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INTRODUCTION: L ittle has been studied to promote aviation health in South Korea. The aim of this study was to analyze the results of aviation medical examinations conducted in South Korea over the past 5 yr and, in doing so, provide evidence for establishing a health promotion, disease prevention plan. METHODS: S ubjects of the study consisted of applicants who underwent aviation medical examinations from January 1, 2016, to December 31, 2020. RESULTS: Over the past 5 yr, the total number of aviation medical examinations in South Korea has shown an annual increase of more than 10%. In the presence of the COVID-19 pandemic in 2020, the number of aviation medical examinations, both renewal and initial, for all types of licenses, except renewal aviation medical examinations for the ATCL, decreased. Disqualification rates were generally higher in initial examinations than in renewal examinations. The examination results for license renewal showed the AT PL disqualification rate to be the highest at 3.5 per 1000 pilots per year in their 50s, with cardiology cases being the most common reason for disqualification, followed by ophthalmology cases and psychiatry cases. Diagnostic categories for those disqualified after initial aviation medical examinations were similar, though ophthalmological causes were most common, followed by cases of psychiatry and neurology. CONCLUSION: Main causes of disqualification in airmen and air traffic controllers were identified as the presence of cardiovascular, ophthalmic, and psychiatric diseases. The results of this study provide evidence for improving health promotion activity plans to manage risk factors of such diseases for aviation workers. [ABSTRACT FROM AUTHOR]

In order to address the continuing growth of demands on airspace capacity, various navigation methods have been developed such as Area Navigation (RNAV), which allows pilots and air traffic controllers to have a higher degree of freedom in the airspace, but at the same time, the airspace becomes more complex than ever, and maintaining the safety and efficiency becomes challenging. To develop assistant tools for such situation, this paper proposes (i) a trajectory pattern identification framework that can identify complex and diverse trajectory patterns in the RNAV terminal airspace, and (ii) a recurrent neural network-based real-time trajectory pattern classification framework that is necessary for real-time air traffic applications. The proposed frameworks are tested with the real air traffic data recorded at Incheon International Airport, South Korea, in 2019, and evaluated by predicting estimated time of arrival in a real-time manner. • Area navigation terminal airspace has complex operations. • Trajectory patterns in the area navigation terminal airspace can now be identified. • Real-time trajectory pattern classification is achieved. • Automated air traffic assistant tools can be better developed and implemented. [ABSTRACT FROM AUTHOR]