• Journal of Internet Computing and Services
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• v.21 no.1
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• pp.237-246
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• 2020

this paper, a data modeling method based on decision-making conditions is proposed for making combat and battlefield management systems to be intelligent, which are also a decision-making support system. A picture of a robot seeing and perceiving like humans and arriving a point it wanted can be understood and be felt in body. However, we can't find an example of implementing a decision-making which is the most important element in human cognitive action. Although the agent arrives at a designated office instead of human, it doesn't support a decision of whether raising the market price is appropriate or doing a counter-attack is smart. After we reviewed a current situation and problem in control & command of military, in order to collect a big data for making a machine staff's advice to be possible, we propose a data modeling prototype based on decision-making conditions as a method to change a current control & command system. In addition, a decision-making tree method is applied as an example of the decision making that the reformed control & command system equipped with the proposed data modeling will do. This paper can contribute in giving us an insight of how a future AI decision-making staff approaches to us.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.07a
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• pp.5-6
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• 2019

본 논문에서는 데이터 기반 정보 고도화를 통해, 사격전술지휘 의사결정체계의 Assisted Decision-Maker인 AI 부전포대장을 구현하는 방법론을 제시한다. 전포대장은 지휘결심의 말단에 있는 지휘관으로서, 최종적인 의사결정자이다. 이들의 지휘결심이 보다 견고하고 신속하게 이루어지도록 하는 것이 전쟁 승패에 매우 중요한 요소이다. 화력체계를 언급하는 경우 JMEM 탄약효과가 자주 언급되고 한국형 구축 사업이 아직 진행 중이기도 하지만, 완료되더라도 임의의 지형과 전술상황 각각에 대한 유용성까지를 입증하는 데에는 또 다른 기간과 노력이 요구된다. 본고에서는 AI 플랫폼 구축의 실제 사례가 전무한 상황에서 AI 부전포대장 구축을 위해 필요한 연구의 범위와 그 대상을 살펴보고, 지능형 사격지휘체계의 구축 방안을 제안한다.

• Journal of the Korea Society of Computer and Information
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• v.18 no.3
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• pp.79-89
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• 2013

ATCIS (Army Tactical Command Information System) provides commanders and staff officers the battlefield information that is reported by tactical echelons under an army corps and the commanders make decisions based on the information by using their experience and specialty in military domain. If ATICS can automatically understand the reported information from rapidly changing battlefield and provide new knowledge that can support decision making, the commanders would be able to make faster and more accurate decision. In this paper, therefore, we propose an intelligent ATCIS using a national defense ontology. To this end, we built the national defense ontology by analyzing the electronic field manuals and ATCIS database, and then we defined military knowledge for decision making as a form of rule by interviewing several staff officers from different fields. In order to show how to apply the ontology and rules to decision making support for the commanders, we implemented a decision support service to estimate the possibility of enemy's provocation by using semantic web technologies.

• The Journal of the Korea Contents Association
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• v.17 no.4
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• pp.384-394
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• 2017

Cessation and re smoking is recursive and addictive behaviors. Understanding differences in awareness of smokers and nonsmokers is fundamental to devise smoking policies. Research is focused on male adult's choices of educators and motivation level by personal attributes and awareness. There was a difference in awareness of smoking policies between smokers and nonsmokers. Community health centers and physicians were preferred for antismoking educator but not different between smokers and nonsmokers. Motivational levels of cessation in pictures of lung cancer, dental therapy, cigarette taxation, smoking area restriction and social marketing were statistically significant. The results indicate that male adult smokers are Motivated to quit smoking by those five contributors[P=.000].

• Proceedings of the Korean Information Science Society Conference
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• 2012.06b
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• pp.66-68
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• 2012

적의 주타격 방향은 적 지휘관의 주요 결정사항 중에 하나이다. 이런 적의 주타격 방향에 영향을 미치는 요소들을 분석하여 예측할 수 있다면 전쟁에서 좀 더 유리한 여건을 조성할 수 있을 것이다. 그러나 현재 군에서는 과학적 분석방법이 아닌 분석관 및 지휘관의 경험에 의한 적 주타격 방향 분석이 주를 이루고 있다. 따라서 본 논문에서는 데이터 마이닝의 대표적 방법인 의사결정트리의 C4.5 알고리즘을 사용하여 북한군의 지휘관 결심지도를 분석하였다. 또한 도출된 분류 규칙을 통해 적 주타격 방향 영향요소를 식별하고 영향요소들 간의 관계 및 정도의 수준을 예측하였다. 분석결과 현재 군에서 사용하고 있는 정보와 유사하고 의미 있는 정보를 도출할 수 있었다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.4
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• pp.610-615
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• 2002

Being a medium to help understand the status of the whole body including the Five Vital Organs and the Six Viscera such as the heart, the mac is considered to represent the elasticity of the blood vessel and the condition of the bloodstream in the Oriental medicine. A doctor makes a subjective judgment on a patient's conditions based on the information derived from the diagnosis and the medical examination of the mac wave. Thus he or she needs objective records and make a decision based on them in order to prevent misdiagnosis. This paper set out to suggest the ways to detect the particular parameters of the mac wave with the methods to visualize the mac wave interpretation to detect basic documents(causes) of health status judgment in three-dimension and with the simulation.

