• Title/Summary/Keyword: AI 개발

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Development of the Content Framework for Elementary Artificial Intelligence Literacy Education (초등학생의 인공지능 소양을 기르기 위한 내용체계 개발)

  • Youngsik Jeong
    • Journal of The Korean Association of Information Education
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    • v.26 no.5
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    • pp.375-384
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    • 2022
  • As artificial intelligence(AI) education becomes essential in elementary schools with the revised 2022 curriculum, it is necessary to develop an AI curriculum for elementary school students. In this study, I developed the AI content framework to cultivate AI literacy of elementary school students. AI education areas were largely divided into AI understanding and AI development, and detailed areas were divided into eight categories: using of AI, impact of AI, AI ethics, recognition of AI, data expression, data exploring, learning of AI, and prediction of AI. In addition, twice expert Delphi surveys were conducted to verify the validity of the subject elements and achievement standards for each area. The final draft was finalized after reflecting expert opinions on the AI education content framework. In order for AI education to be expanded in elementary schools in the future, continuous research is needed, such as developing textbooks and teaching tools according based on the AI framework proposed in this study, securing the lesson hours to apply them to schools, and correcting and supplementing the problems of them.

A Study on the Development of an Automatic Classification System for Life Safety Prevention Service Reporting Images through the Development of AI Learning Model and AI Model Serving Server (AI 학습모델 및 AI모델 서빙 서버 개발을 통한 생활안전 예방 서비스 신고 이미지 자동분류 시스템 개발에 대한 연구)

  • Young Sic Jeong;Yong-Woon Kim;Jeongil Yim
    • Journal of the Society of Disaster Information
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    • v.19 no.2
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    • pp.432-438
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    • 2023
  • Purpose: The purpose of this study is to enable users to conveniently report risks by automatically classifying risk categories in real time using AI for images reported in the life safety prevention service app. Method: Through a system consisting of a life safety prevention service platform, life safety prevention service app, AI model serving server and sftp server interconnected through the Internet, the reported life safety images are automatically classified in real time, and the AI model used at this time An AI learning algorithm for generation was also developed. Result: Images can be automatically classified by AI processing in real time, making it easier for reporters to report matters related to life safety.Conclusion: The AI image automatic classification system presented in this paper automatically classifies reported images in real time with a classification accuracy of over 90%, enabling reporters to easily report images related to life safety. It is necessary to develop faster and more accurate AI models and improve system processing capacity.

A Study on Contents Development for the Use of Generative AI in Elementary and Secondary Classes

  • Injoo Kim;Kwihoon Kim
    • Journal of the Korea Society of Computer and Information
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    • v.29 no.8
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    • pp.223-230
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    • 2024
  • The purposes of this study is to find out how to use Generative AI by class stage and class model so that classes can be planned using various Generative AI in elementary and secondary education. To this end, contents of using Generative AI according to general instructional stages and instructional models by school level and subject were developed, and revised and supplemented through review by 13 field experts. As for the method of using Generative AI by class stage, general class stages were divided into three stages: 'class preparation', 'in class', and 'class arrangement', and the subject of using Generative AI at each stage, the contents of using it, and the types of Generative AI that can be used are summarized. As a method of using Generative AI according to the class model, eight class contents were developed based on teaching and learning models according to the characteristics of each school level and subject. In order to expand the use of Generative AI in elementary and secondary classes, it is necessary to develop more diverse class contents by school level and subject and distribute them in the field. It is also necessary to develop educational materials on matters to consider when using Generative AI in class.

A Development of Program for Positive Teacher based on Appreciative Inquiry (AI 활용 긍정적인 교사 양성 프로그램 개발)

  • Chang, Kyungwon
    • Proceedings of the Korea Contents Association Conference
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    • 2011.05a
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    • pp.355-356
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    • 2011
  • AI는 개인이나 조직이 가지고 있는 강점과 긍정적 경험을 토대로 변화를 이끌어내는 것으로 본 연구는 AI가 가진 이러한 특성을 기반으로 긍정교사 양성을 위한 프로그램을 개발하였다. 먼저 AI의 4D 단계를 진행하기 위한 긍정주제를 선정하였는데, 대주제는 "닮고싶은 선생님"이고, 하위 주제는 이해, 소통, 열정, 실력이다. 각 주제별로 교사들에게 제시할 긍정적 질문을 개발하였고, 질문을 토대로 교사양성 프로그램을 개발하였다. 프로그램 실행 결과 교사들은 자신의 강점을 찾아 그것을 기반으로 자기 개발을 위해 무엇을 할 것인지 계획을 수립하였고 이러한 계획이 교사역량을 개발하는데 매우 유용하다고 평가하였다.

