Background: Information and communication technology development provides services to various fields. In particular, the development of mobile technology has made ubiquitous services possible. However, as technology advances, security is being emphasized more and more. The existing method of user authentication by entering an ID and password is likely to leak sensitive information if the server is attacked or keylogged. Therefore, multi-level authentication is needed to prevent server attacks or keylogging. Methods: Biometric authentication technology has been utilized by smartphones, but it is challenging to apply in the case of a lost device because the central server does not manage biometric data. Encrypting transactions through blockchain technology makes data management more secure because blockchain technology is distributed, and there is no primary target for hackers. Results: The method proposed in this study can become a basis for an authentication method that guarantees both security and integrity due to the synergetic use of biometric and blockchain technologies. Conclusions: The information stored in the service provider does not include sensitive information such as the user’s biometric data but is only a means of verifying the user’s information in the blockchain transaction with guaranteed anonymity. Therefore, users can receive services with confidence and safety.

Due to COVID-19, non-F2F (non-face-to-face) learning is being conducted in educational sites around the world. Unlike theoretical subjects, which have a variety of applicable non-F2F learning content, in practical subjects, learners may undergo many difficulties due to many learning activities. Therefore, this research tries to design and develop a mobile application that allows learners to perform a self-diagnostic on their learning progress. In this research, we conducted a mobile application usability evaluation for 36 students who participated in non-F2F Arduino practice learning. To this end, we applied the ADDIE (Analysis, Design, Development, Implement, and Evaluation) model to develop a self-diagnostic mobile application for students’ learning progress according to the learning content. The research tool modified and distributed the question item appropriate for this subject’s study for the mobile usability evaluation that was used in the previous study. This research applied the ADDIE model to analyze the characteristics of students and learning contents, including designed learning contents, database, menu structure, developed learning contents, and mobile application. After using this in non-F2F practice learning for 15 weeks, a mobile application usability evaluation was conducted. As a result of the study, due to receiving usability scores between 3.53 and 4.42, it was found that the learning progress self-diagnostic in non-F2F practice learning was essential and that mobile applications were useful in non-F2F practice learning. Additionally, 33 out of 36 students responded that it would be useful for their learning if they actively used it in other subjects as well. We have found that leveraging self-diagnostic mobile applications through the mobile application usability evaluation tool can be useful for non-F2F practice learning. Additionally, it is expected to be useful for non-F2F practice learning if additional research is conducted on other factors as well such as teaching presence, online learning engagement, and learning flow in the future.

Due to the recent pandemic of COVID-19, sports events around the world are being hit hard in 2020. However, with the KBO league having been opened even though it is late, it has attracted the attention of baseball fans around the world as it becomes an overseas broadcast. However, since the Republic of Korea is also affected by the global economic crisis, the financial burden of professional baseball teams that rely on their parent company has become a hot topic. Therefore, in this study, we collected records such as IP, ERA, and WAR of KBO league FA pitchers and news related to FA contracts. Then, we preprocessed the data and analyzed it. To this end, we analyzed the performance and financial burden indicators according to the pitcher's age and contract years. In addition, it was found that the performance of athletes was maintained until their mid 30’s, and through rational FA contracts, the team and athletes were able to suggest win-win strategies. And with this basic data analysis in the sports industry, the possibility of utilizing these strategies was confirmed.