• Title/Summary/Keyword: National Defense Data

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A Big Data Analysis of Public Interest in Defense Reform 2.0 and Suggestions for Policy Completion

  • Kim, Tae Kyoung;Kang, Wonseok
    • Journal of East Asia Management
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    • v.4 no.1
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    • pp.1-22
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    • 2023
  • This study conducted a big data analysis study through text mining and semantic network analysis to explore the perception of defense reform 2.0. The collected data were analyzed with the top 70 keywords as the appropriate range for network visualization. Through word frequency analysis, connection centrality analysis, and an N-gram analysis, we identified issues that received much attention such as troop reduction, shortening of military service period, dismantling of the border area unit, and returning wartime operational control. In particular, the results of clustering words through CONCOR analysis showed that there was a great interest in pursuing the technical group, concerns about military capacity reduction, and reorganization of manpower structure. The results of the analysis through text mining techniques are as follows. First, it was found that there was a lack of awareness about measures to reinforce the reduced troops while receiving much attention to the reduction of troops in Defense Reform 2.0. Second, it was found that it is necessary to actively communicate with the local community due to the deconstruction and movement of the border area units, such as the decrease of the population of the region and the collapse of the local commercial area. Third, it was judged that it is necessary to show substantial results through the promotion of barracks culture and the defense industry, which showed that there was less interest than military structure and defense operation from the people and the introduction of active policies. Through this study, we analyzed the public's interest in defense reform 2.0, which is a representative defense policy, and suggested a plan to draw support for national policy.

Ratio Estimation of Indirect Cost Sector about Defense Companies by Statistic Technique (통계 기법에 의한 방산업체의 간접원가부문 비율 추정)

  • Lim, Hyeoncheol;Kim, Suhwan
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.40 no.4
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    • pp.246-252
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    • 2017
  • In the defense acquisition, a company's goal is to maximize profits, and the government's goal is to allocate budgets efficiently. Each year, the government estimates the ratio of indirect cost sector to defense companies, and estimates the ratio to be applied when calculating cost of the defense articles next year. The defense industry environment is changing rapidly, due to the increasing trend of defense acquisition budgets, the advancement of weapon systems, the effects of the 4th industrial revolution, and so on. As a result, the cost structure of defense companies is being diversifying. The purpose of this study is to find an alternative that can enhance the rationality of the current methodology for estimating the ratio of indirect cost sector of defense companies. To do this, we conducted data analysis using the R language on the cost data of defense companies over the past six years in the Defense Integrated Cost System. First, cluster analysis was conducted on the cost characteristics of defense companies. Then, we conducted a regression analysis of the relationship between direct and indirect costs for each cluster to see how much it reflects the cost structure of defense companies in direct labor cost-based indirect cost rate estimates. Lastly a new ratio prediction model based on regularized regression analysis was developed, applied to each cluster, and analyzed to compare performance with existing prediction models. According to the results of the study, it is necessary to estimate the indirect cost ratio based on the cost character group of defense companies, and the direct labor cost based indirect cost ratio estimation partially reflects the cost structure of defense companies. In addition, the current indirect cost ratio prediction method has a larger error than the new model.

Studies on the Operating Requirements of Multi-Resolution Modeling in Training War-Game Model and on the Solutions for Major Issues of Multi-Resolution Interoperation between Combat21 Model and TMPS (훈련용 워게임 모델의 다중해상도모델링 운영소요 및 전투21모델과 TMPS의 다중해상도 연동간 주요 이슈 해결 방안 연구)

  • Moon, Hoseok;Kim, Suhwan
    • Journal of the Korea Institute of Military Science and Technology
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    • v.21 no.6
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    • pp.865-876
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    • 2018
  • This study focuses on the operating requirements of multi-resolution modeling(MRM) in training war-game model and proposes solutions for major issues of multi-resolution interoperation between Combat21 model and tank multi-purpose simulator(TMPS). We study the operating requirements of MRM through interviews with defense M&S experts and literature surveys and report the various issues that could occur with low-resolution model Combat21 and high-resolution model TMPS linked, for example, when to switch objects, what information to exchange, what format to switch to, and how to match data resolutions. This study also addresses the purpose and concept of training using multi-resolution interoperation, role of each model included in multi-resolution interoperation, and issue of matching damage assessments when interoperated between models with different resolutions. This study will provide the common goals and directions of MRM research to MRM researchers, defense modeling & simulation organizations and practitioners.

