• Title/Summary/Keyword: 국방 AI

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A Study on the Effective Command Delivery of Commanders Using Speech Recognition Technology (국방 분야에서 전장 소음 환경 하에 음성 인식 기술 연구)

  • Yeong-hoon Kim;Hyun Kwon
    • Convergence Security Journal
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    • v.24 no.2
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    • pp.161-165
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    • 2024
  • Recently, speech recognition models have been advancing, accompanied by the development of various speech processing technologies to obtain high-quality data. In the defense sector, efforts are being made to integrate technologies that effectively remove noise from speech data in noisy battlefield situations and enable efficient speech recognition. This paper proposes a method for effective speech recognition in the midst of diverse noise in a battlefield scenario, allowing commanders to convey orders. The proposed method involves noise removal from noisy speech followed by text conversion using OpenAI's Whisper model. Experimental results show that the proposed method reduces the Character Error Rate (CER) by 6.17% compared to the existing method that does not remove noise. Additionally, potential applications of the proposed method in the defense are discussed.

Efficacy analysis for the Radar-based Artificial Intelligence (AI) Scientific Guard System based on AHP (AHP를 활용한 레이더 기반 AI 과학화 경계시스템 효과 분석)

  • Minam Moon;Kyuyong Shin;Hochan Lee;Seunghyun Gwak
    • Convergence Security Journal
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    • v.22 no.5
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    • pp.135-143
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    • 2022
  • The defense environment is rapidly changing, such as nuclear and missile threats of North Korea, changes in war patterns, and a decrease in military service resources due to low birth rate. In order to actively respond to these changes, the Korean military is promoting Defense Innovation 4.0 and is trying to foster an army armed with high technology such as artificial intelligence (AI), big data analysis, etc. In this regard, we analyze the effectiveness of the radar-based AI scientific guard system applied by high technology for guard operations using Analytic Hierarchy Process (AHP). We first select evaluation factors that can assess the effectiveness of the scientific guard system, and analyze its relative importance. Each evaluation factor was selected by deriving a significant concept from operating principle and how they work, and by consulting experts on the correlation between each factor and effectiveness of the scientific guard system. We examine the relative effects of the radar-based AI scientific guard system and existing scientific guard system based on the importance of the evaluation factors.

The AI Promotion Strategy of Korea Defense for the AI Expansion in Defense Domain (국방분야 인공지능 저변화를 위한 대한민국 국방 인공지능 추진전략)

  • Lee, Seung-Mok;Kim, Young-Gon;An, Kyung-Soo
    • Journal of Software Assessment and Valuation
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    • v.17 no.2
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    • pp.59-73
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    • 2021
  • Recently, artificial intelligence has spread rapidly and popularized and expanded to the voice recognition personal service sector, and major countries have established artificial intelligence promotion strategies, but in the case of South Korea's defense domain, its influence is low with a geopolitical location with North Korea. This paper presents a total of six strategies for promoting South Korea's defense artificial intelligence, including establishing roadmaps, securing manpower, installing the artificial intelligence base, and strengthening cooperation among stakeholders in order to increase the impact of South Korea's defense artificial intelligence and successfully promote artificial intelligence. These suggestions are expected to establish the foundation for expanding the base of artificial intelligence.

A Study on the Improvement of Weapon System T&E performance System (국방 무기체계 시험평가 수행체계 개선방안 연구)

  • BaekJung Kim;Sukjae Jeong
    • Journal of The Korean Institute of Defense Technology
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    • v.5 no.2
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    • pp.1-9
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    • 2023
  • The purpose of this study is to derive the need to improve the test and evaluation(T&E) performance system of the weapon systems to which advanced science and technology is applied, evaluate priorities, and present development plans. T&E of Al-based weapon systems through a literature research and case analysis on changes in the T&E environment for weapon system, 11 detailed evaluation items were derived from the in terms of the T&E system, structure, and technology. Al-based weapon system test evaluation should be performed in parallel with data-based performance evaluation and actual T&E, and performance measurement using a separate T&E data set is required for AI models performance evaluation. As a result of analyzing the importance of T&E through AHP analysis, the order of T&E system-technology-structure was evaluated, and the priority of detailed evaluation items was evaluated in the order of T&E result judgment-T&E organization and expert training-scientific T&E. For evaluation items with high priority, measures to improve the T&E performance system were presented.

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Designing Effective Summary Models for Defense Articles with AI and Evaluating Performance (AI를 이용한 국방 기사의 효과적인 요약 모델 설계 및 성능 평가)

  • Yerin Nam;YunYoung Choi;JongGeun Choi;HyukJin Kwone
    • Journal of the Korean Society of Systems Engineering
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    • v.20 no.1
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    • pp.64-75
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    • 2024
  • With the development of the Internet, the information in our lives has become fast and diverse. Especially in the field of defense, articles and information are pouring in from various sources every day, and fast information selection, understanding, and decision-making are required in the ever-changing situation. It is very cumbersome to go from platform to platform and read articles one by one to get the information you need. To solve this problem, this research aims to save time and provide quick access to the latest information by allowing you to quickly grasp key information from summarized content without having to read the entire article. This can improve efficiency by allowing defense professionals to focus more on important tasks rather than extensive information search and analysis.

