ABSTRACT
This article has been withdrawn: please see Elsevier Policy on Article Withdrawal (https://www.elsevier.com/about/our-business/policies/article-withdrawal).This article has been withdrawn as part of the withdrawal of the Proceedings of the International Conference on Emerging Trends in Materials Science, Technology and Engineering (ICMSTE2K21). Subsequent to acceptance of these Proceedings papers by the responsible Guest Editors, Dr S. Sakthivel, Dr S. Karthikeyan and Dr I. A. Palani, several serious concerns arose regarding the integrity and veracity of the conference organisation and peer-review process. After a thorough investigation, the peer-review process was confirmed to fall beneath the high standards expected by Materials Today: Proceedings.The veracity of the conference also remains subject to serious doubt and therefore the entire Proceedings has been withdrawn in order to correct the scholarly record.
ABSTRACT
Purpose: Every day thousands of academic institutes suspend their classes and students are staying in their home maintaining social distancing due to the fear of COVID-19 pandemic and Nepal is no exception. Realizing these facts, this study aims to explore the factors for the effectiveness of online mode of classes to on-class course-based students and analyzes the perception of faculties and students toward online mode during the COVID-19 pandemic. Design/methodology/approach: It is based on exploratory research design, following mixed methods of qualitative and quantitative procedure. To build a rich understanding of the phenomenon, three-stage data collection procedure: preliminary interview, structural survey and validation were used. Findings: This study revealed triplet factors: infrastructure, student and teacher as antecedents of effectiveness of online classes during a pandemic. Technological support, infrastructure availability, faculty and students' perception have a significant relationship for the effectiveness of the online mode of the teaching-learning process. Students faced anxiety during the COVID-19 pandemic, but a higher willingness to learn reduces the level of anxiety. Originality/value: This study significantly contributes to the future management of higher education and digs the future path of online and on-class teaching-learning practices. © 2021, Dhruba Kumar Gautam and Prakash Kumar Gautam.
ABSTRACT
Here, the use of CNN-based technologies is provided with a new method for the detection of fraud during e-exams. This technology will assist providers in identifying any unknown situation during online tests, which are recommended by the majority of governments worldwide owing to the Covid-19 pandemic. Most colleges and students worldwide are severely impacted by their academic programmers, and the universities' role of testing using conventional approaches is a challenge. Thus, the students undergo several of their classes from various kinds of online third-party apps. The universities cannot, however, rely on these service providers for a long time to perform online examinations. Therefore, this work provides a full set-up of computing applications for students who can use them on their own laptops/personal computers with strict university guidance. © 2021
ABSTRACT
The necessity of rapid and appropriate diagnosis is emphasized by the COVID 19 as a serious danger to world health. The interchange of patient data across health centers addresses the growth of the number of patients and minimizes needless trials. The sharing of medical information helps patient care to accelerate;thus the sharing of health data is a need nowadays. Due to the sharing of information online among healthcare professionals, safety remains a key concern. In a diagnostic method during the COVID-19 pandemic, computer tomography (CT) and X-ray photos play an essential role in the transmission of information to organizations. Steganography techniques of encryption and imaging can be used in order to secure transmission of COVID-19 pictures. This work proposes a novel encryption for COVID-19 diagnostic using the image steganography (EIS-SDT) paradigm for safe data transfer. For the breakdown of images, a discrete multiple-level transformer for EIS-SDT employs the technique for optimizing the pixel selection for MANTA RY Foraging. For secrete image encryption, the EIS-SDT approach employs a dual logistic chaotic map. Additional security for the steganography process is ensured by the implementation of the DLCM-based encryption mechanism. The EIS-SDT model is efficiently performed by thorough simulation results analysis, and the results are analyzed using many assessment parameters. The analysis showed that the EIS-SDT model exceeds existing technology considerably. © 2021 IEEE.