• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.37-53
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• 2023

The AI based intelligent command and control system can automatically analyzes the properties of intricate battlefield information and tactical data. In addition, commanders can receive situation analysis results and battlefield awareness through the system to support decision-making. It is necessary to build a battlefield situation analysis dataset similar to the actual battlefield situation for learning AI in order to provide decision-making support to commanders. In this paper, we explain the next step of the dataset construction method of the existing previous research, 'A Virtual Battlefield Situation Dataset Generation for Battlefield Analysis based on Artificial Intelligence'. We proposed a method to build the dataset required for the final battlefield situation analysis results to support the commander's decision-making and recognize the future battlefield. We developed 'Dataset Generator SW', a software tool to build a learning dataset for battlefield situation analysis, and used the SW tool to perform data labeling. The constructed dataset was input into the Siamese Network model. Then, the output results were inferred to verify the dataset construction method using a post-processing ranking algorithm.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.4
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• pp.9-20
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• 2011

Future warfare paradigm is changing to network-centric warfare and effects-based operations. In order to find first and strike the enemy in the battlefield, friendly unit requires real-time target acquisition, intelligence collection, accurate situation assessment, and timely decision. The rapid development in advanced sensor technology and wireless networks requires a significant change in operational concepts of the battlefield surveillance. In particular, the introduction of a battlefield surveillance sensor network system is a big challenge to the ground forces which have lack of automated information collection assets. Therefore this paper proposes an ontology-based context-aware framework for the battlefield surveillance sensor network system which is needed for early finding the enemy and visualizing the battlefield in the ground force operations. Compared with the performance of existing systems, the one of the proposed framework has shown highly positive results by applying the context systems evaluation method. The framework has also proven to be satisfactory by the structured evaluation method using device collaboration. Since the proposed ontology-based context-aware framework has a lot of advantages in terms of scalability and reusability, the ground force's reconnaissance and surveillance system can be widely applied to expand in the future. And, ontology-based model has some weak points such as ontology data size, processing time, and limitation of network bandwidth. However, these problems can be resolved by customizing properly to fit the mission and characteristics of the unit. Moreover, development of the next-generation communication infrastructure can expedite the intelligent surveillance and reconnaissance service and may be expected to contribute greatly to expanding the information capacity.

• 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 the Korea Society of Computer and Information
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• v.27 no.6
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• pp.33-42
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• 2022

In the existing intelligent command control system study, the analysis results of the commander's battlefield situation questions are provided from knowledge-based situation data. Analysis reporters write these results in various expressions of natural language. However, it is important to analyze situations about information and intelligence according to context. Analyzing the battlefield situation using artificial intelligence is necessary. We propose a virtual dataset generation method based on battlefield simulation scenarios in order to provide a dataset necessary for the battlefield situation analysis based on artificial intelligence. Dataset is generated after identifying battlefield knowledge elements in scenarios. When a candidate hypothesis is created, a unit hypothesis is automatically created. By combining unit hypotheses, similar identification hypothesis combinations are generated. An aggregation hypothesis is generated by grouping candidate hypotheses. Dataset generator SW implementation demonstrates that the proposed method can be generated the virtual battlefield situation dataset.

• Proceedings of the Korea Information Processing Society Conference
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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.

• Defense and Technology
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• no.5 s.291
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• pp.42-53
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• 2003

각 병사가 미래의 전장 디지털화 시스템에 링크될 때 전술 무전기의 사용이 최고조에 달할 것으로 예상된다. 미 육군은 디지털화 프로그램의 목표를 '말단 병사로부터 지휘관에 이르기까지 전장의 공통 영상을 생성하기 위해 수평 수직적으로 결합된 적시의 정보를 획득, 교환 및 이용하기 위한 기술의 적용'으로 정의한다. 전장 디지털화가 성공하면, 전투지역 내외의 모든 병사는 자신의 위치, 적 및 우군 부대의 위치, 또 이들 부대의 활동 상황을 알 수 있을 것으로 예상된다. 이와 같은 상황 인식이 이루어지면 상대적으로 소규모인 부대가 수적으로 많은 적 부대와 교전이 가능하고 격파도 가능해진다. 무기체계논단 중•장거리 방공시스템의

