• Title/Summary/Keyword: AI-based system

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A Methodology for SDLC of AI-based Defense Information System (AI 기반 국방정보시스템 개발 생명주기 단계별 보안 활동 수행 방안)

  • Gyu-do Park;Young-ran Lee
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.33 no.3
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    • pp.577-589
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    • 2023
  • Ministry of National Defense plans to harness AI as a key technology to bolster overall defense capability for cultivation of an advanced strong military based on science and technology based on Defense Innovation 4.0 Plan. However, security threats due to the characteristics of AI can be a real threat to AI-based defense information system. In order to solve them, systematic security activities must be carried out from the development stage. This paper proposes security activities and considerations that must be carried out at each stage of AI-based defense information system. Through this, It is expected to contribute to preventing security threats caused by the application of AI technology to the defense field and securing the safety and reliability of defense information system.

Development of Artificial Intelligence Education System for K-12 Based on 4P (4P기반의 K-12 대상 인공지능 교육을 위한 교육체계 개발)

  • Ryu, Hyein;Cho, Jungwon
    • Journal of Digital Convergence
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    • v.19 no.1
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    • pp.141-149
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    • 2021
  • Due to the rapid rise of artificial intelligence technology around the world, SW education conducted in elementary and secondary schools is expanding including AI education. Therefore, this study aims to present an AI education system based on 4P(Play, Problem Solving, Product Making, Project) that can be applied from kindergarten to high school. The AI education system presented in this study is designed to be applied in 4P-based Play, Problem Solving, Product Making, and Project 4 stages so that it can be applied by school age and step by step. The level was presented by dividing it into two areas: AI literacy and AI development. In order to verify the validity of the developed AI education system, the Delphi method was applied to 15 experts who had experience in SW education or AI education. The AI education system derived as a result of the verification will be able to contribute to the development of a content system for AI education at each school level in the future.

FlappyBird Competition System: A Competition-Based Assessment System for AI Course (FlappyBird Competition System: 인공지능 수업의 경쟁 기반 평가 시스템의 구현)

  • Sohn, Eisung;Kim, Jaekyung
    • Journal of Korea Multimedia Society
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    • v.24 no.4
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    • pp.593-600
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    • 2021
  • In this paper, we present the FlappyBird Competition System (FCS) implementation, a competition-based automated assessment system used in an entry-level artificial intelligence (AI) course at a university. The proposed system provides an evaluation method suitable for AI courses while taking advantage of automated assessment methods. Students are to design a neural network structure, train the weights, and tune hyperparameters using the given reinforcement learning code to improve the overall performance of game AI. Students participate using the resulting trained model during the competition, and the system automatically calculates the final score based on the ranking. The user evaluation conducted after the semester ends shows that our competition-based automated assessment system promotes active participation and inspires students to be interested and motivated to learn AI. Using FCS, the instructor significantly reduces the amount of time required for assessment.

Exploratory Analysis of AI-based Policy Decision-making Implementation

  • SunYoung SHIN
    • International Journal of Internet, Broadcasting and Communication
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    • v.16 no.1
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    • pp.203-214
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    • 2024
  • This study seeks to provide implications for domestic-related policies through exploratory analysis research to support AI-based policy decision-making. The following should be considered when establishing an AI-based decision-making model in Korea. First, we need to understand the impact that the use of AI will have on policy and the service sector. The positive and negative impacts of AI use need to be better understood, guided by a public value perspective, and take into account the existence of different levels of governance and interests across public policy and service sectors. Second, reliability is essential for implementing innovative AI systems. In most organizations today, comprehensive AI model frameworks to enable and operationalize trust, accountability, and transparency are often insufficient or absent, with limited access to effective guidance, key practices, or government regulations. Third, the AI system is accountable. The OECD AI Principles set out five value-based principles for responsible management of trustworthy AI: inclusive growth, sustainable development and wellbeing, human-centered values and fairness values and fairness, transparency and explainability, robustness, security and safety, and accountability. Based on this, we need to build an AI-based decision-making system in Korea, and efforts should be made to build a system that can support policies by reflecting this. The limiting factor of this study is that it is an exploratory study of existing research data, and we would like to suggest future research plans by collecting opinions from experts in related fields. The expected effect of this study is analytical research on artificial intelligence-based decision-making systems, which will contribute to policy establishment and research in related fields.

Time-based Expert System Design for Coherent Integration Between M&S and AI (M&S와 AI간의 유기적 통합을 위한 시간기반 전문가 시스템 설계)

  • Shin, Suk-Hoon;Chi, Sung-Do
    • Journal of the Korea Society for Simulation
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    • v.26 no.2
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    • pp.59-65
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    • 2017
  • Along with the development of M&S, modeling research utilizing AI technology is attracting attention because of the fact that the needs of fields including human decision making such as defense M&S are increased. Obviously AI is a way to solve complex problems. However, AI did not consider logical time such as input time and processing time required by M&S. Therefore, in this paper we proposed a "time-based expert system" which redesigned the representative AI technology rule-based expert system. It consists of a rule structure "IF-THEN-AFTER" and an inference engine, takes logical time into consideration. We also tried logical analysis using a simple example. As a result of the analysis, the proposal Time-based Expert System proved that the result changes according to the input time point and inference time.

