ABSTRACT
The spread of COVID-19 has adversely affected many sectors, including tourism, retail, and manufacturing. The educational field is no exception, and many universities, including our own, have taken measures to prevent infection, such as implementing online classes and banning the use of facilities. These infection control measures are expected to change the living environment of students. If students are unable to lead their lives as before due to changes in their living environment, this may lead to a decline in academic performance and poor health. Therefore, it is very important for universities to understand how COVID-19 affects students' lives in order for them to lead healthy student lives. Therefore, this study aims to understand the impact of COVID-19 on students' lives by using data mining techniques to analyze the response data from a survey conducted for students, and to provide appropriate support and infection prevention measures for students. As a result, we identified a tendency for students to feel anxious about infection with COVID-19 and changes in students' evaluations of classes conducted in a face-to-face format under infection prevention measures. We believe that these results can contribute to reconsideration of support for students and class formats. © 2022 IEEE.
ABSTRACT
A system that uses the susceptible-exposed-infectious-removed (SEIR) model and some methods to predict COVID-19 (SARS-Cov-2) trajectory of the pandemic which is currently prevalent. This paper reports on how to estimate the optimal parameters of the SEIR model, which can predict the pandemics of infectious diseases. © 2021 IEEE.