• The Korean Journal of Applied Statistics
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• v.32 no.1
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• pp.129-138
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• 2019

Ammunition is an integral element of a weapon systems and in calculating fighting strength. The Korea Army utilizes the basic load (B/L) concept to supply ammunition smoothly. The required supply rate (RSR) is the basis of a B/L that is estimated from real combat data that includes a troop's mission and operation terrain. The current RSR is based on Korean War data and the sample mean has some problems in applications to modern combat. Therefore, this study used Korea Combat Training Center (KCTC) data that is similar to real combat to estimate rifle ammunition RSR. We used a quantile of truncated Weibull distribution to estimate rifle ammunition RSR considering that rifle ammunition consumption data in KCTC is truncated. As a result, we obtained a rifle ammunition RSR which covers most ammunition consumption by reflecting the individual consumption of rifle ammunition.

• Journal of the Korea Society of Computer and Information
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• v.26 no.9
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• pp.97-104
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• 2021

Since 1993, Successfully localized naval combat System has made steady development on various domestic and foreign ships. On the other hand, Engineering Control System(ECS) is dependent on foreign companies. Therefore, there is a lot of interest and research in the localization of ECS in the navy defense industry. As one of various studies, a preliminary study of domestic ECS software that can be commonly applied to naval ships is in progress. This paper propose Ecs Obts Scalable Platform(EOSPA) as the standard architecture of ECS On-Board Training System(OBTS) software by applying object-oriented programming and standardization. And this introduces EOSPA's structure, function, and features of each component. Furthermore, high reusability and maintainability are expected in the development of ECS OBTS software applying EOSPA in various naval ships.

• Journal of Digital Contents Society
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• v.19 no.6
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• pp.1197-1205
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• 2018

In this paper, we perform Single Image Super Resolution(SISR) for acquired images of EOTS or IRST from naval combat system. In order to conduct super resolution, we use Generative Adversarial Networks(GANs), which consists of a generative model to create a super-resolution image from the given low-resolution image and a discriminative model to determine whether the generated super-resolution image is qualified as a high-resolution image by adjusting various learning parameters. The learning parameters consist of a crop size of input image, the depth of sub-pixel layer, and the types of training images. Regarding evaluation method, we apply not only general image quality metrics, but feature descriptor methods. As a result, a larger crop size, a deeper sub-pixel layer, and high-resolution training images yield good performance.

• Journal of the military operations research society of Korea
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• v.36 no.3
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• pp.83-93
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• 2010

In this paper, we propose a new expert system for close combat in military war game model for training. Simulation logic for damage assesment is one of the main simulation functions in military war game. In Changcho 21's model which is the war game model for Republic of Korea Army corps and division, the main function of close combat's damage assessment has not been calculated by Changcho 21's model, but by COBRA which was made by US Army and has been the expert system for close combat. Results which were calculated in COBRA were sent to Changcho 21's model through a cable network. And Changcho 21's model finally calculated the value of damage assessment with the results. In this paper, we develop an new expert system for close combat using decision tree. The experimental results show that the proposed expert system has similar performance to COBRA and has less computing complexity. And it can substitute for COBRA and be applicable to battlefield.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.1
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• pp.34-41
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• 2020

There has not been any scientific analysis on appropriate size of workforce and salary for civilian workers in military so far. Thus, this paper conducted analysis on propriety in employment size of military doctrine researchers using system dynamic methodology based on annual military doctrine workload. Vensim software was mainly used to measure complement of the research group based on data from job analysis. Secondly, a multiple regression analysis was performed to study an appropriate wage for researchers based on their expertise and working condition. The data from twenty public research institutions and twenty eight job positions that are performing similar duty with military doctrine researchers was obtained and utilized to create a salary-estimation regression equation in the analysis. Finally, with cost-benefit analysis method this paper studied financial effectiveness of hiring military doctrine researchers. Contingent valuation method, which has been recognized as one of the most effective methodologies in cost-benefit analysis on intangible value, was utilized to measure benefit of hiring the researchers. The methodology presented in this paper can be applied to measure and improve the efficiency of military organization not only in military doctrine research area but also in several military functional area (military training, logistics, administration, combat development, and combat support).

• Journal of the Korea Institute of Military Science and Technology
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• v.17 no.6
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• pp.773-785
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• 2014

For decades, modeling of pilots has been intensively studied due to its advantages in reducing costs for training and enhancing safety of pilots. In particular, research for modeling of pilots' non-kinetic behaviors which refer to the decisions made by pilots is beneficial as the expertise of pilots can be inherent in the models. With the recent growth in the amount of combat logs accumulated, employing statistical learning methods for the modeling becomes possible. However, the combat logs consist of heterogeneous data that are not only continuous or discrete but also sequence independent or dependent, making it difficult to directly applying the learning methods without modifications. Therefore, in this paper, we present a kernel function named hybrid sequence kernel which addresses the problem by using multiple kernel learning methods. Based on the empirical experiments by using combat logs obtained from a simulator, the proposed kernel showed satisfactory results.