Validation of the effectiveness of AI-Based Personalized Adaptive Learning: Focusing on basic math class cases (인공지능(AI) 기반 맞춤형 학습의 효과검증: 기초 수학수업 사례 중심으로)

  • Eunae Burm;Yeol-Eo Chun;Ji Youn Han
    • Journal of Internet of Things and Convergence
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    • v.9 no.3
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    • pp.35-43
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    • 2023
  • This study tried to find out the applicability and effectiveness of the AI-based adaptive learning system in university classes by operating an AI-based adaptive learning system on a pilot basis. To this end, an AI-based adaptive learning system was applied to analyze the operation results of 42 learners who participated in basic mathematics classes, and a survey and in-depth interviews were conducted with students and professors. As a result of the study, the use of an AI-based customized learning system improved students' academic achievement. Both instructors and learners seem to contribute to improving learning performance in basic concept learning, and through this, the AI-based adaptive learning system is expected to be an effective way to enhance self-directed learning and strengthen knowledge through concept learning. It is expected to be used as basic data related to the introduction and application of basic science subjects for AI-based adaptive learning systems. In the future, we suggest a strategy study on how to use the analyzed data and to verify the effect of linking the learning process and analyzed data provided to students in AI-based customized learning to face-to-face classes.

A Study on the Militarization of Artificial Intelligence Technology in North Korea and the Development Direction of Corresponding Weapon System in South Korea (북한 인공지능 기술의 군사화와 우리 군의 대응 무기체계 발전방향 연구)

  • Kim, Min-Hyuk
    • Journal of Information Technology Services
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    • v.20 no.1
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    • pp.29-40
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    • 2021
  • North Korea's science and technology policies are being pursued under strong leadership and control by the central government. In particular, a large part of the research and development of science and technology related to the Fourth Industrial Revolution in North Korea is controlled and absorbed by the defense organizations under the national defense-oriented policy framework, among which North Korea is making national efforts to develop advanced technologies in artificial intelligence and actively utilize them in the military affairs. The future weapon system based on AI will have superior performance and destructive power that is different from modern weapons systems, which is likely to change the paradigm of the future battlefield, so a thorough analysis and prediction of the level of AI militarization technology, the direction of development, and AI-based weapons system in North Korea is needed. In addition, research and development of South Korea's corresponding weapon systems and military science and technology are strongly required as soon as possible. Therefore, in this paper, we will analyze the level of AI technology, the direction of AI militarization, and the AI-based weapons system in North Korea, and discuss the AI military technology and corresponding weapon systems that South Korea military must research and develop to counter the North Korea's. The next study will discuss the analysis of AI militarization technologies not only in North Korea but also in neighboring countries in Northeast Asia such as China and Russia, as well as AI weapon systems by battlefield function, detailed core technologies, and research and development measures.

AI-based system for automatically detecting food risk information from news data (뉴스 데이터로부터 식품위해정보 자동 추출을 위한 인공지능 기술)

  • Baek, Yujin;Lee, Jihyeon;Kim, Nam Hee;Lee, Hunjoo;Choo, Jaegul
    • Food Science and Industry
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    • v.54 no.3
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    • pp.160-170
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    • 2021
  • A recent advance in communication technologies accelerates the spread of food safety issues once presented by the news media. To respond to those safety issues and take steps in a timely manner, automatically detecting related information from the news data matters. This work presents an AI-based system that detects risk information within a food-related news article. Experts in food safety areas participated in labeling risk information from the food-related news articles; we acquired 43,527 articles in which food names and risk information are marked as labels. Based on the news document, our system automatically detects food names and risk information by analyzing similarities between words within a text by leveraging learned word embedding vectors. Our AI-based system shows higher detection accuracy scores over a non-AI rule-based system: achieving an absolute gain of +32.94% in F1 for the food name category and +41.53% for the risk information category.

Hybrid Learning-Based AI Education System Design Model (하이브리드 러닝 기반 AI 교육 시스템 구성)

  • Hong, Misun;Bae, JinAh;Park, Jung-Hwan;Cho, Jungwon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.10a
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    • pp.188-190
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    • 2022
  • We propose how to configure the AI education system based on the purpose of hybrid learning and the teaching-learning principle. Based on the four components of hybrid learning, we have designed the system conceptual diagram and DB configuration diagram for on-line and offline learning environments for effective AI education. The proposed AI education system model in this paper is expected to be a foundation for maximizing the effectiveness of AI education according to the level and needs of learners and building a more effective learner-centered learning environment in cultivating computational thinking in AI education.

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Blockchain-Based Juridical AI Registration System (블록체인 기반 AI 법인 등록제)

  • Jeon, MinGyu;Hwang, Chiyeon;Na, Hyeon-Suk
    • Journal of Digital Convergence
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    • v.18 no.5
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    • pp.17-23
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    • 2020
  • With the advancement of AI technology, legal status and regulation issues for AI robots, and the necessity of a robot registration system are emerging. Since the shape and activity area of AI robots will no longer be limited to hardware in one country, the definition and regulation of AI robots should be expanded to a comprehensive concept including software, and information about them should be securely managed and shared by governments around the world. From this perspective, we extend 'AI robot' to the concept of Juridical AI encompassing hardware and software, and propose a method to operate the Juridical AI registration system using a permissioned blockchain called Juridical AI Chain. Since blockchain is an internationally distributed database, operating such AI registration system based on the blockchain will be a way to effectively cope with the global problems caused by the commercialization of AI robots.