Global Competitiveness Analysis of National Defense Industry - DEA and Malmquist Production Analysis- (국내 방위산업 글로벌 경쟁력 분석 -효율성 및 생산성 중심으로-)

  • Kim, Joon-Young;Hong, Jong-Yi
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.16 no.12
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    • pp.8378-8385
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    • 2015
  • The interest of global competitiveness for national defense industry. This study analyzes the efficiency and productivity of 45 defense companies in each continent(North America, Europe and Northeast Asia, etc.), including Korea defense companies. It is analyzed by Data Envelopment Analysis(DEA) and Malmquist Productivity Analysis over the period 2009-2013(5 years). The sample companies has been selected on the data avilability among the SIPRI Top 100 arms-producing and military services companies in the world(excluding China) in 2013. It extracts the relative efficiency and Malmquist productivity index of companies and each continent. Based on the DEA and MPI results, this paper estimates the global competitiveness and position of national defense industry and extracts implication. This study can be utilized for improvement of national defense industry and policy planning for cultivating the national defense companies.

A Study on the Strategic Application of National Defense Data for the Construction of Smart Forces in the 4th IR (4차 산업혁명시대 스마트 강군 건설을 위한 국방 데이터의 전략적 활용 방안연구)

  • Kim, Seyong;Kim, Junsang;Kang, Seokwon
    • Convergence Security Journal
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    • v.20 no.4
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    • pp.113-123
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    • 2020
  • The fourth industrial revolution can be called the hyper-connected-based intelligent revolution triggered by advanced information technology and intelligent technology, and the basis for implementing these technologies is 'data'. This study proposes a way to strategically use data in order to lead this intelligent revolution in the defense area. First of all, implications through analysis of domestic and international trends and prior research and current status of defense data management were analyzed, and four directions for development were presented. If the government composes conditions for building, releasing, sharing, distribution, and convergence of defense data considering the environment of national defense in the future, it is expected that it will serve as a foundation and a shortcut to be a digitalized strong military through smart defense innovation in the era of the fourth industrial revolution.

A Study on Forecasting Spare Parts Demand based on Data-Mining (데이터 마이닝 기반의 수리부속 수요예측 연구)

  • Kim, Jaedong;Lee, Hanjun
    • Journal of Internet Computing and Services
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    • v.18 no.1
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    • pp.121-129
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    • 2017
  • Demand forecasting is one of the most critical tasks in defense logistics, because the failure of the task can bring about a huge waste of budget. Up to date, ROK-MND(Republic of Korea - Ministry of National Defense) has analyzed past component consumption data with time-series techniques to predict each component's demand. However, the accuracy of the prediction still needs to be improved. In our study, we attempted to find consumption pattern using data mining techniques. We gathered an 18,476 component consumption data first, and then derived diverse features to utilize them in identification of demanding patterns in the consumption data. The results show that our approach improves demand forecasting with higher accuracy.

The Developing of Analytical Statistics System for the Efficiency of Defense Management (국방경영 효율화를 위한 분석형 통계시스템 구축)

