• 한국디지털정책학회:학술대회논문집
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• 한국디지털정책학회 2005년도 추계학술대회
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• pp.613-628
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• 2005

The purpose of this study was to design and implementation of project learning site by using XML. The development of the Internet site for project learning was planned as per preparation, development and test/application stages. At the stage of preparation, literature and cases were reviewed to find the elements of design principles needed for development of a project learning program and those required in the actual development. At the stage of development, the elements of the design principles and those for the actual development, both explored from the stage of preparation were used to develop a draft Internet site for project learning. The elements used for the development of the Internet site for project learning were motivation, specification of learning goals, reminiscence of preceding knowledge, positive participation in teaching activities, learning-guide feedback, evaluation, reinforcement and correction. It is changing web based format. XML advent because of HTML limitations of web based internet and expand it's field. XML is able to gather data on HTML of text based format, thus it is possible to control it's inside. It is expected that many teachers apply this model to their classes and show realistic results.

• 한국환경교육학회지:환경교육
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• 제23권2호
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• pp.32-45
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• 2010

The purpose of the present study is to develop ecological experience learning program for the wetland so that elementary school students can recognize the significance and values of wetland and have the attitudes to protect it through their ecological experience learning, and investigate changes in elementary school students' perception for wetland. The experimental class was composed of 26 elementary school students and took the ecological experience learning. The comparison class was also composed of 26 students who took theoretical learning for wetland. It was found that knowledge and attitudes for wetland of the experimental class were significantly high not only in the knowledge area but also in the affective area than those of the comparison class. And it was found that interest and curiosity into wetland were elevated also in the results of the qualitative evaluation, suggesting that we could get the effect of ecological experience learning. Therefore, it is thought that above all, more experience learning programs for wetland are needed to develop for elementary school students' right view of nature and minds to love it by continuously finding and providing materials of experience learning like those of this research in the future.

• 한국IT서비스학회지
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• 제15권4호
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• pp.85-95
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• 2016

Recently, deep learning and machine learning have attracted considerable attention and many supporting frameworks appeared. In artificial intelligence field, a large body of research is underway to apply the relevant knowledge for complex problem-solving, necessitating the application of various learning algorithms and training methods to artificial intelligence systems. In addition, there is a dearth of performance evaluation of decision making agents. The decision making agent that can find optimal solutions by using reinforcement learning methods designed through this research can collect raw pixel data observed from dynamic environments and make decisions by itself based on the data. The decision making agent uses convolutional neural networks to classify situations it confronts, and the data observed from the environment undergoes preprocessing before being used. This research represents how the convolutional neural networks and the decision making agent are configured, analyzes learning performance through a value-based algorithm and a policy-based algorithm : a Deep Q-Networks and a Policy Gradient, sets forth their differences and demonstrates how the convolutional neural networks affect entire learning performance when using pixel data. This research is expected to contribute to the improvement of artificial intelligence systems which can efficiently find optimal solutions by using features extracted from raw pixel data.

• 한국환경복원기술학회지
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• 제24권6호
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• pp.89-96
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• 2021

In this study, a deep-learning image analysis model was established and validated for AI-based monitoring of the tidal flat ecosystem for marine protected creatures Ocypode stimpsoni and their habitat. The data in the study was constructed using an unmanned aerial vehicle, and the U-net model was applied for the deep learning model. The accuracy of deep learning model learning results was about 0.76 and about 0.8 each for the Ocypode stimpsoni and their burrow whose accuracy was higher. Analyzing the distribution of crabs and burrows by putting orthomosaic images of the entire study area to the learned deep learning model, it was confirmed that 1,943 Ocypode stimpsoni and 2,807 burrow were distributed in the study area. Through this study, the possibility of using the deep learning image analysis technology for monitoring the tidal ecosystem was confirmed. And it is expected that it can be used in the tidal ecosystem monitoring field by expanding the monitoring sites and target species in the future.

• 대한후두음성언어의학회지
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• 제33권3호
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• pp.142-155
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• 2022

Diagnosis using voice is non-invasive and can be implemented through various voice recording devices; therefore, it can be used as a screening or diagnostic assistant tool for laryngeal voice disease to help clinicians. The development of artificial intelligence algorithms, such as machine learning, led by the latest deep learning technology, began with a binary classification that distinguishes normal and pathological voices; consequently, it has contributed in improving the accuracy of multi-classification to classify various types of pathological voices. However, no conclusions that can be applied in the clinical field have yet been achieved. Most studies on pathological speech classification using speech have used the continuous short vowel /ah/, which is relatively easier than using continuous or running speech. However, continuous speech has the potential to derive more accurate results as additional information can be obtained from the change in the voice signal over time. In this review, explanations of terms related to artificial intelligence research, and the latest trends in machine learning and deep learning algorithms are reviewed; furthermore, the latest research results and limitations are introduced to provide future directions for researchers.