• 한국벤처창업학회:학술대회논문집
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• 2022.11a
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• pp.167-173
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• 2022

임팩트투자는 재무적인 수익과 더불어 사회에 긍정적인 영향을 만들고자 하는 의도를 가진 기업, 조직, 펀드를 대상으로 하는 투자 방식으로서 사회적 문제를 해결하기 위해 혁신적인 기술과 아이디어를 기잔 소셜벤처 기업에 재무적 지원을 위한 초기단계 투자로서 많은 관심을 받고 있다. 임팩트투자자는 재무적 수익과 사회적 가치추구라는 이중적인 판단 요인 때문에 사회적가치지표(SVI: Social Value Index)를 투자판단에 참고로 활용하고 있으나 투자를 결심하는 판단요인에 있어서는 여전히 개인의 경험과 주관적인 판단에 의존하고 있는 실정이다. 본 연구를 통하여 임팩트투자자가 복합적으로 고려하는 투자판단 요인들에 대한 타당도와 상대적 가중치를 객관화 하고, 재무적 수익과 사회적 가치의 이중적이 가치판단 중에서 어느 쪽을 더 주요하게 고민하는 지에 대하여 분석하였다. 본 연구는 판단분석기법을 활용하였으며 '임팩트투자자의 소셜벤처 투자결정에 대한 종합적인 평가'를 판단문제로 정의하고, 임팩트투자자의 투자의사결정 요인을 도출하기 위하여 투자자로서 재무적 이익과 회수 가능성 판단을 위한 ①초기투자단계에서의 투자의사결정 요인, 사회에 미치는 영향과 파급력, 소셜벤처의 상생과 연대를 위한 ②창업가(팀)의 정치적 기술, 임팩트투자펀드 조성 목적에 부합하는 ③소셜벤처기업의 소셜미션 등 세가지의 분류로 구성하여 연구를 진행하였다.

• Convergence Security Journal
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• v.21 no.4
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• pp.41-48
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• 2021

Recently, the aspect of war is evolving due to the 4th industrial revolution technology. Among them, AI technology is changing the way of war as it is applied to advanced weapon systems and decision-making systems. Mosaic Warfare, presented by the U.S. DARPA, is shifting military warfare from attrition-centric warfare to decision-centric warfare by combining Internet of Things, cloud computing, big data, mobile, and artificial intelligence technologies. In addition, it is a method to perform operations quickly so that the most offensive effect can be achieved by appropriately combining the distributed and deployed forces according to the battlefield context. In other words, military operations are not carried out through a uniform combat process, but various forces are operated through a distributed system depending on the battlefield context. In cyber warfare, as artificial intelligence is applied to cyber attack technology, there is a limit to responding with the same procedural response method as the existing cyber kill chain. Therefore, in this paper, the execution method of mosaic warfare is applied to perform context-resilient cyber operations that can operate a response system according to the attack and cyberspace context.

• Journal of Korean Home Economics Education Association
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• v.18 no.1 s.39
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• pp.31-47
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• 2006

This study developed practical reasoning teaching-learning material for middle school home economics education and tested its effects on middle school students' self-esteem The type of this study was a quasi-experimental research and its independent variable was practical reasoning instruction and its dependent variable was self-esteem. The research design for this study was a pretest-posttest design. Practical reasoning instruction was given for experimental group whereas traditional instruction was given to comparison group. For measuring self-esteem, 'self-esteem scale' developed by Choi & Jun(1993) was used and its Cronbach'a was ranged from .69 to .84. Statistic analysis was done by mean and standard deviation for general characteristics of samples and paired t-test for testing difference of pretest-posttest. The results of this study showed that practical reasoning instruction improved middles school students' self-esteem, the general self-esteem and social self-esteem among sub-areas of self-esteem in particular.

• Journal of the Korea Society for Simulation
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• v.29 no.1
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• pp.47-55
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• 2020

This paper presents a real-time autonomous computation of shot numbers and aiming points against multiple soft targets on grounds by applying an unsupervised learning, k-mean clustering and Monte carlo simulation. For this computation, a 100 × 200 square meters size of virtual battlefield is created where an augmented enemy infantry platoon unit attacks, defences, and is scatted, and a virtual weapon with a lethal range of 15m is modeled. In order to determine damage types of the enemy unit: no damage, light wound, heavy wound and death, Monte carlo simulation is performed to apply the Carlton damage function for the damage effect of the soft targets. In addition, in order to achieve the damage effectiveness of the enemy units in line with the commander's intention, the optimal shot numbers and aiming point locations are calculated in less than 0.4 seconds by applying the k-mean clustering and repetitive Monte carlo simulation. It is hoped that this study will help to develop a system that reduces the decision time for 'detection-decision-shoot' process in battalion-scaled combat units operating Dronebot combat system.