Titlebook: Emerging Technologies During the Era of COVID-19 Pandemic; Ibrahim Arpaci,Mostafa Al-Emran,Gon?alo Marques Book 2021 The Editor(s) (if app

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Behavioral Intention of Students in Higher Education Institutions Towards Online Learning During COrom 191 students whom have just completed the “Educational Technology” course on Spring 2020 at A’Sharqiyah University-Oman (ASU). The main finding of this study indicating that the identified factors; PEOU and SI significantly influenced students’ Behavioral Intention (BI) towards online learning,

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Molecular Regulation of Synaptic Releaseevelopment by non-conventional antigens. We then propose several DL-based platforms to utilize for future applications regarding the latest publications and medical reports. Considering the evolving date on COVID-19 and its ever-changing nature, we believe this survey can give readers some useful id

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Rhonda Douglas Brown,Vincent J. Schmithorstconcentrated on the use of machine learning algorithms in identifying and diagnosing the potential COVID-19 cases and predicting its extinction time. However, the number of articles published on the role of intelligent systems during COVID-19 pandemic is relatively few, suggesting that research in t

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Psychological Approach to Stress,. The IT tool can identify the descriptive details of the outbreak and it can also show the interrelationship between emerging infection to time and place. Additionally, the IT tool can also help further predict the trend or progression of the outbreak. This is a useful application for further publi

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Surabhi Gautam,Taruna Arora,Rima Dadaoups. Classification of COVID-19 has been performed using those extracted features through four different popularly used classifiers. The overall analysis of the study has been performed over two datasets. The Random Forest classifier generates the best accuracy of 98.6% and 98.9% for dataset 1 and