In modern aircraft, batteries are essential to power the systems. However, these batteries pose safety concerns due to potential thermal runaway that can occur due to overheating or short circuiting, leading to fire. The US Federal Aviation Administration (FAA) reported that there will be more than 61 battery-related accidents in 2024, highlighting the need for stringent safety protocols and effective risk management strategies in the aviation sector. Battery accidents are mainly caused by improper handling, extreme temperatures, and use of counterfeit or low-quality batteries. To address these issues, the aviation industry is implementing comprehensive monitoring systems, regulatory frameworks, and stringent safety standards through safety management systems (SMS). This study aims to analyze the latest technological trends to ensure battery safety in aircraft and develop proactive risk management strategies to prevent future battery-related accidents. Advances in battery technology combined with improved safety measures and regulatory compliance will play a vital role in effectively mitigating battery-related risks in aviation systems.

The excessive concentration of air cargo transportation at Incheon International Airport has raised concerns about economic inefficiencies and the need for alternative airports in case of emergencies. This study investigates the necessity of diversifying air cargo functions and evaluates the feasibility of sharing these functions with Cheongju International Airport. The potential for activating air cargo at Cheongju Airport was examined from the perspectives of infrastructure, local government support policies, and regional air cargo demand. The results showed that Cheongju Airport has limited capacity for handling air cargo due to a lack of related infrastructure. However, based on the 2023 air cargo performance data, it was found that using Cheongju Airport could reduce inland logistics costs and transportation time by an average of about 40%. Furthermore, with the planned policy support from local governments in the Chungcheong region and the expansion of transportation networks, it is expected that Cheongju Airport can efficiently share air cargo demand once its infrastructure is expanded.

The purpose of this study is to analyze the relationship between job values, self-efficacy, and job preparation behavior among aviation service major students and to verify the mediating role of self-efficacy. First, the results confirm that extrinsic job values have a significant positive effect on self-efficacy, while intrinsic job values do not show a significant impact. Second, self-efficacy positively influences job preparation behavior, indicating that students with higher self-efficacy are more actively engaged in job-related activities such as job information searches, interview preparation, and competency development. Third, extrinsic job values have a direct positive effect on job preparation behavior, while intrinsic job values do not show a significant relationship. Fourth, the mediating effect of self-efficacy is confirmed in the relationship between extrinsic job values and job preparation behavior. However, the mediating effect of self-efficacy is not observed in the relationship between intrinsic job values and job preparation behavior. Based on these results, this study highlights the importance of structured career development programs and educational approaches that enhance both self-efficacy and job motivation, ultimately aiding students in achieving successful employment outcomes.

Artificial intelligence (AI) is rapidly advancing in the aviation industry, enhancing efficiency, improving safety, and optimizing operational decision-making. However, its integration also raises new legal and cybersecurity challenges. This study analyzes the latest trends in AI applications within aviation, including air traffic control, aircraft operations, and airport management. It also examines international regulatory frameworks, such as the EU AI Act, EASA AI Roadmap 2.0, and ICAO cybersecurity guidelines, to assess legal responses. Additionally, it evaluates Korea's legislative developments and the need for regulatory adaptation to mitigate AI-related risks. Based on a comparative analysis of global AI regulations and aviation cybersecurity policies, this study provides policy recommendations to strengthen legal frameworks and enhance aviation security against AI-driven threats.

Urban air mobility (UAM) is an emerging transport system that operates above urban areas, addressing urbanization-related challenges. As a critical component of UAM infrastructure, vertiports require significant time and resource investment. Therefore, a systematic model is essential for determining optimal locations. This study proposes a location assessment model based on two primary service objectives: passenger transportation and emergency medical services. The model follows a step-by-step assessment, integrating site constraints, user demand, and facility supply with tailored evaluation criteria. To validate the model's applicability, an empirical analysis was conducted in the Gyeongsangnam-do region. The analysis identified optimal vertiport locations for passenger transport and emergency medical services. Prioritization assessment demonstrated the practical utility and effectiveness of the proposed model.

This study aims to analyze research trends in the domain of air traffic control and identify significant issues and topics within the related literature. The data were collected from the Research Information Service System (RISS), and 297 Korean research papers containing the keyword "air traffic control" were analyzed using Textom. The main keywords were examined and visualized through frequency analysis and keyword network analysis, following a data refinement process. Additionally, CONCOR cluster analysis was conducted to assess keyword centrality. Research on air traffic control has been consistently ongoing since 1972, with a marked expansion in the 2010s. The term frequency (TF) analysis of the main keywords identified "air traffic control," "system," "flight," "aviation," and "airspace" as main keywords. The TF-IDF weighted analysis revealed that the main keywords were "system," "airspace," "air traffic control," "flight," and "UAV." Semantic network and CONCOR cluster analysis indicated that keywords with the highest degree centrality were "flight," "airspace," "air traffic control," "air traffic controller," and "plane." This study highlights the key topics related to air traffic control, as evidenced by the results of the keyword network analysis.

With the advancement of Unmanned Aerial Vehicle (UAV) technology and improvements, multi-UAV systems have gained significant attention in various application domains. Target tracking using multiple UAVs is a crucial research topic in military surveillance, disaster response, environmental monitoring, logistics, and security. This paper proposes a vector field-based cooperative control technique for multi-UAV target tracking. The proposed approach generates roll angle commands to maintain a constant distance from the target, ensuring both mission efficiency and safety. Additionally, velocity control commands are designed to maintain a constant phase angle between UAVs, facilitating multiple viewpoints and collision avoidance. The effectiveness of the control commands is validated through numerical simulations for both stationary and moving targets. The proposed guidance strategy can be extended to cooperative control applications involving a large number of ground robots as well as UAVs.

This study explores the integrated application of Evidence-Based Training (EBT), an International Civil Aviation Organization (ICAO) standard, with digital technologies to enhance aviation safety in the era of digital transformation. EBT strengthens pilots' practical response capabilities based on real flight data and accident analysis, while digital technologies improve training effectiveness through data analytics, advanced simulators, and virtual reality (VR). The study underscores the necessity of such advancements to prevent incidents like the 2024 Muan International Airport accident and analyzes cases from ICAO, EASA, FAA, and CAA. Key challenges in the domestic training system include a lack of digital infrastructure, insufficient instructor competency, and inadequate data management. To address these issues, the study proposes solutions such as digital infrastructure development, instructor training, legal support, and the establishment of a structured data management system to effectively implement EBT in South Korea. Additionally, the study suggests introducing digital EBT into student pilot training to enhance safety capabilities from the early stages. The findings confirm that digital EBT has the potential to revolutionize aviation safety culture and contribute to accident prevention. However, limitations remain regarding cost and feasibility analysis, highlighting the need for future economic viability assessments and empirical research.