• The Korean Journal of Emergency Medical Services
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• v.26 no.1
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• pp.7-19
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• 2022

Purpose: The purpose of this study is to evaluate the interrupted chest compression time during the use of an automated external defibrillator (AED) depending on different AED practice training methods, and to report differences in self-efficacy before and after training. Methods: We enrolled university freshmen who have had cardiopulmonary resuscitation (CPR) training but have not or have had AED training but over 6 months. We examined differences between the group that practiced only shockable rhythms during training and the group that practiced both shockable and non-shockable rhythms. Results: A total of 72 individuals participated in this study, with 36 individuals each in the control and experimental groups. There was no statistically significant difference in the proficiency of AED usage between the two groups. In non-shockable cases, the experimental group showed shorter chest compression interruption time than the control group (2.30±1.21sec vs. 3.16±1.73 sec; p<0.01). In terms of self-efficacy before and after training, both groups showed higher self-efficacy after than before training. Conclusion: Individuals who underwent training that provided practice on both shockable and non-shockable rhythms had a shorter interrupted chest compression time when using the AED.

• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.4
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• pp.425-433
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• 2022

This paper studies the method of delivering munitions using both drones and UGVs that are developing along with the 4th Industrial Revolution. While drones are more mobile than UGVs, their loading capacity is small, and UGVs have relatively less mobility than drones, but their loading capacity is better. Therefore, by simultaneously operating these two delivery means, each other's shortcomings may be compensated. In addition, on actual battlefields, time constraints are an important factor in delivering munitions. Therefore, assuming an actual battlefield environment with a time limit, we establish delivery routes that minimize delivery time by operating both drones and UGVs with different capacities and speeds. If the delivery is not completed within the time limit, penalties are imposed. We devised the hybrid genetic algorithm to find solutions to the proposed model, and as results of the experiment, we showed the algorithm we presented solved the actual size problems in a short time.

• Annual Conference of KIPS
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• 2010.11a
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• pp.117-119
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• 2010

미래 전쟁은 과거의 재래식 전쟁과는 판이하게 변화된 환경 속에서 새로운 전투 형태와 방법으로 전개될 것이다. 특히, 첨단 기술의 급속한 발전은 전장에서 싸우는 방법을 변화시키는 주요 요인이라고 할 수 있다. 전장에서 적을 먼저 발견하고 타격하기 위해서는 실시간 표적 획득 및 첩보 수집과 정확한 상황판단 및 적시적인 지휘가 요구되기 때문에 정보 수집 자산이 부족한 사 여단급 부대를 대상으로 감시 정찰 센서 네트워크 시스템을 구축하는 것이 필요하다. 그러나 평시 체계와 전시 체계의 운용 개념이 부족한 상태에서 실 세계에 적용하는 것은 유지비용의 증가, 감지 오류, 야전 환경과의 부적합 등을 야기한다. 따라서, 이러한 문제점의 해결 대안으로 이 논문에서는 지상군 작전에서 적의 조기 발견과 전장 가시화에 필요한 전장감시 센서 네트워크 시스템을 위한 상황 인식 프레임 워크를 제안하였다.

• Journal of the Korea Institute of Military Science and Technology
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• v.26 no.2
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• pp.197-204
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• 2023

The importance of each warfighting function for Army TIGER unit attack drones is measured using the AHP technique. As a result, the importance of attack drones is high in the order of maneuver, firepower, intelligence, command/control, protection, and operation sustainment, but the importance of maneuver, firepower, and intelligence are almost similar. In addition, it is analyzed that attack drones capable of carrying out day and night missions by being equipped with an EO/IR sensor and being commanded/controlled in conjunction with the C4I system to eliminate threats with small bombs or aircraft collisions is needed. Finally, based on the results of this study, a virtual battle scenario for attack drones is proposed.

• Convergence Security Journal
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• v.24 no.1
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• pp.77-82
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• 2024

Recent research has seen significant improvements in various object detection and classification models overall. However, the study of object detection and classification in situations where objects are partially obscured remains an intriguing research topic. Particularly in the military domain, unmanned combat systems are often used to detect and classify objects, which are typically partially concealed or camouflaged in military scenarios. In this study, a method is proposed to enhance the classification performance of partially obscured objects. This method involves adding occlusions to specific parts of object images, considering the surrounding environment, and has been shown to improve the classification performance for concealed and obscured objects. Experimental results demonstrate that the proposed method leads to enhanced object classification compared to conventional methods for concealed and obscured objects.