• The Korean Journal of Applied Statistics
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• v.28 no.5
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• pp.921-932
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• 2015

This study analyzed military personnel survivability in regards to offensive operations according to the scientific military training data of a reinforced infantry battalion. Scientific battle training was conducted at the Korea Combat Training Center (KCTC) training facility and utilized scientific military training equipment that included MILES and the main exercise control system. The training audience freely engaged an OPFOR who is an expert at tactics and weapon systems. It provides a statistical analysis of data in regards to state-of-the-art military training because the scientific battle training system saves and utilizes all training zone data for analysis and after action review as well as offers training control during the training period. The methodologies used the Cox PH modeling (which does not require parametric distribution assumptions) and decision tree modeling for survival data such as CART, GUIDE, and CTREE for richer and easier interpretation. The variables that violate the PH assumption were stratified and analyzed. Since the Cox PH model result was not easy to interpret the period of service, additional interpretation was attempted through univariate local regression. CART, GUIDE, and CTREE formed different tree models which allow for various interpretations.

• Journal of the Korean Society of Physical Medicine
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• v.15 no.3
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• pp.61-68
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• 2020

PURPOSE: The purpose of this study was to investigate the current state of rapid weight loss and physical and mental complaints among elite combat athletes who were selected and trained as national representatives. METHODS: A total of 127 combat athletes who had trained at the national training center in 2019 were enrolled. The questionnaire used as the survey tool was interpreted as words that Korean athletes could easily understand based on the Portuguese version of the 'Rapid Weight Loss Questionnaire' (RWLQ). χ² tests was performed to determine the differences in physical and mental changes according to sports and weight loss method. RESULTS: Combat athletes in Korea regularly undergo rapidly weight loss within a short period of time prior to competition. There were statistically similar results in terms of weight loss method, physical and mental changes and information about weight loss according to the sport. Weight loss methods often limit food and water intake and dehydrate. The physical complaints associated with them are symptoms such as "no energy", "dizziness", and "muscle spasms". The mental complaints include "irritability", "concentration loss" and "anxiety". These symptoms can be caused by side effects such as food intake limitation, water restriction and dehydration. Information sources for weight loss were in the order of "senior or colleagues", "supervisor or coach", and "Internet". No information was obtained from a doctor or dietitian. CONCLUSION: These results provide a baseline for predicting proper weight loss in athletes and provide useful information for developing performance enhancement as well as weight loss.

• Journal of National Security and Military Science
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• s.2
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• pp.121-163
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• 2004

Science technique development expanded into, not only land, sea, and air operations but also those of airspace, and cyber battle spaces. It is generally accepted at this time that space centric operations currently cannot be effectively divided from air operations. However, science and technology advancements make it possible to integrate Army, Navy, Airforce, and Marine forces into effective operations as never before. The Republic of Korea Armed Forces needs to establish a more effective joint concept. The US military, considered by many experts as the most effective in the world, understands the necessity of joint operations and accordingly has highly developed its own concept of joint operations. The US joint operational concepts demonstrated their effectiveness during the Iraqi War by dominating the battlefield through effective use of all combat and non-combat power. Following the US Iraqi War experience, the US Department of Defense continued to enhance Joint Capability through the acceleration of US Military Transformation involving all components. The future national security of the Republic of Korea, faced with the peculiarity of communist threat in the form of North Korea, and the conflicting interest of four strong powers; the United States, China, Japan, and Russia, depends on small but strong armed forces employing all available combat power through effective National and Military Strategy, and considering domestic and international constraints. In order to succeed in future wars, military operations following joint operational concepts must effectively employ all available combat power in a timely manner. The Republic of Korea Armed Forces must establish a joint forces concept in order to integrate all available combat power during employment. Therefore we must establish military operations that develop the military structure and organization, doctrine, weapon systems, training and education of our armed forces based on the key concept of joint operations.

• Journal of Intelligence and Information Systems
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• v.14 no.3
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• pp.25-39
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• 2008

The objective of this study is to forecast the operational continuous ability using Artificial Neural Networks in battalion defensive operation for the commander decision making support. The forecasting of the combat result is one of the most complex issue in military science. However, it is difficult to formulate a mathematical model to evaluate the combat power of a battalion in defensive operation since there are so many parameters and high temporal and spatial variability among variables. So in this study, we used company combat power level data in Battalion Command in Battle Training as input data and used Feed-Forward Multilayer Perceptrons(MLP) and General Regression Neural Network (GRNN) to evaluate operational continuous ability. The results show 82.62%, 85.48% of forecasting ability in spite of non-linear interactions among variables. We think that GRNN is a suitable technique for real-time commander's decision making and evaluation of the commitment priority of troops in reserve.