• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.429-438
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• 2021

Owing to the development of science technology, particularly the smart concept and defense policy factors of the 4th industry, military weapon systems are advanced, and the scientific and operational force is reduced dramatically. The aspect of the future war is characterized by the operation of troops with reduced forces from advanced and scientific weapon systems in an operational area that has expanded more than four times compared to the present. Reflecting on these situational factors, it is necessary to improve combat methods based on the changes in the battlefield environment and advanced weapon systems. In this study, to find a more efficient future combat method in a changing war pattern, this study applied the battle experiment methodology using Vision21 war game model, which is an analytical model used by the army. Finally, this study aimed to verify the future combat method and unit structure. Therefore, the scenario composition and experiment method that reflect the change in the ground operational environment and weapon system was first composed. Subsequently, an analysis method based on the combat effectiveness was applied to verify the effective combat performance method and unit structure of future infantry units.

• The Korean Journal of Applied Statistics
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• v.33 no.6
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• pp.753-762
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• 2020

With an increasing interest in integrating artificial intelligence (AI) into interview processes, the Republic of Korea (ROK) army is trying to lead and analyze AI-powered interview platform. This study is to analyze the AI interview data using a unified non-crossing multiple quantile tree (UNQRT) model. Compared to the UNQRT, the existing models, such as quantile regression and quantile regression tree model (QRT), are inadequate for the analysis of AI interview data. Specially, the linearity assumption of the quantile regression is overly strong for the aforementioned application. While the QRT model seems to be applicable by relaxing the linearity assumption, it suffers from crossing problems among estimated quantile functions and leads to an uninterpretable model. The UNQRT circumvents the crossing problem of quantile functions by simultaneously estimating multiple quantile functions with a non-crossing constraint and is robust from extreme quantiles. Furthermore, the single tree construction from the UNQRT leads to an interpretable model compared to the QRT model. In this study, by using the UNQRT, we explored the relationship between the results of the Army AI interview system and the existing personnel data to derive meaningful results.

• Journal of the Korean Society for Library and Information Science
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• v.55 no.1
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• pp.619-644
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• 2021

This study is to collect and organize the writings and related materials of Lee Jae Wook, the first director of Korea National Library, and, therefore, find out his achievements in the library system. By comparing existing and newly collected lists of Lee's writings, the total lists had been revised and complemented. As a result, the lists were finalized with 190 writings which were published on books, library journals, cultural magazines and various newspapers. In consequence of analyzing the writing-lists with historical records, Lee's accomplishments are as follows: First, he find philological and bibliographical value in Korean books and writings by studying classic literature. Second, he played an important role in grafting theory and practice of modern library into Korea in Japanese colonial era. Third, he made an effort to diffuse reading culture all around Korea through column and essays he published. Fourth, he contributed to make status and fundamental of early National Library with pioneering leadership by solving a problem of transferring National Library's legislation books that U.S. Military Government Office requested and founding Chosun Library School. Fifth, he implemented the core business of environment of Korean Library such as library class, establishment and implementation of Reading Week, foreign cooperation and etc., as a president of Chosun Library Association.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.477-483
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• 2021

In a military maintenance system, the standard maintenance man-hour of weapon systems is a tool to estimate the maintenance capabilities of maintenance units, provide standards for determining the maintenance needs and workload, and provide basic data for establishing a maintenance plan. The standard maintenance man-hours of major weapon systems have already been derived and used, but the standard maintenance man-hour in a wartime maintenance environment has not been computed. Therefore, the standard wartime maintenance man-hours need to be derived and This study proposes a process and method of computing the maintenance man-hours. In addition, this work suggests the criteria of collecting and screening data that is necessary for estimating the standard maintenance man-hours and introduces a methodology for analyzing the characteristics of maintenance man-hour distribution in the process. The proposed process first designs a model that reflects the wartime maintenance environment, selects statistical techniques, collects maintenance data, analyzes the descriptive statistics, estimates the distribution, and finally presents representative values of maintenance man-hour. Based on the proposed method, the standard wartime maintenance man-hours of the four weapon systems were calculated, and the distribution of the maintenance man-hours was analyzed to follow a lognormal distribution, and the method presented reliable results.