• 한국과학교육학회지
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• 제27권6호
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• pp.519-528
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• 2007

Although science continues to be a key subject in the education of the majority of young people throughout the world, it is becoming increasingly clear that school science is failing to win the hearts and minds of many of today's younger generation. Researchers have begun to look at ways in which the learning that takes place in museums, science centres and other informal settings can add value to science learning in schools. Four case studies are used to illustrate the potential afforded by informal contexts to research aspects of science learning. The case studies involve: the European Union PENCIL (Permanent European Resource Centre for Informal Learning) project (a network of 14 museums and science centres working with schools to enhance learning in maths and science); a large natural history museum in England; the Tate Modernart gallery in London, and the Outdoor Classroom Action Research Project which involved researchers working in school grounds, field centres and farms. The range of research questions that were asked are examined as are the methodological approaches taken and the methods used to collect and analyse data. Lessons learned from the studies about research in the informal contexts are discussed critically.

• 대한영상의학회지
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• 제83권6호
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• pp.1208-1218
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• 2022

최근, 의료 분야에서 인공지능은 많은 발전을 통해 다양한 분야로 확장하며 활용되고 있다. 하지만 대부분의 인공지능 기술들은 하나의 모델이 하나의 태스크만을 수행할 수 있도록 개발되고 있으며, 이는 의사들의 복잡한 판독 과정을 인공지능으로 설계하는데 한계로 작용한다. 멀티 태스크 러닝은 이러한 한계를 극복하기 위한 최적의 방안으로 알려져 있다. 다양한 태스크들을 동시에 하나의 모델로 학습함으로써, 효율적이고 일반화에 유리한 모델을 만들수 있다. 본 종설에서는 멀티 태스크 러닝에 대한 개념과 종류, 유사 개념 등에 대해 알아보고, 연구 사례들을 통해 의료 분야에서의 멀티 태스크 러닝의 활용 현황과 향후 가능성을 살펴보고자 한다.

• 대한영상의학회지
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• 제81권6호
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• pp.1274-1289
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• 2020

최근, 의료 영상 분야에서 딥러닝은 가장 활발하게 연구되고 있는 기술 중 하나이다. 충분한 데이터와 최신의 딥러닝 알고리즘은 딥러닝 모델의 개발에 중요한 요소이다. 하지만 일반화된 최적의 딥러닝 모델을 개발하기 위해서는 데이터의 양과 최신의 딥러닝 알고리즘 외에도 많은 것을 고려해야 한다. 데이터 수집부터 가공, 전처리, 모델의 학습 및 검증, 경량화까지 모든 과정이 딥러닝 모델의 성능에 영향을 미칠 수 있기 때문이다. 본 종설에서는 의료 영상에 최적화된 딥러닝 모델을 위해 개발 과정 각각에서 고려해야 할 중요한 요소들을 살펴보고자 한다.

• 융합경영연구
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• 제12권3호
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• pp.35-42
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• 2024

Purpose This study aims to investigate the correlation of social skills and metacognition among university students participating in service-learning programs. Also by evaluating the satisfaction of college students participating in service learning, this research seeks to understand the impact of this program on learning experiences. Research design, data and methodology: The research period spans two semesters, each comprising 15 weeks, from March 2, 2023, to December 20, 2023. Detailed procedures, including planning, preparation, data collection, analysis, and organization, cover activities conducted over the course of 30 weeks. These activities encompass various stages, from initial classroom planning with designated English storybooks to reflection and feedback sessions aimed at continuous development. Data collection methods include surveys, interviews, and observations, allowing for a comprehensive examination of social skills and metacognition among participating students. Results: The results show significant correlations between social skills and metacognition, such as the correlation between knowledge and statistics (r = 0.759, p < .01), the moderate correlation between cooperation and knowledge (r = 0.532, p < .01), the moderate correlation between statistics and cooperation (r = 0.539, p < .01), and the correlation between self-regulation and assertion (r = 0.278, p < .001). The average score of the satisfaction of college students participating in service learning was 4.8 out of 5. Conclusions: This study highlights the significant role of service-learning in boosting social skills and metacognition among university students. This study enhances the academic understanding of the relationships between social skills, metacognition, and service-learning programs, contributing to the expansion of both theoretical and practical knowledge in the field.

• 한국지구과학회지
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• 제35권3호
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• pp.180-191
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• 2014

본 연구에서는 전라북도 부안군 채석강 지역에 대한 3D파노라마 가상 현실 지질 답사 투어 학습자료를 개발하였다. 개발된 프로그램은 $360^{\circ}{\times}180^{\circ}$ 파노라마로서 관측 지점의 모든 면을 볼 수 있고, 확대, 축소, 화면 돌리기 등의 상호작용이 가능하다. 이 프로그램의 교육적 효과를 얻기 위해 컴파스 활용하기, 지층의 경사 등을 측정하기 위한 이동 가능한 각도기 제공, 관찰 지점의 표본에 대한 3D 관찰하기 등을 제공하였다. 또 주요 관찰 포인트에는 확대된 사진, 팝업창, 전문가 설명 등으로 학습을 도왔다. 이 프로그램의 교육적 효과를 알아보기 위하여 중학교 과학 영재반 학생 35명에게 적용해본 결과 약 85% 이상의 긍정적인 반응을 보여주었다. 따라서 이 프로그램은 중학교 과학과 지질학 수업 시 간접적 상황학습이 될 수 있고, 시간문제, 비용문제, 안전문제 등을 줄일 수 있는 하나의 보충적인 지질 답사 방법이 될 것이다.