  • Lee, Jung-Man
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.38 no.3
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    • pp.87-94
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    • 2015
  • Recently, management based on statistical data has become a big issue and the importance of the statistics has been emphasized for the management innovation in the defense area. However, the Military Management based on the statistics is hard to expect because of the shortage of the statistics in the military. There are many military information systems having great many data created in real time. Since the infrastructure for gathering data form the many systems and making statistics by using gathered data is not equipped, the usage of the statistics is poor in the military. The Analytical Defense Statistics System is designed to improve effectively the defense management in this study. The new system having the sub-systems of Data Management, Analysis and Service can gather the operational data from interlocked other Defense Operational Systems and produce Defense Statistics by using the gathered data beside providing statistics services. Additionally, the special function for the user oriented statistics production is added to make new statistics by handling many statistics and data. The Data Warehouse is considered to manage the data and Online Analytical Processing tool is used to enhance the efficiency of the data handling. The main functions of the R, which is a well-known analysis program, are considered for the statistical analysis. The Quality Management Technique is applied to find the fault from the data of the regular and irregular type. The new Statistics System will be the essence of the new technology like as Data Warehouse, Business Intelligence, Data Standardization and Statistics Analysis and will be helpful to improve the efficiency of the Military Management.

Selecting the Optimal Hidden Layer of Extreme Learning Machine Using Multiple Kernel Learning

  • Zhao, Wentao;Li, Pan;Liu, Qiang;Liu, Dan;Liu, Xinwang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.12
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    • pp.5765-5781
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    • 2018
  • Extreme learning machine (ELM) is emerging as a powerful machine learning method in a variety of application scenarios due to its promising advantages of high accuracy, fast learning speed and easy of implementation. However, how to select the optimal hidden layer of ELM is still an open question in the ELM community. Basically, the number of hidden layer nodes is a sensitive hyperparameter that significantly affects the performance of ELM. To address this challenging problem, we propose to adopt multiple kernel learning (MKL) to design a multi-hidden-layer-kernel ELM (MHLK-ELM). Specifically, we first integrate kernel functions with random feature mapping of ELM to design a hidden-layer-kernel ELM (HLK-ELM), which serves as the base of MHLK-ELM. Then, we utilize the MKL method to propose two versions of MHLK-ELMs, called sparse and non-sparse MHLK-ELMs. Both two types of MHLK-ELMs can effectively find out the optimal linear combination of multiple HLK-ELMs for different classification and regression problems. Experimental results on seven data sets, among which three data sets are relevant to classification and four ones are relevant to regression, demonstrate that the proposed MHLK-ELM achieves superior performance compared with conventional ELM and basic HLK-ELM.

A Development Technique of Core Architecture Data Model(CADM) for Defense Information Resource Management (국방 정보자원관리를 위한 핵심아키텍처데이터모델 개발 기법)

  • Choi, Nam-Yong;Jin, Jong-Hyeon;Song, Young-Jae
    • The KIPS Transactions:PartD
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    • v.11D no.3
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    • pp.683-690
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    • 2004
  • MND(Ministry of National Defense) has developed .nm AF(Ministry of National Defense Architecture Framework) to guarantee interoperability among defense information systems. Users can easily and consistently develop architecture products through MND AF. There is necessity for development if CADM(Core Architecture Data Model), which facilitate exchange, integration, and comparison for architecture data, to store architecture data from architecture products and reuse them. We developed CADM from defining entities and relationships that satisfy data requirement of each architecture product from MND AF. After we developed architecture products about MIMS(Military Intelligence Management System), and inserted these architecture data to CADM repository. we verified CADM entities and relationships through query. Through CABM which provides common data model for the whole my architectures, interoperability and integration among defense information systems ran be improved, and integrated defense information resources efficiently can be managed.

Utilization of Spatial Weather Information System for Effective Air Operations

  • Kim, Young-Hae;Yoon, Soungwoong;Lee, Sang-Hoon
    • Journal of the Korea Society of Computer and Information
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    • v.23 no.4
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    • pp.139-145
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    • 2018
  • In this paper, we propose the methodology and system to show weather information to spatial system. When using the spatial information system, it is easy and convenient to show information such as target location, mission contents, enemy threats and so on. However, drawing 1-dimensional weather information on 3-dimensional space in spatial information system is hard task. To fuse data, we need to add a spatial layer including weather information to spatial layers and perform space modeling for showing weather information as spatial data in a virtual space. The virtual space is shown by receiving meteorological data and then changing in real time through weather database linkage.