ABSTRACT
Since January 2020, the corona epidemic has created havoc worldwide. Although this virus has been mutated many times, the recent variant is more fatal for humans. Increasing active and death cases in the globe as well as in our country affect the psychological well-being of the people. India has experienced all variants including Alpha variant (B.1.1.7), Delta variant (B.1.617.2), and Omicron variant (B.1.1.529). All variants have some common symptoms along with extended symptoms. In this paper, we propose a rule base to classify and predict the variants of COVID-19 using a rough set approach. Our approach works for the elimination of redundant symptoms to create effective reduct, core, and selection of important symptoms to maintain the accuracy in a rule base. Our rules are validated to computer-generated data with 90% accuracy. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
Since January 2020, the corona epidemic has created havoc worldwide. Although this virus has been mutated many times, the recent variant is more fatal for humans. Increasing active and death cases in the globe as well as in our country affect the psychological well-being of the people. India has experienced all variants including Alpha variant (B.1.1.7), Delta variant (B.1.617.2), and Omicron variant (B.1.1.529). All variants have some common symptoms along with extended symptoms. In this paper, we propose a rule base to classify and predict the variants of COVID-19 using a rough set approach. Our approach works for the elimination of redundant symptoms to create effective reduct, core, and selection of important symptoms to maintain the accuracy in a rule base. Our rules are validated to computer-generated data with 90% accuracy. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
COVID pandemic and the subsequent recent emergence of its different variants have posed significant challenges for continuing everyday lifestyle, including any educational institute's campus life. In contrast, educational institutes conduct classes, exams, placement, and other co-curricular activities online, offline, and hybrid modes. Because of this, we have achieved a web-based survey on students about their mental health and other related issues such as anxiety, worry, disturbance, fear of infection, and mental anguish caused by COVID-19 in university undergraduates. 1100 pupils completed a digital survey in this crosssectional study. All these are college graduates from various universities in Bhubaneswar, India, and other universities in Odisha. COVID-19 awareness, nervousness, tension, panic, and mental illness in the past were used to screen the psychological distress. This paper reviews the current scenario of COVID-19 concerning psychological distress and related issues. Students' mental health can be affected by using the development of RST (rough set theory) principles. © 2022 Nova Science Publishers, Inc. All rights reserved.