• Journal of Digital Convergence
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• v.18 no.6
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• pp.287-295
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• 2020

This study defined the characteristics of micro-learning emerging by mobile learning and micro-contents in the e-learning field, and analyzed the satisfaction of application, to see if micro-learning could become a new learning type in the future. To this end, the characteristics of micro-learning were defined through preliminary literature analysis, the characteristic satisfaction was verified in the well-equipped micro-learning site, and any other technical functions were suggested through expert opinion gathering. It was suggested that the future technology of e-learning should be linked to technical functions such as learning analysis and performance measurement. According to the results of this study, if micro-learning reflects its functional characteristics well, it will become an effective learning type in the e-learning field and will greatly contribute to education, learning, and training for the new millennial.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.517-535
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• 2021

The development of digital technology has not only brought many changes to our lives, but also many changes to the online education environment. The emergence of micro-learning is to meet the needs of individual learners who hopes to receive personalized learning content immediately when they need it. Therefore, Micro-learning can be said to be 'adaptive' education. This research attempts to explore the development principles of adaptive micro-learning through literature research and case analysis. The results of the research draw four aspects of the development principles, including adaptive learning environment, adaptive learning content, adaptive learning sequence and adaptive learning evaluation, as well as detailed elements of each aspect. Micro-learning is a new form of e-learning that reflects the needs of the current society. As exploratory research, this research attempts to point out the direction for future follow-up research.

• Journal of the Korea Convergence Society
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• v.11 no.7
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• pp.369-376
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• 2020

This study was conducted to verify the effectiveness of learning using micro-running. To this end, the learning materials of the class were produced in three forms: micro-learning, existing e-learning, and handouts, to compare the learning satisfaction and learning effect for college students at Y and K universities located in K-do. First, when using learning materials in the form of micro-learning, learning satisfaction was the highest. Second, the learning effect was effective for both e-learning and micro-learning. And micro-learning was more effective when both types of learning materials were used. The results of this study look forward to activating micro-learning in university by researching micro-learning of the new learning type that emerged as a social phenomenon, highlighting the importance of micro-learning and presenting basic data for subsequent study.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.973-980
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• 2023

This study analyzed the effects of a Micro-learning content-based extracurricular program among university students based on their general characteristics. A survey was conducted on 600 students affiliated with G University, a major national university. Learning immersion and learning motivation were used as the key indicators for measuring the learning effects. Cronbach's α coefficient analysis was performed to validate the reliability of the learning effect measurement tool. Independent sample t-tests were utilized to analyze differences in learning immersion and learning motivation based on gender and major disciplines. One-way analysis of variance (ANOVA) was employed to measure differences in learning immersion and learning motivation according to academic year. According to the research findings, gender and academic year did not significantly influence participation in the Micro-learning content-based program. However, differences in learning immersion and learning motivation were observed depending on the major discipline. Based on this, it is suggested that future programs should provide suitable environments and stimuli based on the students' major disciplines.

• The Journal of the Korea Contents Association
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• v.9 no.6
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• pp.17-24
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• 2009

This paper proposes a new e-learning model which introduces a participant method based on concepts of open source as well as UCC of web2.0 and achieves learner-centered learning. It is possible for learner to participate actively in creation of micro-contents and reorganize contents using various micro-content with one's learning strategies in consideration of one's own intellectual power, learning objectives and propensity to learn. The learner can achieve the learner-oriented learning through this procedure and select micro-contents in order to reorganize the personalized learning contents to take advantage of social network among learners. The higher effectiveness of learning would be expected by forming connectedness among learners using social network.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.05a
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• pp.78-80
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• 2022

