• 한국컴퓨터정보학회논문지
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• 제15권2호
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• pp.135-146
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• 2010

본 논문에서는 이러닝 마켓플레이스에서 자기주도학습지원을 위한 추천시스템을 제안한다. 이 시스템은 마켓플레이스를 지원하기위한 개선된 협업필터링을 이용한 추천시스템이다. 기존의 협업필터링 기법은 입력데이터구성, 최근접 이웃선정을 통한 유사고객 그룹을 형성하고, 추천목록 생성하는 3단계로 구성되었다. 본 연구는 이를 개선하여 산업 수준을 고려한 최근접 이웃 교육과정 선정 단계를 추가한 협업필터링에 사용하여, 자기주도학습을 지원할 수 있는 추천시스템을 설계하였다. 이 서비스는 산업체 학습자에게 보다 정확한 교육과정을 선택할 수 있도록 도와준다. 추천시스템은 다양한 기법을 통해 구축되며, 협업필터링 방식을 사용하여 명시적인 속성이 부여 되어진 콘텐츠를 추천하는 것은, 기존 콘텐츠 추천의 한계를 해결하고자 하였다.

• 한국IT서비스학회지
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• 제6권3호
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• pp.111-128
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• 2007

The purpose of the research is to analyze the status and problems of the e-Learning quality assurance system on e-Learning contents and service provider(institutes) in the field of enterprise education. In addition, the research is to suggest the direction and strategies for revising and developing the system. The research put emphasis on two systems of the e-Learning quality assurance(contents, service provider) which directly influence financial support of government. This study depended mostly on literature review, supplemented by expert panel meetings. In the case of the quality assurance system on e-Learning contents, the followings are suggested; (1)admitting the contents made of the combination of modules in the approved module set, (2)making easier the qualifying of modified contents for maintenance, (3)revising evaluation criteria, (4)providing substantial feedback. In the field of service provider, the followings are requested; (1)differentiating of qualifying system by industry and scale of company, (2)extending the qualifying cycle, (3)improving the feedback and sharing system.

• 제어로봇시스템학회논문지
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• 제19권12호
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• pp.1099-1104
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• 2013

This paper presents a learning-based visual inspection method that addresses the need for an improved adaptability of a visual inspection system for parts verification in panorama sunroof assembly lines. It is essential to ensure that the many parts required (bolts and nuts, etc.) are properly installed in the PLC sunroof manufacturing process. Instead of human inspectors, a visual inspection system can automatically perform parts verification tasks to assure that parts are properly installed while rejecting any that are improperly assembled. The proposed visual inspection method is able to adapt to changing inspection tasks and environmental conditions through an efficient learning process. The proposed system consists of two major modules: learning mode and test mode. The SVM (Support Vector Machine) learning algorithm is employed to implement part learning and verification. The proposed method is very robust for changing environmental conditions, and various experimental results show the effectiveness of the proposed method.

• 한국인공지능학회지
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• 제7권2호
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• pp.19-24
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• 2019

Lung cancer is a chronic disease which ranks fourth in cancer incidence with 11 percent of the total cancer incidence in Korea. To deal with such issues, there is an active study on the usefulness and utilization of the Clinical Decision Support System (CDSS) which utilizes machine learning. Thus, this study reviews existing studies on artificial intelligence technology that can be used in determining the lung cancer, and conducted a study on the applicability of machine learning in determination of the lung cancer by comparison and analysis using Azure ML provided by Microsoft. The results of this study show different predictions yielded by three algorithms: Support Vector Machine (SVM), Two-Class Support Decision Jungle and Multiclass Decision Jungle. This study has its limitations in the size of the Big data used in Machine Learning. Although the data provided by Kaggle is the most suitable one for this study, it is assumed that there is a limit in learning the data fully due to the lack of absolute figures. Therefore, it is claimed that if the agency's cooperation in the subsequent research is used to compare and analyze various kinds of algorithms other than those used in this study, a more accurate screening machine for lung cancer could be created.

• ETRI Journal
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• 제28권4호
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• pp.461-474
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• 2006

This project aims to design and develop a prototype for an agent that support online collaborative learning. Online collaborative learning, which has emerged as a new form of education in the knowledge-based society, is regarded as an effective method for improving practical and highly advanced problem-solving abilities. Collaborative learning involves complicated processes, such as organizing teams, setting common goals, performing tasks, and evaluating the outcome of team activities. Thus, a teacher may have difficulty promoting and evaluating the entire process of collaborative learning, and a system may need to be developed to support it. Therefore, to promote interaction among learners in the process of collaborative learning, this study designed an extensible collaborative learning agent (ECOLA) for an online learning environment.

