Republic of Korea is building a multi-layered missile defense system against North Korea’s growing ballistic missile threat. To maximize the intercept performance of a multi-layered missile defense system, it is important to develop an efficient engagement plan that considers the interceptable time/space of each interceptor system for ballistic missiles. To do so, it is necessary to predict the flight trajectory of the ballistic missile, which must be done within a short time considering the short battlefield environment and the speed of the ballistic missile. This study presents a model for rapid trajectory prediction of ballistic missiles using the kinetic characteristics of each flight phase(thrust phase, midcourse phase, and re-entry phase) of ballistic missiles, a method for estimating kinetic information from ballistic missile observation data(time and position), and a mathematical analysis of the equations of motion of ballistic missiles.

효과적인 해양 교통관리 및 사고 예방 체계 구축에 있어서 AIS는 매우 중요한 요소이다. AIS는 선박의 동적, 정적, 항해 정보를 송수신하여 항해 의사결정을 지원하고 효과적인 선박 교통관제에 도움을 준다. 이러한 AIS는 환경적 요인, 기계적 요인 등에 의해서 손실 이 발생하며, 손실이 생긴 AIS 데이터는 선박 운항자 및 관제의 측면에서 의사결정에 혼동을 야기한다. 때문에, 본 연구에서는 AIS 데이터 를 통해 선박 항적 데이터를 수신하고, 해당 항적 데이터의 손실을 복원한다. AIS 데이터 수신 시 저비용의 싱글보드 컴퓨터인 Raspberry Pi와 AIS 수신 보드인 dAISy HAT을 활용하여 하드웨어를, Raspberry Pi의 운영체제인 LINUX환경과Open chart plotter인 OPENCPN을 통해 소 프트웨어를 구성하였다. 해당 시스템을 활용하여 수신한 AIS 데이터의 손실이 발생하는 데이터 중 활용이 가능한 위도, 경도, 시간 데이 터를 통해 손실이 발생한 구간의 데이터를 보간하고, 보간된 데이터는 “INTERP”라는 태그를 통해 기존의 데이터와 함께 인터넷 웹 서버 인 AWS S3에 저장한다. 본 연구를 통하여, AIS 수신기를 통하여 선박 항적 데이터를 수신하고, 손실이 발생한 부분을 보간함으로써 항적 데이터의 활용도를 높일 수 있을 것으로 보인다. 향후 손실된 AIS 데이터로 인한 선박 항적 데이터의 복원을 위한 다양한 기법을 활용한 연구가 필요하다.

기후변화와 식품공급망의 복잡성 증대로 식품 위해요소 의 발생 경로와 패턴이 다변화됨에 따라, 과학적 예측과 선 제적 개입이 가능한 예방형 식품안전 관리체계의 필요성이 대두되고 있다. 본 연구는 기후·환경 요인이 식품 위해요소 에 미치는 영향을 분석함으로써, 기후 민감성이 높은 위해 요소를 식별하고 예측 가능성과 주요 환경인자를 도출하였 다. 아울러 국내외 데이터 기반 위해예측 시스템의 운영 사 례를 비교·분석함으로써, 식품위해예측센터의 실질적 운영 과 역할을 위한 발전방향을 제시하였다. 본 연구를 통해 향 후 식품위해예측센터가 식품안전 정책의 과학화와 지능화 를 이끄는 전략적 플랫폼으로 기능하고, 예방 중심의 관리 체계로의 전환을 유도할 수 있도록 실효적 토대와 정책적 방향성을 제공하고자 한다.

This study analyzed the impact of improvements to the driver’s license system for elderly drivers on the incidence of traffic accidents. As South Korea’s population ages, the number of licensed drivers aged 65 years and older has surpassed 4.5 million as of 2024, accounting for approximately 15% of all license holders. Traffic accidents involving elderly drivers have increased steadily and tend to be more severe than those involving younger drivers. In response, the Road Traffic Act was amended in 2019 to shorten the license renewal cycle for drivers aged 75 and older, mandate dementia screening, and require traffic safety education. This study compared traffic accident statistics before and after the policy change (2018 and 2023) and used consulting data from 617 elderly drivers to examine the relationships between driving time, frequency, distance, and potential accident risk factors using a negative binomial regression analysis. The results show that after the policy changes, the number of traffic accidents per 10,000 elderly drivers decreased by up to 20.4%, demonstrating the effectiveness of the reforms. Furthermore, increased driving time, frequency, and distance were all significantly associated with a higher accident risk, whereas older age was linked to fewer accidents, likely owing to self-regulation among elderly drivers. Policy recommendations include limiting continuous driving time to 60 min, encouraging regular breaks, enhancing tailored safety education, tightening license aptitude test standards, and supporting the adoption of advanced safety features in vehicles. This study is expected to contribute to the development of effective policies to reduce traffic accidents among elderly drivers and create a safer traffic environment.

Stroke is one of the major causes of death worldwide, and in Korea, it has the second highest mortality rate after cancer. Stroke patients require continuous observation and rehabilitation treatment after onset, and in particular, paralysis symptoms are likely to worsen during rehabilitation, emphasizing the need for a real-time monitoring system. Meanwhile, the importance of medical data quality control (QC) algorithms is increasing. In this study, various causes such as failure of sensors such as voltage, current, and temperature of the patient's imaging device diagnostic device, or power loss, may cause malfunctions and transmit inaccurate data. Therefore, in order to secure the reliability of the patient's imaging device diagnostic device data, we plan to design data analysis and algorithms based on QC data of the imaging device diagnostic device. In order to design data analysis and algorithms based on QC data, a system capable of measuring and analyzing sensor data of imaging device diagnostic equipment was built. The reference values of the algorithms to be developed, such as physical limit tests, continuity tests, step tests, median filter tests, and frequency distribution tests, were derived. Voltage, current, and temperature sensor data were statistically analyzed, and in the case of analysis that changes in real time, algorithm S/W was inserted to calculate in real time. It is judged that by monitoring in real time, efficient management and maintenance of the device, and rapid response to device failures will be possible. In the case of device failure, various accidents and high costs can occur. Therefore, if real-time failures are confirmed and rapid maintenance is possible, maintenance costs can be reduced and reliability can be improved, so it is judged that efficient management of the device will be possible.

This study aims to explore the public perception of sports welfare by employing big data analysis techniques and to analyze it through a multi-layered lens grounded in Bronfenbrenner’s ecological systems theory. To this end, text mining software Textom and Ucinet 6 were utilized to examine online textual data related to “sports welfare” collected from May 2017 to February 2025. frequency analysis, TF-IDF analysis, degree centrality analysis, and CONCOR analysis were conducted. The results identified keywords such as “physical education.” “fitness.” “citizens.” “society.” “support.” “disability.” “voucher.” “university.” and “center.” as having high co-occurrence with sports welfare. CONCOR analysis revealed six major clusters: National Fitness 100 Service, Sports Voucher Program, Health Programs at Public Sports Centers, Community-Based Sports Welfare Environment, Training of Sports Welfare Professionals, and Support System Centered on the Korea Sports Promotion Foundation. This study suggests that the level of individual sports welfare can be enhanced through dynamic and interactive relationships between the individual and various environmental systems. Furthermore, to realize sustainable sports welfare, it is essential to develop long-term national strategies that holistically integrate all levels of the ecological systems from the micro system to the chrono system.