A Study of the Neutrosophic Set Significance on Deep Transfer Learning Models: An Experimental Case on a Limited COVID-19 Chest X-Ray Dataset - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook A Study of the Neutrosophic Set Significance on Deep Transfer Learning Models: An Experimental Case on a Limited COVID-19 Chest X-Ray Dataset write by Nour Eldeen M. Khalifa. This book was released on . A Study of the Neutrosophic Set Significance on Deep Transfer Learning Models: An Experimental Case on a Limited COVID-19 Chest X-Ray Dataset available in PDF, EPUB and Kindle. Coronavirus, also known as COVID-19, has spread to several countries around the world. It was announced as a pandemic disease by The World Health Organization (WHO) in 2020 for its devastating impact on humans. With the advancements in computer science algorithms, the detection of this type of virus in the early stages is urgently needed for the fast recovery of patients. In this paper, a study of neutrosophic set significance on deep transfer learning models over a limited COVID-19 chest x-ray dataset will be presented. The study relies on neutrosophic set theory, as it shows a huge potential for solving many computers problems related to the detection, and the classification domains.
Neutrosophic Sets and Systems, Vol. 41, 2021
Neutrosophic Sets and Systems, Vol. 41, 2021 - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Neutrosophic Sets and Systems, Vol. 41, 2021 write by Florentin Smarandache. This book was released on . Neutrosophic Sets and Systems, Vol. 41, 2021 available in PDF, EPUB and Kindle. “Neutrosophic Sets and Systems” has been created for publications on advanced studies in neutrosophy, neutrosophic set, neutrosophic logic, neutrosophic probability, neutrosophic statistics that started in 1995 and their applications in any field, such as the neutrosophic structures developed in algebra, geometry, topology, etc.
Collected Papers. Volume XI
Collected Papers. Volume XI - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Collected Papers. Volume XI write by Florentin Smarandache. This book was released on 2022-08-01. Collected Papers. Volume XI available in PDF, EPUB and Kindle. This eleventh volume of Collected Papers includes 90 papers comprising 988 pages on Physics, Artificial Intelligence, Health Issues, Decision Making, Economics, Statistics, written between 2001-2022 by the author alone or in collaboration with the following 84 co-authors (alphabetically ordered) from 19 countries: Abhijit Saha, Abu Sufian, Jack Allen, Shahbaz Ali, Ali Safaa Sadiq, Aliya Fahmi, Atiqa Fakhar, Atiqa Firdous, Sukanto Bhattacharya, Robert N. Boyd, Victor Chang, Victor Christianto, V. Christy, Dao The Son, Debjit Dutta, Azeddine Elhassouny, Fazal Ghani, Fazli Amin, Anirudha Ghosha, Nasruddin Hassan, Hoang Viet Long, Jhulaneswar Baidya, Jin Kim, Jun Ye, Darjan Karabašević, Vasilios N. Katsikis, Ieva Meidutė-Kavaliauskienė, F. Kaymarm, Nour Eldeen M. Khalifa, Madad Khan, Qaisar Khan, M. Khoshnevisan, Kifayat Ullah,, Volodymyr Krasnoholovets, Mukesh Kumar, Le Hoang Son, Luong Thi Hong Lan, Tahir Mahmood, Mahmoud Ismail, Mohamed Abdel-Basset, Siti Nurul Fitriah Mohamad, Mohamed Loey, Mai Mohamed, K. Mohana, Kalyan Mondal, Muhammad Gulfam, Muhammad Khalid Mahmood, Muhammad Jamil, Muhammad Yaqub Khan, Muhammad Riaz, Nguyen Dinh Hoa, Cu Nguyen Giap, Nguyen Tho Thong, Peide Liu, Pham Huy Thong, Gabrijela Popović, Surapati Pramanik, Dmitri Rabounski, Roslan Hasni, Rumi Roy, Tapan Kumar Roy, Said Broumi, Saleem Abdullah, Muzafer Saračević, Ganeshsree Selvachandran, Shariful Alam, Shyamal Dalapati, Housila P. Singh, R. Singh, Rajesh Singh, Predrag S. Stanimirović, Kasan Susilo, Dragiša Stanujkić, Alexandra Şandru, Ovidiu Ilie Şandru, Zenonas Turskis, Yunita Umniyati, Alptekin Ulutaș, Maikel Yelandi Leyva Vázquez, Binyamin Yusoff, Edmundas Kazimieras Zavadskas, Zhao Loon Wang.
Neutrosophic data envelopment analysis based on the possibilistic mean approach
Neutrosophic data envelopment analysis based on the possibilistic mean approach - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Neutrosophic data envelopment analysis based on the possibilistic mean approach write by Kshitish Kumar Mohanta. This book was released on 2023-01-01. Neutrosophic data envelopment analysis based on the possibilistic mean approach available in PDF, EPUB and Kindle. Data envelopment analysis (DEA) is a non-parametric approach for the estimation of production frontier that is used to calculate the performance of a group of similar decision-making units (DMUs) which employ comparable inputs to produce related outputs. However, observed values might occasionally be confusing, imprecise, ambiguous, inadequate, and inconsistent in real-world applications. Thus, disregarding these factors may result in incorrect decision-making. Thus neutrosophic sets have been created as an extension of intuitionistic fuzzy sets to represent ambiguous, erroneous, missing, and inaccurate information in real-world applications. In this study, we have proposed a technique for solving the neutrosophic form of the Charnes–Cooper–Rhodes (CCR) model based on single-value trapezoidal neutrosophic numbers (SVTrNNs). The possibilistic mean for SVTrNNs is redefined and applied the Mehar approach to transforming the neutrosophic DEA (Neu-DEA) model into its corresponding crisp DEA model. As a result, the efficiency scores of the DMUs are calculated using different risk parameter values lying in [0, 1]. A numerical example is given to analyze the performance of the all India institutes of medical sciences and compared it with Abdelfattah’s ranking approach.
A Survey on Deep Transfer Learning and Edge Computing for Mitigating the COVID-19 Pandemic
A Survey on Deep Transfer Learning and Edge Computing for Mitigating the COVID-19 Pandemic - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook A Survey on Deep Transfer Learning and Edge Computing for Mitigating the COVID-19 Pandemic write by Abu Su an. This book was released on . A Survey on Deep Transfer Learning and Edge Computing for Mitigating the COVID-19 Pandemic available in PDF, EPUB and Kindle. Global Health sometimes faces pandemics as are currently facing COVID-19 disease. The spreading and infection factors of this disease are very high. A huge number of people from most of the countries are infected within six months from its rst report of appearance and it keeps spreading. The required systems are not ready up to some stages for any pandemic; therefore, mitigation with existing capacity becomes necessary. On the other hand, modern-era largely depends on Artificial Intelligence(AI) including Data Science; Deep Learning(DL) is one of the current ag-bearer of these techniques. It could use to mitigate COVID-19 like pandemics in terms of stop spread, diagnosis of the disease, drug & vaccine discovery, treatment, and many more.