• 서비스연구
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• 제6권4호
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• pp.47-57
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• 2016

오픈소스는 스마트폰의 등장과 함께 놀라운 확산을 하고 있다. 이러닝 분야의 오픈소스인 Moodle 학습관리시스템은, 상용프로그램인 Blackboard를 제외하고 전 세계적으로 가장 많이 사용되고 있는 학습관리시스템이다. 그 이유 중 하나는 교육공학의 이론적 기초가 되며, 이러닝의 핵심 원칙이라 할 수 있는 구성주의 원칙에 따른, 협동학습과 상호작용이 잘 지원되도록 설계되어, 높은 교육적 효과와 장점을 가지기 때문이다. 본 연구에서는 오픈소스인 Moodle 학습관리시스템을 이용한 협동학습 운영 사례를 중심으로, 사용자의 협동학습을 지원하는 구체적 내용을 소개하고, 사례를 통하여 나타난, Moodle 학습관리시스템 협동학습의 장점과 특이점을 살펴본다. 연구 결과 PC와 스마트폰 환경에서 동시에 구현된, Moodle 학습관리시스템의 팀 프로젝트 협동학습을 통하여, 협동학습의 재미와 유용성을 확인하고, 학습자체의 중요성을 넘어 관계의 중요성이 학습자의 협동학습동기를 유발시킨다는 것을 사례를 통하여 확인할 수 있다.

• 한국정보시스템학회지:정보시스템연구
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• 제2권
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• pp.194-206
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• 1993

Intelligent remote learning system is a system that incorporate communication technology and others : a database engine, an intelligent tutorial system. Learners can study by themselves through the intelligent tutorial system. The existence of a communication, database and artificial intelligence enhance the capability of IRLS. According to Parsaye, an intelligent databases should have the following features : 1) Knowledge discovery. 2) Data integrity and quality control. 3) Hypermedia management. 4) Data presentation and display. 5) Decision support and scenario analysis. 6) Data format management. 7) Intelligent system design tools. I hope that this research of framework for IRLS paves for the future research. As mentioned in the above, the future work will include an intelligent database, self-learning mechanism using neural network.

• 한국비블리아학회지
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• 제34권2호
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• pp.93-114
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• 2023

자기주도적 창의교육을 중시하는 교육 패러다임에 따라 학생들의 학습을 지원하는 주요한 공적 기관인 학교도서관과 공공도서관은 교과연계프로그램을 통한 자기주도적 학습 지원을 주요 업무로 강조하고 있다. 자기주도적 학습을 위해서는 학습자 중심의 교육 지식정보 제공이 필수적이며, 교과서에 반영된 교육과정을 심화·확장할 수 있는 교과서 연계 참고자료가 풍부하게 확보되어야 한다. 이 연구에서는 우선 초등학교 교과과정을 분석하여 도서관 자료를 적극적으로 활용하거나 확장하고자 하는 정보요구가 큰 주요 교과를 식별하고, 도서관 컬렉션 및 분류체계와 연계할 중점 매핑 포인트를 설정하였다. 각 교과의 학습주제 및 교과연계도서의 서지정보와 함께 한국십진분류법(KDC)의 분류표목 및 상관색인의 도입어를 참조하여 학습주제와 연관된 분류항목을 파악하였다. 이를 바탕으로, 학생들에게 친숙하지 않은 KDC 체계를 초등학교 주요 교과의 단원을 중심으로 재구성하여 학습자 중심의 교과서 연계 서지정보 및 주제정보를 구축하였다. 이를 통해 도서관은 교과과정의 학습주제를 중심으로 이용자별로 타겟화된 도서관 콘텐츠와 초등학교 교육콘텐츠를 연계함으로써 온라인 환경에서 초등학생의 자기주도적 창의학습 지원을 강화할 수 있다.

• Journal of the Korean Data and Information Science Society
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• 제14권4호
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• pp.1083-1090
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• 2003

Web-based learning is currently an active area of research and a considerable number of studies have been conducted on its application in the learning environment. However, in spite of many advances in the research and development of the educational contents, questions about how the environment affects learning remains largely unanswered. In this article, we propose a Web-based learning environment to improve the educational effect. The goal of this article is not to provide a complete system to support Web-based learning but rather to describe some meaningful strategies and fundamental design concepts that utilize information technologies to support teaching and learning.

• International Journal of Internet, Broadcasting and Communication
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• 제14권2호
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• pp.119-128
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• 2022

Recently, due to the development of related technologies for autonomous vehicles, driving work is changing more safely. However, the development of support technologies for level 5 full autonomous driving is still insufficient. That is, even in the case of an autonomous vehicle, the driver needs to drive through forward attention while driving. In this paper, we propose a method to monitor driving tasks by recognizing driver behavior. The proposed method uses pre-trained deep convolutional neural network models to recognize whether the driver's face or body has unnecessary movement. The use of pre-trained Deep Convolitional Neural Network (DCNN) models enables high accuracy in relatively short time, and has the advantage of overcoming limitations in collecting a small number of driver behavior learning data. The proposed method can be applied to an intelligent vehicle safety driving support system, such as driver drowsy driving detection and abnormal driving detection.