최근 딥러닝을 이용한 영상 분석은 자율주행, 감시카메라 등 다양한 서비스에 필수적으로 활용되고 있으며 실시간 처리 및 보안 요소를 만족하기 위해 기존의 클라우드 컴퓨팅 방식의 단점을 개선한 클라우드 엣지 컴퓨팅 방식을 적용하는 사례가 크게 증가하고 있다. 하지만 사용자 및 단말과 가까운 위치에서 딥러닝 추론을 진행하는 클라우드 엣지 서버는 클라우드 서버와 비교하여 컴퓨팅 자원이 충분하지 않을 경우가 많으며 기존의 딥러닝 모델을 그대로 클라우드 엣지 환경에 적용하는 것은 자원 활용 측면에서 여러가지 문제점들을 갖고 있다. 따라서 본 논문에서는 마이크로서비스 구조를 통해 자원을 보다 유연하게 활용할 수 있도록 개선된 딥러닝 모델로 대규모의 클라이언트 요청을 처리 가능한 동영상 데이터 추론 서비스인 G-Edge AI 추론 서비스 개발에 대해 설명한다.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.5 no.4
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• pp.180-185
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• 2012

Social Learning is a new study model of future knowledge information society. In different existing study, it concentrate on relationship with others and design to connect studying with social effect as a study platform using social media such as Blog, SNS, UCC, Microblog. In my paper, social learning characteristics are described to understand social learning, that is 3 keyword such as context, connectivity, collaboration. Also we investigate social media characteristics and social media how to be used social learning. Also social learning system building method using facebook is presented.

• Journal of The Korean Association of Information Education
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• v.25 no.6
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• pp.995-1003
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• 2021

As the need for artificial intelligence (AI) education, which will become the core of the upcoming intelligent information society rises, the national level is also focusing attention by including artificial intelligence-related content in the curriculum. In this study, the PASPA education program was presented to enhance students' creative problem-solving ability in the process of solving problems in daily life through supervised machine learning. And Micro:bit, a physical computing tool, was used to enhance the learning effect. The teaching and learning process applied to the PASPA education program consists of five steps: Problem Recoginition, Argument, Setting data standard, Programming, Application and evaluation. As a result of applying this educational program to students, it was confirmed that the creative problem-solving ability improved, and it was confirmed that there was a significant difference in knowledge and thinking in specific areas and critical and logical thinking in detailed areas.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2020.07a
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• pp.26-27
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• 2020

본 논문에서는 서로 다른 특성을 갖기 때문에 표준화가 어려운 엣지 플랫폼에서 동일한 머신 러닝 모델로도 확장 가능한 분석 서비스를 하기 위해, 마이크로서비스 기반으로 협업 분석 하는 설계 방법을 소개한다. 이를 위해 실제 사용자 분석 결과 적응적인 컨텐츠 서비스 시나리오를 고려하였다. 서로 다른 성능을 갖는 엣지가 협업하기 위해서 클라우드에서 제공 받는 어플리케이션을 마이크로 서비스화 하고 다수의 엣지에 해당 서비스를 분산 분포하여 연결한다. 해당 방법은 전체 서비스를 상호 독립적인 최소 구성 요소로 분할하고 모든 요소가 독립적으로 연동되어 타스크를 수행하게 하며 유사한 프로세스는 공유함으로서 상대적으로 성능이 떨어지는 엣지들간 협력으로 효율적인 분석 서비스 제공이 가능하도록 할 것이다.

• Journal of the Microelectronics and Packaging Society
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• v.30 no.4
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• pp.69-78
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• 2023

With the rapid growth of artificial intelligence, the demand for semiconductors is enormously increasing everywhere. To ensure the manufacturing quality and quantity simultaneously, the importance of automatic defect detection during the packaging process has been re-visited by adapting various deep learning-based methodologies into automatic packaging defect inspection. Deep learning (DL) models require a large amount of data for training, but due to the nature of the semiconductor industry where security is important, sharing and labeling of relevant data is challenging, making it difficult for model training. In this study, we propose a new framework for securing sufficient data for DL models with fewer computing resources through a divide-and-conquer approach. The proposed method divides high-resolution images into pre-defined sub-regions and assigns conditional labels to each region, then trains individual sub-regions and boundaries with boundary loss inducing the globally coherent and seamless images. Afterwards, full-size image is reconstructed by combining divided sub-regions. The experimental results show that the images obtained through this research have high efficiency, consistency, quality, and generality.