• The Transactions of the Korea Information Processing Society
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• v.6 no.8
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• pp.2020-2030
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• 1999

Data acquired about 53 gigabyte per a naval vessel is massive, expensive and impossible to be retested in a underwater acoustic measurement. So, it is required to manage systematically. In this paper, we mention MUADS (Massive Underwater Acoustic Database System) that was developed to store a long time, manage systematically and supply raw data and analyzed data. we analyze client/server performance based on 6003 input data individually in our MUADS that Unix server having a massive DC-jukebox and Windows clients.

• The Journal of Society for e-Business Studies
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• v.3 no.1
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• pp.43-67
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• 1998

Logistics is by no means a new subject area. The concept of logistics goes way become more complex as technology advances, and logistics requirements have increased accordingly. In 1964, when ILS philosophy formally came into being, ILS was defined in general terms and did not describe what actions an ILS program should accomplish. ILS philosophy have been developed from 1964 through 1980. In 1982, United States Department of Defense formulated a new concept, CALS. CALS is the strategy that the US defense development to management the transition to integration and automated interchange in defense system engineering, manufacturing, and logistic support. Its goal is to use the inherent features of digitized data to revolutionize the function of data -gathering, data storage and data - transfer techologies associared with the development of defense systems. The Result will be systems that are cheaper, more reliable, and easier to maintain. To define CALS's character, the purpose of this papers compare two concepts - CALS and ILS. The elements of CALS consist of standads and EDI. The elements of ILS include LCC(Life Cycle Cost), LSA(Logistics Support Analysis), LSAR(Logistics Support Analysis Rcord), Aquisition Cycle.

• 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.

• IE interfaces
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• v.24 no.2
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• pp.128-138
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• 2011

This research proposes a resource allocation model of Data QC (Quality Control) activities using COQ (Cost of Quality). The model has been developed based on a series of research efforts such as COQ classifications, weight determination of Data QC activities, and an aggregation approach between COQ and Data QC activities. In the first stage of this research, COQ was divided into the four typical classifications (prevention costs, appraisal costs, internal failure costs and external failure costs) through the opinions from five professionals in Data QC. In the second stage, the weights of Data QC activities were elicited from the field professionals. An aggregation model between COQ and Data QC activities has been then proposed to help the practitioners make a resource allocation strategy. DEA (Data Envelopment Analysis) was utilized for locating efficient decision points. The proposed resource allocation model has been validated using the case of Korea national defense information system. This research is unique in that it applies the concept of COQ to the data management for the first time and that it demonstrates a possible contribution to a real world case for budget allocation of national defense information.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.4
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• pp.687-694
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• 2020

SDN and NFV are next-generation network technologies, and cloud, such as data centers, campuses, and large companies, has been established, or is actively applied by service-oriented communication companies. In particular, the Defense Integrated Data Center will be a prime example for military applications. In order for the Defense Integrated Data Center (DIDC) to become an intelligent center, it is accelerating the promotion of the "Smart Defense Integrated Data Center", which applied the latest information and communication technology (ICT). At the time of the establishment of DIDC, it plans to start building infrastructure such as cloud services at around 30% level, and expand D-Cloud to 75% through 'Cloud First'. In addition, the introduction of SDN/NFV will reduce the operation cost and manpower of DIDC, strengthen the ability to efficiently use information resources and cyber information protection systems, and increase flexibility and agility in using each system to improve efficiency in defense management in the future. Therefore, we will discuss the justification and expected effects of SDN/NFV introduction, focusing on DIDC.

• Proceedings of the KIEE Conference
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• 2006.07a
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• pp.173-174
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• 2006

The power infrastructure defense system monitor and control a power system with parameters of a power system such as voltage, phasor angle, frequency and power flow which are measured at the same instance. For this, synchronized phasor measurement based on the GPS(Global Positioning System) is necessary. PMU(Phasor Measurement Unit) measures synchrophasor and transmits it to the power infrastructure defense system. For this communication, IEEE H37.118 defines a communication message format and measurement concept and we extend the protocol to transmit disturbance data. The synchrophasor data can be sent at various rates and there are several options for phasor information sent in the synchrophasor message. In this paper, we develop software that simulate communication between the power infrastructure defense system and PMU to annalize the traffic.

• Journal of Korean Society for Quality Management
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• v.45 no.3
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• pp.309-326
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• 2017

Purpose: The purpose of this study is to propose useful idea and data by association analyzing MRA results of defense research and development. Methods: The collected data through the DTaQ MRA system are analyzed using three association analysis measurements. Results: The results of this study are as follows; some evaluation items are very highly associated according to confidence and lift. The result is also meaningful as contents of evaluation items. The result of this study suggests a direction for improvement of MRA system. Conclusion: Some evaluation items of MRA are meaningfully associated. Therefore, the result can support the improvement of MRA system.

• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.4
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• pp.426-434
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• 2020

This paper studies the impact of the maintenance time of anti-ship missile Harpoon on operational availability with real field data. The Harpoon maintenance simulation model is developed as a testbed for identifying the optimal inventory levels on operational availability. Using multiple linear regression analysis and integer programming, the optimal inventory levels of essential assemblies are suggested. Finally, the result of sensitivity analysis shows the quantitative impact of maintenance time on operational availability and inventory costs. The authors believe that this quantitative analysis can support policy decisions to decrease maintenance time of missiles.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.4
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• pp.253-259
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• 2017

Recent development in science and technology has modernized the weapon system of ROKN (Republic Of Korea Navy). Although the cost of purchasing, operating and maintaining the cutting-edge weapon systems has been increased significantly, the national defense expenditure is under a tight budget constraint. In order to maintain the availability of ships with low cost, we need accurate demand forecasts for spare parts. We attempted to find consumption pattern using data mining techniques. First we gathered a large amount of component consumption data through the DELIIS (Defense Logistics Intergrated Information System). Through data collection, we obtained 42 variables such as annual consumption quantity, ASL selection quantity, order-relase ratio. The objective variable is the quantity of spare parts purchased in f-year and MSE (Mean squared error) is used as the predictive power measure. To construct an optimal demand forecasting model, regression tree model, randomforest model, neural network model, and linear regression model were used as data mining techniques. The open software R was used for model construction. The results show that randomforest model is the best value of MSE. The important variables utilized in all models are consumption quantity, ASL selection quantity and order-release rate. The data related to the demand forecast of spare parts in the DELIIS was collected and the demand for the spare parts was estimated by using the data mining technique. Our approach shows improved performance in demand forecasting with higher accuracy then previous work. Also data mining can be used to identify variables that are related to demand forecasting.

• Journal of the Korea Institute of Military Science and Technology
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• v.22 no.1
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• pp.106-123
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• 2019

Demand for performance analysis is increasing for efficient use of limited budgets such as improving investment efficiency and strategic budget allocation in accordance with the continuous increase demand of R&D budget for developing advanced weapon systems in the future battlefields. In accordance with the Act on the Performance Evaluation and Performance Management of the National R&D Projects established in March 2006, the performance analysis has been conducted for the systematic management and utilization of the R&D project performance. It was recognized as a project to achieve self-defense through strengthening the weapons system development capability, however, efficiency evaluation of Defense R&D projects was not much emphasized. Research on the efficiency analysis of defense R&D projects has been conducted in recent years, but most studies focused on corporate efficiency and productivity of defense companies. In this study, we analyzed the three-stage performance of defence R&D projects based on the logical model using the data envelope analysis(DEA) model. We also analyzed performance analysis from various perspectives through R&D type, technology classification and performance model. This study is expected to help defense department improve defense R&D projects and make decision.