• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.58-61
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• 2022

As data is evaluated as a key asset for digital transformation, efficient and stable management of data, smooth sharing data, and provision of services using data are also required in the defense. To support this, the Korean military is laying the foundation for the Military Artificial Intelligence Platform which is a defense data management infrastructure. In this paper, we examine the data strategies and data platform promotion directions of Korea and major advanced groups, and we look for suggestion and present the direction of development of the Military Intelligent Platform. We are expected that it can contribute to the establishment of a safe and efficient defense data management infrastructure for the Korean military.

• The Journal of the Convergence on Culture Technology
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• v.10 no.4
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• pp.425-430
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• 2024

This paper analyzes the characteristics of various types of unmanned aerial vehicles (drones) for military use and how each type can be utilized in military operations. The scope of the study focuses on the structural features, advantages and disadvantages, and military application cases of fixed-wing, rotary-wing, hybrid, and swarm drones. It also discusses the development direction of drone technology, changes in military strategy, opportunities, and challenges. The results show that each type of drone plays a crucial role in various military operations such as reconnaissance, surveillance, strike, logistics, search, and rescue. With advancements in artificial intelligence, autonomous flight, and swarm technologies, the range of drone applications is expected to expand further. However, ensuring the safety and ethics of drone operations and establishing international norms have emerged as major challenges.

• 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.

• Journal of the military operations research society of Korea
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• v.22 no.1
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• pp.67-80
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• 1996

Artificial Intelligence(AI) techniques and Object-Oriented(OO) techniques contribute to the simulation modeling of the complex systems. AI techniques are suitable to model human reasoning in the simulation. While OO techniques have advantages of re-usability, maintainability and extendability of the software. Thus, in this paper, we design a knowledge-based object-oriented simulation model, particularly for the logistics analysis of military armor vehicles. The simulation model consists of three modules i.e., scenario, simulation mechanism, and inference engine. The model is designed within the OO paradigm and implemented by using the C++ language. An example case of using the model for the logistic analysis is included.

• Journal of National Security and Military Science
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• s.2
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• pp.285-314
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• 2004

The forms of current war are diversified over the pan-national industry. Among these, one kind of threats which has permeated the cyber space based on the advanced information technology causes a new type of war. C4ISR, the military IT revolution, as a integrated technology innovation of Command, Control, Communications, Computer, Intelligence, Surveillance and Reconnaissance suggests that the aspect of the future war hereafter is changing much. In this paper, we design the virtual decoy system and intrusion trace marking mechanism which can capture various attempts and evidence of intrusion by hackers in cyber space, trace the penetration path and protect a system. By the suggested technique, we can identify and traceback the traces of intrusion in cyber space, or take a legal action with the seized evidence.

• Electronics and Telecommunications Trends
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• v.34 no.4
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• pp.76-88
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• 2019

With advances in olfactory sensor technologies, the number of reports on various intelligent applications using multiple sensors (sensor arrays) are continuously increasing for fields such as medicine, environment, security, etc. For intelligent and point-of-care applications, it is not only important for the sensor technology to perform chemical or physical measurements rapidly and accurately, but it is also important for artificial intelligence technology to recognize and quantify specific chemicals or diagnose diseases such as lung cancer and diabetes. In particular, great advances in pattern recognition technologies, including deep learning algorithms, as well as sensor array technologies, are expected to enhance the potential of various types of olfactory intelligence applications, including early cancer diagnosis, drug seeking, military operations, and air pollution monitoring.

• Journal of the Korea Institute of Military Science and Technology
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• v.26 no.2
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• pp.197-204
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• 2023

The importance of each warfighting function for Army TIGER unit attack drones is measured using the AHP technique. As a result, the importance of attack drones is high in the order of maneuver, firepower, intelligence, command/control, protection, and operation sustainment, but the importance of maneuver, firepower, and intelligence are almost similar. In addition, it is analyzed that attack drones capable of carrying out day and night missions by being equipped with an EO/IR sensor and being commanded/controlled in conjunction with the C4I system to eliminate threats with small bombs or aircraft collisions is needed. Finally, based on the results of this study, a virtual battle scenario for attack drones is proposed.

• Acta Via Serica
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• v.8 no.1
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• pp.101-120
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• 2023

In March 1245, Pope Innocent IV authorized three missions to the Mongols, seeking information about this menace from the East and summoning Eastern Christian support against an anticipated Mongol onslaught. Only one of the missions, led by John of Plano Carpini, reached Mongolia-the first-known Western European party to reach East Asia by a land route. Traveling along the Silk Road's new "Grasslands Route," John and his companion Benedict reached the camp of Güyüg Khan, where they witnessed his installation as the Great Khan. Upon their return to the papal court in 1247, they delivered Güyüg's letter demanding the submission of the pope and all the West's princes. John also presented a detailed report on what he and Benedict had learned. A close reading of it reveals a master intelligence operative at work. In addition to presenting an overview of Mongol history and culture, Friar John's report provides detailed information on the Mongols' grand strategy, their military organization and armaments, and their battle tactics. Turning from intelligence gathering to military operations, he offered practical advice on how to meet and defeat the coming Mongol onslaught, an attack that, providentially for the West, never came. What did occur was a modest but significant migration of Western missionaries and merchants to East Asia in the century following this pioneering journey.

• Journal of the Korea Institute of Military Science and Technology
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• v.26 no.4
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• pp.352-360
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• 2023

Recently, AI pilots using reinforcement learning are developing to a level that is more flexible than rule-based methods and can replace human pilots. In this paper, a curriculum was used to help head-on combat with reinforcement learning. It is not easy to learn head-on with a reinforcement learning method without a curriculum, but in this paper, through the two circle-based head-on air combat learning technique, ownship gradually increase the difficulty and become good at head-on combat. On the two-circle, the ATA angle between the ownship and target gradually increased and the AA angle gradually decreased while learning was conducted. By performing reinforcement learning with and w/o curriculum, it was engaged with the rule-based model. And as the win ratio of the curriculum based model increased to close to 100 %, it was confirmed that the performance was superior.

• The Journal of Korea Robotics Society
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• v.18 no.4
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• pp.436-443
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• 2023

With the advancement of robot intelligence, the concept of man and unmanned teaming (MUM-T) has garnered considerable attention in military research. In this paper, we present a transformer-based architecture for predicting the health status of agents, with the help of multi-head attention mechanism to effectively capture the dynamic interaction between friendly and enemy forces. To this end, we first introduce a framework for generating a dataset of battlefield situations. These situations are simulated on a virtual simulator, allowing for a wide range of scenarios without any restrictions on the number of agents, their missions, or their actions. Then, we define the crucial elements for identifying the battlefield, with a specific emphasis on agents' status. The battlefield data is fed into the transformer architecture, with classification headers on top of the transformer encoding layers to categorize health status of agent. We conduct ablation tests to assess the significance of various factors in determining agents' health status in battlefield scenarios. We conduct 3-Fold corss validation and the experimental results demonstrate that our model achieves a prediction accuracy of over 98%. In addition, the performance of our model are compared with that of other models such as convolutional neural network (CNN) and multi layer perceptron (MLP), and the results establish the superiority of our model.