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Development of Game Graphics and AI Picture Classification Model for Real-Life Images on CNN (CNN 기반의 실사 이미지에 대한 게임 그래픽과 AI 그림 분류 모델 개발)

  • Seung-Bo Park;Dong-Hwi Cho;Seo-Young Choi;Eun-Ji Kim
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2023.07a
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    • pp.465-466
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    • 2023
  • AI 기술의 발전으로 AI가 그린 그림과 인간이 직접 그린 그림을 식별하는 것이 어려워졌다. AI 기술을 통해 작품을 특정 화풍으로 그리는 것이 쉬워져 작품 도용과 평가 절하가 증가하고 있으며, AI가 인간과 유사하게 그림을 표현하는 경우 딥페이크 피싱과 같은 악용 사례도 늘어나고 있다. 따라서 본 논문에서는 AI 그림을 식별하기 위한 인공지능 모델 개발을 목표로 하고 있으며, 데이터셋을 구축하여 인공지능 기술을 활용한 알고리즘을 개발한다. YOLO Segmentation과 CNN을 활용하여 학습을 진행하고, 이를 통해 도용과 딥페이크 피해를 방지하는 프로세스를 제안한다.

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Exploring teaching and learning methods using artificial intelligence (AI) in the mathematics classroom : Focusing on the development of middle school statistic scenarios (수학교실에서 인공지능(AI)을 활용한 교수학습 방안 탐색 : 중학교 통계 단원 시나리오 개발을 중심으로)

  • Choi, Inseon
    • Journal of the Korean School Mathematics Society
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    • v.25 no.2
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    • pp.149-174
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    • 2022
  • The purpose of this study is to explore the teaching and learning method using artificial intelligence (AI) in the mathematics classroom. To this end, to predict the direction of mathematics education using AI in the mathematics classroom, this study investigates the fields where AI is applied to education, and discuss issues to consider when introducing AI through scenario development using AI in middle school statistics. This study is meaningful in that it specifically considered how artificial intelligence can be grafted into the mathematics classroom through the development of scenarios that integrate and apply artificial intelligence that has been developed and used segmentally in the current middle school statistics. Afterwards, based on the contents of this study, implications for using AI in the math classroom were derived.

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.

An Empirical Study on Frequently used Python APIs in AI-Related Open Source Python Software Projects (인공지능과 관련된 오픈 소스 파이썬 소프트웨어 프로젝트에서 자주 사용되는 파이썬 API들에 대한 연구)

  • Jungil Kim
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2024.01a
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    • pp.19-22
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    • 2024
  • 전통 소프트웨어 프로젝트 개발과 AI 관련된 소프트웨어 프로젝트 개발에 큰 차이가 있어서 AI 관련된 소프트웨어 프로젝트 개발 환경을 이해하려는 많은 노력이 있었지만 AI 관련 소프트웨어 프로젝트 개발에서 어떤 API들이 자주 사용되는지에 대해서 아직 충분히 조사되지 않았다. 본 논문에서는 "AI 관련 오픈 소스 소프트웨어 프로젝트에서 어떤 파이썬 API들이 자주 사용되는가?"에 대한 연구 질문의 해답을 알아보는 경험 연구를 소개한다. 이 경험 연구의 결과로 AI 관련 오픈 소스 소프트웨어 프로젝트에서 파이썬 표준 라이브러리와 관려된 API들이 가장 자주 사용된다는 것을 확인했다. 또한 기계 학습을 포함해서 데이터 처리, 이미지 처리, 테스팅, 웹 서비스와 관련된 라이브러리들에 있는 API들도 AI 관련 오픈 소스 소프트웨어 프로젝트들에 자주 사용된다는 것을 알아냈다.

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Development of Smart medicine box Integrated with AI speaker (AI 스피커와 연동되는 스마트 약통 개발)

  • Choi, Hyo Hyun;Yu, Kwang Sik
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2022.01a
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    • pp.289-290
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    • 2022
  • 본 논문에서는 약을 제 시간에 복용할 수 있도록 도와주는 스마트 약통 서비스를 개발한 결과를 보인다. 라즈베리파이, 자석감지센서, LED, AI스피커와 외부서버를 결합한 구조로 개발하였으며, 사용자는 약을 복용하였는지에 따라 AI스피커를 통해서 약 복용 여부를 물어볼 수 있고 LED를 통해서 아침, 점심, 저녁의 시간에 따라 복용해야 하는 약을 표시해 줄 수 있도록 하였다.

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Implementation of Autonomous IoT Integrated Development Environment based on AI Component Abstract Model (AI 컴포넌트 추상화 모델 기반 자율형 IoT 통합개발환경 구현)

  • Kim, Seoyeon;Yun, Young-Sun;Eun, Seong-Bae;Cha, Sin;Jung, Jinman
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.21 no.5
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    • pp.71-77
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    • 2021
  • Recently, there is a demand for efficient program development of an IoT application support frameworks considering heterogeneous hardware characteristics. In addition, the scope of hardware support is expanding with the development of neuromorphic architecture that mimics the human brain to learn on their own and enables autonomous computing. However, most existing IoT IDE(Integrated Development Environment), it is difficult to support AI(Artificial Intelligence) or to support services combined with various hardware such as neuromorphic architectures. In this paper, we design an AI component abstract model that supports the second-generation ANN(Artificial Neural Network) and the third-generation SNN(Spiking Neural Network), and implemented an autonomous IoT IDE based on the proposed model. IoT developers can automatically create AI components through the proposed technique without knowledge of AI and SNN. The proposed technique is flexible in code conversion according to runtime, so development productivity is high. Through experimentation of the proposed method, it was confirmed that the conversion delay time due to the VCL(Virtual Component Layer) may occur, but the difference is not significant.