the globe and few of them are on the verge of failing. The detection of this virus as early as possible will help in contaminating the spread of it as the virus is mutating itself as fast as possible and currently there are about 4,300 strains of the virus according to the reports. Clinical studies have shown that most of the COVID-19 patients suffer from a lung infection similar to influenza. So, it is possible to diagnose lung infection using imaging techniques. Although a chest computed tomography (CT) scan has been shown to be an effective imaging technique for lung-related disease diagnosis, chest X-ray is more widely available across the hospitals due to its considerably lower cost and faster imaging time than CT scan. The advancements in the area of machine learning and pattern recognition has resulted in intelligent systems that analyze CT Scans or X-ray images and classify between pneumonia and normal patients. This paper proposes KE Sieve Neural Network architecture, which helps in the rapid diagnosis of COVID-19 using chest X-ray images. This architecture is achieving an accuracy of 98.49%. This noninvasive prediction method can assist the doctors in this pandemic and reduce the stress on health care systems.


2012 ◽  
Vol 41 (9) ◽  
pp. 1090-1093
Author(s):  
杨国洪 YANG Guohong ◽  
韦敏习 WEI Minxi ◽  
侯立飞 HOU Lifei ◽  
易涛 YI Tao ◽  
李军 LI Jun ◽  
...  

1992 ◽  
Vol 287 (1) ◽  
pp. 183-185 ◽  
Author(s):  
K J I'Anson ◽  
V J Morris ◽  
P R Shewry ◽  
A S Tatham

Small angle X-ray scattering was used to study the solution conformation of the C hordeins of barley (Hordeum vulgare), a group of proteins whose primary structure consists predominantly of an octapeptide repeat motif. Measurements on the protein in 0.1 M-acetic acid at 25 degrees C are consistent with a model for the protein conformation of a stiff coil, the so-called ‘worm-like’ chain. The characteristic parameters (the Kuhn statistical segment length and the contour length) of the protein were calculated as 5.11 and 71.5 nm respectively.


Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 264
Author(s):  
Yingquan Qi ◽  
Xiangyang Gan ◽  
Zhong Li ◽  
Lu Li ◽  
Yan Wang ◽  
...  

In order to investigate the change law of the explosion characteristic parameters of hybrid mixture of coal dust and gas, and then establish an effective prediction method of these parameters, the maximum explosion pressure, explosion index, and lower explosion limit of coal dust and gas mixtures were measured in a standard 20 L spherical explosion system. Four different kinds of hybrid mixture were selected in this study and they are composed of coal dust with different components and gas respectively. According to the measured results, the change law of the explosion characteristic parameters of hybrid mixture of coal dust and gas was analyzed, and the prediction method of these parameters was discussed. The results show that the addition of gas to a coal dust cloud can obviously increase its maximum explosion pressure and explosion index and notably reduce its minimum explosion concentration. On increasing the gas equivalent ratio, the maximum explosion pressure of coal dust and gas mixture increases linearly and the explosion index increases quadratically, while the decrease curve of the lower explosion limit is nonlinear. Based on these change laws, the methods for predicting the maximum explosion pressure and the explosion index of hybrid mixture of coal dust and gas were established respectively. The applicability of the existing methods for predicting the lower explosion limit of hybrid mixture to coal dust and gas mixture was demonstrated.


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