• Journal of the Korea Society of Computer and Information
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• v.28 no.1
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• pp.1-8
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• 2023

In this paper, we propose a training method of a recommendation learning model that analyzes the battlefield situation and recommends a suitable hypothesis for the current situation. The proposed learning model uses the preference determined by comparing the two hypotheses as a label data to learn which hypothesis best analyzes the current battlefield situation. Our model is based on Siamese neural network architecture which uses the same weights on two different input vectors. The model takes two hypotheses as an input, and learns the priority between two hypotheses while sharing the same weights in the twin network. In addition, a score is given to each hypothesis through the proposed post-processing ranking algorithm, and hypotheses with a high score can be recommended to the commander in charge.

• Journal of the Korea Society of Computer and Information
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• v.25 no.4
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• pp.11-17
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• 2020

In this paper, we propose a method to build a knowledge base based on natural language processing for intelligent battlefield awareness service. The current command and control system manages and utilizes the collected battlefield information and tactical data at a basic level such as registration, storage, and sharing, and information fusion and situation analysis by an analyst is performed. This is an analyst's temporal constraints and cognitive limitations, and generally only one interpretation is drawn, and biased thinking can be reflected. Therefore, it is essential to aware the battlefield situation of the command and control system and to establish the intellignet decision support system. To do this, it is necessary to build a knowledge base specialized in the command and control system and develop intelligent battlefield awareness services based on it. In this paper, among the entity names suggested in the exobrain corpus, which is the private data, the top 250 types of meaningful names were applied and the weapon system entity type was additionally identified to properly represent battlefield information. Based on this, we proposed a way to build a battlefield-aware knowledge base through mention extraction, cross-reference resolution, and relationship extraction.

• Defense and Technology
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• no.2 s.288
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• pp.50-59
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• 2003

전술$C^4I$체계가 전력화되어 작전반응이 더욱 빨라지고 획득한 정보가 필요한 부서와 제대에 모두 공유되고, 부대의 각종 자산을 충분히 활용 가능하며, 전장상황의 인식이 더욱 용이해지게 된다. 또한 전술$C^4I$체계 구축을 통해 미래 지상전장 운용개념인 "다차원 동시 통합전투"가 비로소 가능해진다. 이런 직접적인 효과 이외에도 군의 과학화 마인드를 확산시키며, 민간의 선진기술이 군에 적용되는 간접적인 효과가 있을 것이다. 우리 군이 현재 미래 전장환경과 주변국 위협에 대비하여 장거리 타격수단에 표적을 제공하기 위한 대부대용 UAV를 전력화하여 전천후 감시로 실시간 장거리 영상정보를 수집하고 있는 것은 획기적인 사실이다.

• Convergence Security Journal
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• v.20 no.4
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• pp.143-151
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• 2020

The cyber battlefield called the fifth battlefield, is not based on geological information unlike the existing traditional battlefiels in the land, sea, air and space, and has a characteristics that all information has tightly coupled correlation to be anlayized. Because the cyber battlefield has created by the network connection of computers located on the physical battlefield, it is not completely seperated from the geolocational information but it has dependency on network topology and software's vulnerabilities. Therefore, the analysis for cyber battlefield should be provided in a form that can recognize information from multiple domains at a glance, rather than a single geographical or logical aspect. In this paper, we describe a study on the development of the cyber operation COP(Common Operational Picture), which is essential for command and control in the cyber warfare. In particular, we propose an architecure for cyber operation COP to intuitively display information based on visualization techniques applying the multi-layering concept from multiple domains that need to be correlated such as cyber assets, threats, and missions. With this proposed cyber operation COP with multi-layered visualization that helps to describe correlated information among cyber factors, we expect the commanders actually perfcrm cyber command and control in the very complex and unclear cyber battlefield.