ABSTRACT
Coronavirus disease 2019 (COVID-19) vaccines play a crucial role in preventing the spread of the disease. However, the circulation of low-quality and counterfeit vaccines seriously affects human health and the reputation of real vaccine manufacturers (VMs) and increases the amount of fear concerning vaccination. In this study, we address this problem by developing a blockchain-based COVID-19 vaccine tracking system called "Vacchain”. Our Vacchain allows users (USERs) to track and trace the route of vaccines. We propose three mechanisms, namely, a system manager (SYS-MAN), a mutual agreement concerning vaccine ownership, and vaccine passports, to enhance the security and reliability of data recorded in the Vacchain ledger. We develop this system on the Substrate platform with the Rust language. Our implementation, evaluation, and analysis have shown that Vacchain can trace and track vaccines smoothly. In addition, data security and reliability are enhanced by the abovementioned three mechanisms. The proposed system is expected to contribute to preventing the spread of COVID-19. © 2023 by the authors.
ABSTRACT
Short stick exercises have been attracting attention from the viewpoint of preventing falls and improving the health of elderly people and are generally performed under the guidance of instructors and nursing staff at nursing homes. However, in situations such as the COVID-19 pandemic, where people should refrain from unnecessary outings, it is advisable that individuals perform short stick exercises at home and record their exercise implementation status. In this paper, we propose an inertial measurement unit (IMU)-sensor-based short stick exercise tracking method that can automatically record the types and amounts of exercises performed using a short stick equipped with an IMU sensor. The proposed method extracts time-domain and frequency-domain features from linear acceleration and quaternion time-series data obtained from the IMU sensor and classifies the type of exercise using an inference model based on machine learning algorithms. To evaluate the proposed method, we collected sensor data from 21 young subjects (in their 20s) and 14 elderly subjects (79-95 years old), where the participants performed three sets (10 times per set) of eight basic types of short stick exercises (five types for elderly people). As a result of evaluating the proposed method using this data set, we confirmed that when LightGBM was used as the learning algorithm, it achieved F values of 90.0 and 86.6% for recognizing the type of exercise for young and elderly people, respectively. © 2022 M Y U Scientific Publishing Division. All rights reserved.
ABSTRACT
Due to the spread of COVID-19, the daily lives of most people have changed drastically. The educational environment was certainly no exception. Most universities in Japan restricted access to their campuses and had to provide students with remote lectures. In our university, most lectures were provided remotely during the spring semester, 2020. Our school decided to give all lectures using Microsoft Teams and made videos on how to take the remote lectures using Microsoft Teams;thus we were able to start giving remote lectures smoothly. We report on the approaches which helped us to create a successful environment for providing remote lectures in our school. In this paper, we also report the effects of on-line flipped lectures, which we conducted on a trial basis. © 2022, ICIC International. All rights reserved.