• Journal of the Korea Society for Simulation
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• v.31 no.1
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• pp.11-18
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• 2022

Recently, research to classify human activity using imagery has been actively conducted for the purpose of crime prevention and facility safety in public places and facilities. In order to improve the performance of human activity classification, most studies have applied deep learning based-transfer learning. However, despite the increase in the number of backbone network models that are the basis of deep learning as well as the diversification of architectures, research on finding a backbone network model suitable for the purpose of operation is insufficient due to the atmosphere of using a certain model. Thus, this study applies the transfer learning into recently developed deep learning backborn network models to build an intelligent system that classifies human activity using imagery. For this, 12 types of active and high-contact human activities based on sports, not basic human behaviors, were determined and 7,200 images were collected. After 20 epochs of transfer learning were equally applied to five backbone network models, we quantitatively analyzed them to find the best backbone network model for human activity classification in terms of learning process and resultant performance. As a result, XceptionNet model demonstrated 0.99 and 0.91 in training and validation accuracy, 0.96 and 0.91 in Top 2 accuracy and average precision, 1,566 sec in train process time and 260.4MB in model memory size. It was confirmed that the performance of XceptionNet was higher than that of other models.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.225-227
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• 2022

Now In Seoul, about 75,000 CCTVs are installed in 25 district offices. Each ward office in Seoul has built a control center for CCTV control and is building information such as people, vehicle types, license plate recognition and color classification into big data through 24-hour artificial intelligence intelligent image analysis. Seoul Metropolitan Government has signed MOUs with the Ministry of Land, Infrastructure and Transport, the National Police Agency, the Fire Service, the Ministry of Justice, and the military base to enable rapid response to emergency/emergency situations. In other words, we are building a smart city that is safe and can prevent disasters by providing CCTV images of each ward office. In this paper, the CCTV image is designed to extract the characteristics of the vehicle and personnel when an incident occurs through artificial intelligence, and based on this, predict the escape route and enable continuous tracking. It is designed so that the AI automatically selects and displays the CCTV image of the route. It is designed to expand the smart city integration platform by providing image information and extracted information to the adjacent ward office when the escape route of a person or vehicle related to an incident is expected to an area other than the relevant jurisdiction. This paper will contribute as basic data to the development of smart city integrated platform research.

• Journal of Space Technology and Applications
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• v.3 no.2
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• pp.165-198
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• 2023

According to the studies recently published through advanced maui optical and space surveillance technologies (AMOS) Conference 2021, LEO conjunction assessment revolves around not on operating satellites but space debris such as rocket bodies and non-operational satellites, hence suggesting a solution through space traffic management. Against this backdrop, the issue of active debris removal (ADR) has emerged to the surface as an international challenge throughout the globe. In step with this, the United Nations General Assembly approved a resolution calling on nations to halt tests of direct-ascent anti-satellites, to which U.S. and twelve other nations included Republic of Korea were original signatories. ADR techniques are also actively being researched in the civil sector, and these commercial services, if successfully developed, could possibly be utilized for military use as well. As such, this paper will help readers' understanding for the current status of ADR techniques, space threat assessments, on-orbit rendezvous and proximity operations by looking at previous cases, reflecting on space-faring nations' ADR techniques and its development probability in relation to space weapons. As a conclusion, this study will propose the needs of developing space propulsion system by understanding Space Maneuver Warfare in preparation for the future space battlefield.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.127-135
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• 2023