• Convergence Security Journal
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• v.24 no.2
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• pp.161-165
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• 2024

Recently, speech recognition models have been advancing, accompanied by the development of various speech processing technologies to obtain high-quality data. In the defense sector, efforts are being made to integrate technologies that effectively remove noise from speech data in noisy battlefield situations and enable efficient speech recognition. This paper proposes a method for effective speech recognition in the midst of diverse noise in a battlefield scenario, allowing commanders to convey orders. The proposed method involves noise removal from noisy speech followed by text conversion using OpenAI's Whisper model. Experimental results show that the proposed method reduces the Character Error Rate (CER) by 6.17% compared to the existing method that does not remove noise. Additionally, potential applications of the proposed method in the defense are discussed.

• Journal of the Korea Safety Management & Science
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• v.26 no.3
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• pp.11-17
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• 2024

The Occupational Safety and Health Act (OSHA) aims to maintain and promote the safety and health of workers. Additionally, violations of the act can result in imprisonment or fines, depending on the severity of the offense. This study examines whether the severity of OSHA violations is proportional to the size of the fines imposed. There are 120 items subject to fines, with penalties ranging from a minimum of 50,000 won to a maximum of 30 million won. To assess the severity of these items, pairwise comparisons were conducted, and the results were expressed numerically. In summary, no significant correlation was found between the severity of violations and the amount of the fines. Therefore, this study proposes calculating fines based on the severity of violations. In many small companies, resources (e.g., budget and manpower) are limited. Thus, greater attentions tend to be directed toward addressing items with higher fines. Consequently, aligning the severity of legal violations with the size of the fines may contribute to improving the industrial safety.

• KIISE Transactions on Computing Practices
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• v.23 no.6
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• pp.343-349
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• 2017

Combat modeling and simulation (M&S) of large-scale computer generated forces (CGFs) enables the development of even the most sophisticated strategy of combat warfare and the efficient facilitation of a comprehensive simulation of the upcoming battle. The DEVS-POMDP framework is proposed where the DEVS framework describing the explicit behavior rules in military doctrines, and POMDP model describing the autonomous behavior of the CGFs are hierarchically combined to capture the complexity of realistic world combat modeling and simulation. However, it has previously been well documented that computing the optimal policy of a POMDP model is computationally demanding. In this paper, we show that not only can the performance of CGFs be improved by an efficient POMDP tree search algorithm but CGFs are also able to conveniently learn the behavior model of the enemy through case studies in the scenario of counterfire warfare and the scenario of a mechanized infantry brigade's offensive operations.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.4
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• pp.138-144
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• 2020

The Army's engineers are carrying out a range of operations using various equipment, of which, artillery unit support is the representative engineering operation field. The main task of the artillery unit is to attack the enemy's center with firepower from the rear of a friendly force. The artillery must move its original position after firing several times to prevent exposure of the shooting position. This paper proposed a mathematical model and heuristic algorithm that can be used to determine the optimal allocation among engineer equipment, the team (work), and position while reflecting the constraints of the construction of an artillery position. The model proposed in this paper derived the optimal solution for the small size problems, but it takes a long time to derive the optimal solution for the problem of equipment placement of the engineer battalion and brigade scale. Although the heuristic suggested in this study does not guarantee the optimal solution, the solution could be obtained in a reasonable amount of time.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.234-241
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• 2021

By recognizing the importance of demand forecasting, the military is conducting many studies to improve the prediction accuracy for repair parts. Demand forecasting for repair parts is becoming a very important factor in budgeting and equipment availability. On the other hand, the demand for intermittent repair parts that have not constant sizes and intervals with the time series model currently used in the military is difficult to predict. This paper proposes a method to improve the prediction accuracy for intermittent repair parts of the Patriot. The authors collected intermittent repair parts data by classifying the demand types of 701 repair parts from 2013 to 2019. The temperature and operating time identified as external factors that can affect the failure were selected as input variables. The prediction accuracy was measured using both time series models and data mining models. As a result, the prediction accuracy of the data mining models was higher than that of the time series models, and the multilayer perceptron model showed the best performance.