• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.9
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• pp.233-239
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• 2019

An unmanned underwater vehicle is a major weapon system that allows surveillance and reconnaissance missions in border areas or threatening areas where enemy submarines are present. Unmanned underwater vehicles can be used to explore underwater resources, predict disasters, and survey the topography of the ocean floor in the civilian fields, while in the defense fields, it can be used for anti-submarine reconnaissance and mine countermeasures. In this paper, we first investigate the main classification of unmanned underwater vehicles, and foreign R&D trends are analyzed based on the main classification criteria by weight, such as portable, light, heavy and large-scale unmanned underwater vehicles. Then we examine the trends in the development of domestic unmanned underwater vehicles. Finally, through the analysis of both domestic and foreign unmanned underwater vehicles, we present future development trends of unmanned underwater vehicles in order to set defense goals to counter the anticipated threats and diversified potential environment.

• Journal of the Korea Society for Simulation
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• v.29 no.1
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• pp.47-55
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• 2020

This paper presents a real-time autonomous computation of shot numbers and aiming points against multiple soft targets on grounds by applying an unsupervised learning, k-mean clustering and Monte carlo simulation. For this computation, a 100 × 200 square meters size of virtual battlefield is created where an augmented enemy infantry platoon unit attacks, defences, and is scatted, and a virtual weapon with a lethal range of 15m is modeled. In order to determine damage types of the enemy unit: no damage, light wound, heavy wound and death, Monte carlo simulation is performed to apply the Carlton damage function for the damage effect of the soft targets. In addition, in order to achieve the damage effectiveness of the enemy units in line with the commander's intention, the optimal shot numbers and aiming point locations are calculated in less than 0.4 seconds by applying the k-mean clustering and repetitive Monte carlo simulation. It is hoped that this study will help to develop a system that reduces the decision time for 'detection-decision-shoot' process in battalion-scaled combat units operating Dronebot combat system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.5
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• pp.409-416
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• 2020

Artificial intelligence, which is in the spotlight as the core driving force of the 4th industrial revolution, is expanding its scope to various industrial fields such as smart factories and autonomous driving with the development of high-performance hardware, big data, data processing technology, learning methods and algorithms. In the field of defense, as the security environment has changed due to decreasing defense budget, reducing military service resources, and universalizing unmanned combat systems, advanced countries are also conducting technical and policy research to incorporate artificial intelligence into their work by including recognition systems, decision support, simplification of the work processes, and efficient resource utilization. For this reason, the importance of technology-driven planning and investigation is also increasing to discover and research potential defense future technologies. In this study, based on the research data that was collected to derive future defense technologies, we analyzed the characteristic evaluation indicators for future technologies in the field of artificial intelligence and conducted empirical studies. The study results confirmed that in the future technologies of the defense AI field, the applicability of the weapon system and the economic ripple effect will show a significant relationship with the prospect.

• The Journal of the Convergence on Culture Technology
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• v.10 no.4
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• pp.443-449
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• 2024

This study aims to analyze the complex impact of technological changes in the Fourth Industrial Revolution era and demographic shifts in Korea on military personnel management, and to explore innovative strategies for the Korean military's workforce operations. The research findings indicate that changes in future battlefield environments and the introduction of advanced technologies necessitate a fundamental restructuring of military personnel, emphasizing a shift towards a highly specialized and elite workforce. Key research findings are as follows: First, the military application of cutting-edge technologies, such as unmanned systems, autonomous weapon systems, and AI-based decision support systems, is expanding. Second, this technological advancement requires a restructuring of personnel to foster a technology-intensive elite force, including optimizing troop size, reorganizing unit structures, and increasing the utilization of civilian expertise. Third, strategies for securing high-tech talent include strengthening internal technology talent development programs, establishing systems to attract civilian experts, and building a talent development system through industry-academia-research cooperation. The significance of this study lies in providing a theoretical and practical foundation for building a future-oriented and efficient Korean military organization by presenting innovative measures for military human resource management systems suitable for the Fourth Industrial Revolution era. For these changes to be successfully implemented, cooperation among relevant stakeholders, including the military, government, academia, and industry, is essential, supported by comprehensive national-level planning and support.