With the development of information and communication technology, the amount of information produced and shared in the battlefield and stored and managed in the system dramatically increased. This means that the amount of information which cansupport situational awareness and decision making of the commanders has increased, but on the other hand, it is also a factor that hinders rapid decision making by increasing the information overload on the commanders. To overcome this limitation, this study proposes a method to automatically search, select, and summarize documents that can help the commanders to understand the battlefield situation reports that he or she received. First, named entities are discovered from the battlefield situation report using a named entity recognition method. Second, the documents related to each named entity are discovered. Third, a language model and collaborative filtering are used to select the documents. At this time, the language model is used to calculate the similarity between the received report and the discovered documents, and collaborative filtering is used to reflect the commander's document reading history. Finally, sentences containing each named entity are selected from the documents and sorted. The experiment was carried out using academic papers since their characteristics are similar to military documents, and the validity of the proposed method was verified.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.137-144
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• 2023

Cyberattack technology is evolving to an unpredictable degree, and it is a situation that can happen 'at any time' rather than 'someday'. Infrastructure that is becoming hyper-connected and global due to cloud computing and the Internet of Things is an environment where cyberattacks can be more damaging than ever, and cyberattacks are still ongoing. Even if damage occurs due to external influences such as cyberattacks or natural disasters, intelligent self-recovery must evolve from a cyber resilience perspective to minimize downtime of cyber assets (OS, WEB, WAS, DB). In this paper, we propose an intelligent self-recovery technology to ensure sustainable cyber resilience when cyber assets fail to function properly due to a cyberattack. The original and updated history of cyber assets is managed in real-time using timeslot design and snapshot backup technology. It is necessary to secure technology that can automatically detect damage situations in conjunction with a commercialized file integrity monitoring program and minimize downtime of cyber assets by analyzing the correlation of backup data to damaged files on an intelligent basis to self-recover to an optimal state. In the future, we plan to research a pilot system that applies the unique functions of self-recovery technology and an operating model that can learn and analyze self-recovery strategies appropriate for cyber assets in damaged states.

• Journal of the Korean Society of Systems Engineering
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• v.20 no.spc1
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• pp.12-29
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• 2024

The purpose of this study is to identify the social issues discussed in Korea regarding Maritime Autonomous Surface Ships (MASS), the most advanced ICT field in the shipbuilding industry, and to suggest policy implications. In recent years, it has become important to reflect social issues of public interest in the policymaking process. For this reason, an increasing number of studies use media data and social media to identify public opinion. In this study, we collected 2,843 domestic media articles related to MASS from 2017 to 2022, when MASS was officially discussed at the International Maritime Organization, and analyzed them using text mining techniques. Through term frequency-inverse document frequency (TF-IDF) analysis, major keywords such as 'shipbuilding,' 'shipping,' 'US,' and 'HD Hyundai' were derived. For LDA topic modeling, we selected eight topics with the highest coherence score (-2.2) and analyzed the main news for each topic. According to the combined analysis of five years, the topics '1. Technology integration of the shipbuilding industry' and '3. Shipping industry in the post-COVID-19 era' received the most media attention, each accounting for 16%. Conversely, the topic '5. MASS pilotage areas' received the least media attention, accounting for 8 percent. Based on the results of the study, the implications for policy, society, and international security are as follows. First, from a policy perspective, the government should consider the current situation of each industry sector and introduce MASS in stages and carefully, as they will affect the shipbuilding, port, and shipping industries, and a radical introduction may cause various adverse effects. Second, from a social perspective, while the positive aspects of MASS are often reported, there are also negative issues such as cybersecurity issues and the loss of seafarer jobs, which require institutional development and strategic commercialization timing. Third, from a security perspective, MASS are expected to change the paradigm of future maritime warfare, and South Korea is promoting the construction of a maritime unmanned system-based power, but it emphasizes the need for a clear plan and military leadership to secure and develop the technology. This study has academic and policy implications by shedding light on the multidimensional political and social issues of MASS through news data analysis, and suggesting implications from national, regional, strategic, and security perspectives beyond legal and institutional discussions.