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Institution

Government College

About: Government College is a based out in . It is known for research contribution in the topics: Population & Ring (chemistry). The organization has 4481 authors who have published 5986 publications receiving 57398 citations.


Papers
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Journal ArticleDOI
TL;DR: A noisy feature removal scheme for multi-focus image fusion combining the decision information of optimized individual features is proposed and it reveals that GGWO based proposed method performs better visual quality than other methods.
Abstract: Modern developments in image technology enabled easy access to an innovative type of sensor-based networks, Camera or Visual Sensor Networks (VSN). Nevertheless, more sensor data sources bring about the problem of overload information. To solve this problem, some researchers have been carried out on the techniques to counteract the data overload caused by sensors without losing useful data. The aim of fusion in each application is to combine images from several sensors, which leads to the decreased amount of input image data, producing an image with more accurate data. This paper proposes a noisy feature removal scheme for multi-focus image fusion combining the decision information of optimized individual features. The proposed scheme is developed in two main steps. In the first step, the diverse types of features are extracted from each block of input blurred images. The useful information of these individual features indicates which image block is more focused among corresponding blocks in source images. After that, noisy features are removed using binary Genetic Grey wolf optimizer (GGWO) algorithm. The ensemble decision based on individual features is employed to fuse blurred images in the second step. The experimentation is evaluated on different multi-focus images and it reveals that GGWO based proposed method performs better visual quality than other methods.

40 citations

Journal ArticleDOI
TL;DR: In this paper, the Coulomb and proximity potential model for deformed nuclei (CPPMDN) was used to calculate the α-decay properties of superheavy nuclei Z = 124 in the range 282 ≤ A ≤ 333.
Abstract: We have studied the α-decay properties of superheavy nuclei (SHN) Z = 124 in the range 282 ≤ A ≤ 333 using the Coulomb and proximity potential model for deformed nuclei (CPPMDN). The calculated α half-lives agree with the values computed using the Viola–Seaborg systematic, the universal curve of Poenaru et al. [Phys. Rev. C 83 (2011) 014601; 85 (2012) 034615] and the analytical formulas of Royer [J. Phys. G, Nucl. Part. Phys. 26 (2000) 1149]. To identify the mode of decay of these isotopes, the spontaneous-fission half-lives were also evaluated using the semiempirical relation given by Xu et al. [Phys. Rev. C 78 (2008) 044329]. The calculated half-lives help to predict the possible isotopes of this superheavy element Z = 124. As we could observe α chain consistently from the nuclei 288−312124, we have predicted that these nuclei could not be synthesized and detected experimentally via α decay as their decay half-lives are too small. The nuclei 313−318124 were found to have long half-lives and hence could be sufficient to detect them if synthesized in a laboratory.

39 citations

Journal ArticleDOI
TL;DR: In this paper, higher-order closed-form solutions are obtained for static bending and free vibration analysis of laminated composite and sandwich spherical shells using a generalized higher order shell theory.

39 citations

Journal ArticleDOI
TL;DR: In this paper, the effective atomic number (Zeff) and electron density (Nel) of hydroxyapatite (HA) and cortical bone have been computed for total photon interaction in the wide energy range of 1-keV-100-GeV using WinXCom.

39 citations


Authors

Showing all 4481 results

NameH-indexPapersCitations
Rajesh Kumar1494439140830
Sanjeev Kumar113132554386
Rakesh Kumar91195939017
Praveen Kumar88133935718
V. Balasubramanian5445710951
Ghulam Murtaza53100514516
Marimuthu Govindarajan522126738
Muhammad Akram433937329
Ghulam Abbas404396396
Shivaji H. Pawar391684754
Muhammad Afzal381184318
Deepankar Choudhury351993543
Hidayat Hussain343165185
Hitesh Panchal341523161
Sher Singh Meena331873547
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202227
2021991
2020797
2019477
2018486
2017437