Knowledge Based and Object-Oriented Simulation Model for Logistics Analysis (지식기반 객체지향 군수시뮬레이션 모델에 관한 연구 - 초기군수지원성 분석모델을 중심으로 -)

  • 마호명;최상영
    • 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.

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Research on PEFT Feasibility for On-Device Military AI (온 디바이스 국방 AI를 위한 PEFT 효용성 연구)

  • Gi-Min Bae;Hak-Jin Lee;Sei-Ok Kim;Jang-Hyong Lee
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2024.01a
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    • pp.51-54
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    • 2024
  • 본 논문에서는 온 디바이스 국방 AI를 위한 효율적인 학습 방법을 제안한다. 제안하는 방법은 모델 전체를 재학습하는 대신 필요한 부분만 세밀하게 조정하여 계산 비용과 시간을 대폭 줄이는 PEFT 기법의 LoRa를 적용하였다. LoRa는 기존의 신경망 가중치를 직접 수정하지 않고 추가적인 낮은 랭크의 매트릭스를 학습하는 방식으로 기존 모델의 구조를 크게 변경하지 않으면서도, 효율적으로 새로운 작업에 적응할 수 있다. 또한 학습 파라미터 및 연산 입출력에 데이터에 대하여 32비트의 부동소수점(FP32) 대신 부동소수점(FP16, FP8) 또는 정수형(INT8)을 활용하는 경량화 기법인 양자화도 적용하였다. 적용 결과 학습시 요구되는 GPU의 사용량이 32GB에서 5.7GB로 82.19% 감소함을 확인하였다. 동일한 조건에서 동일한 데이터로 모델의 성능을 평가한 결과 동일 학습 횟수에선 LoRa와 양자화가 적용된 모델의 오류가 기본 모델보다 53.34% 증가함을 확인하였다. 모델 성능의 감소를 줄이기 위해서는 학습 횟수를 더 증가시킨 결과 오류 증가율이 29.29%로 동일 학습 횟수보다 더 줄어듬을 확인하였다.

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국방지휘통제체계 AI 적용을 위한 고찰

  • Kim, Yeong-Do;Gwon, Hyeok-Jin
    • Korea Information Processing Society Review
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    • v.24 no.1
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    • pp.13-18
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    • 2017
  • 국방지휘통제체계는 다양한 감시정찰 자산으로부터 수집된 많은 양의 정보를 융합하고 분석하여 지휘관이 최적의 의사결정을 내릴 수 있도록 지원하는 시스템이다. 하지만 현재 운영 중인 지휘 통제체계는 단순히 정보를 보여주고 유통하는 체계로 대량의 정보를 분석하고, 최적의 방책을 제공하는 등과 같은 지휘관의 의사결정을 지원하기에는 미흡한 수준이다. 지휘통제체계의 지능화 수준을 높이기 위해서 최근 이슈가 되고 있는 인공지능을 지휘 통제체계에 적용해 보고자 한다. 인공지능은 다양한 분야와의 융합을 통해 새로운 가치를 창출하고 사회 전반의 변혁을 이끌고 있다. 이러한 특성으로 4차 산업혁명의 핵심으로 주목받고 있다. 본 논문은 주요 선진국들의 인공지능 관련 추진동향과 인공지능의 국방적용을 위한 군사적 활용의 필요성, 그리고 지휘통제체계의 적용을 위한 고려요인들에 중점을 두었다. 지휘관의 의사결정을 보다 효과적으로 지원할 수 있도록 지능화된 지휘통제체계로 발전하는 데 기여할 수 있다고 생각한다.

Research on the core of unmanned system development using SNA (SNA을 이용한 무인체계 발전의 중심에 대한 연구)

  • Jin-Gwang Kim
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2024.01a
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    • pp.215-218
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    • 2024
  • 본 논문에서는 사회연결망분석을 이용하여 무인체계 관련 뉴스, 기사 자료를 분석하고 이를 통해 무인체계 발전의 중심을 파악하고자 하였다. 국방부는 인구감소로 인한 병역자원의 감소 문제를 해결하기 위해 발전하는 과학기술을 바탕으로 기존 병력 중심의 유인체계에서 AI 기반 유·무인 복합전투체계로 전환하기 위한 계획을 추진하고 있다. 이에 따라 최근 5년간의 무인체계 발전 동향을 확인함으로써 국방 무인체계 발전의 중심이 되는 노드를 살펴보고자 한다.

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