• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.4
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• pp.663-670
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• 2017

The purpose of this study is to define On-line Video Syllabus Template which is based on adaptive mode with interaction.A syllabus has the significance as a teaching and learning plan. However, it has not only been considered as a formal document, has also been limited into a simple query since it has been made into a fragmentary structure, lacking of link between other services and reuse. Additionally, this paper is aimed to design three-dimensional syllabus which makes it possible to provide students with practical information related to teaching and learning and share it with teachers and students. The following is the technique proposed in this paper. It is made to be served for the Syllabus centered on teaching and learning, which is including the definition of hierarchy structure, the media contents application according to the learner's preference and real-time variation function. On-line Video Syllabus provided through LMS has availability and credibility of teaching and learning, in that it enable increased utilization by strengthening convenience.

• Journal of Digital Convergence
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• v.11 no.2
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• pp.33-42
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• 2013

The study looks for keys to provide development direction of digital textbooks based on educational meaning and roles for increasing satisfaction of teacher and student uses in educational activities. In the paradigm shift toward learner-centered pedagogy, digital textbooks have been actively discussed in exploiting the pedagogical ideas, such as multimedia learning, self-regulated learning, deeper learning, and collaborative learning, offered by the technology. In the study, we discuss the concept and historical background of digital textbooks based on the changes of pedagogical paradigm, and then we discuss fundamental functionality, effectiveness, physical and psychological impact, and cognitive aspects to empower the use of digital textbooks in public education system.

• Journal of Korea Multimedia Society
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• v.12 no.10
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• pp.1486-1498
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• 2009

Modem efforts on digitizing electronic books focus on preserving authentic image representation of the original sources. Unlike the text-based format, it is difficult to recognize the information in the image, so the new format requires new tools to help users to access, process, and make sense of digital information. This paper presents an approach which assists users of these image sources by giving them a combination of annotation and social navigation support. Especially in the education domain, the proposed technique improves the usability of online education system. This approach is currently fully implemented and under evaluation in a classroom study.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.05a
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• pp.705-707
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• 2022

인체의 흉부 X-ray 영상으로부터 척추질환과 관련된 의료 진단지표를 자동으로 추출하는 과정을 위하여 흉추조직의 정확한 분할이 필요하다. 본 연구에서는 HRNet 기반의 학습을 통하여 흉추조직을 분할하는 방법을 고찰한다. 분할 과정에서 영상 내의 상대적인 위치 정보가 효과적으로 반영될 수 있도록, 계층별로 영상의 고해상도의 표현이 그대로 유지되는 구조와 저해상도의 특징 지도로 변환되는 구조가 병렬적으로 연결되는 형태의 심층 신경망 모델을 채택하였다. 흉부 X-ray 영상에서 콥각도(Cobb's angle)를 산출하는 문제를 대상으로 흉추 분할을 위한 학습 방법, 진단지표 추출 방법 등을 소개하며, 부수적으로 피사체의 위치 변화 및 크기 변화 등에 강인한 성능을 제공하기 위하여 학습 데이터를 증강하는 방법론을 제시하였다. 총 145개의 영상을 사용한 실험을 통하여 제안된 이론의 타당성을 평가하였다.

• Journal of The Korean Association of Information Education
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• v.14 no.2
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• pp.229-240
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• 2010

The purpose of this paper is to develop and apply an electronic English textbook for the teaching and learning of 3rd grade students. For this purpose, the textbook was based on XML to maximize the advantages of the electronic textbook format, and avoid the disadvantages of the CD-ROM that $3^{rd}$ grade classes currently use. After electronic textbook was developed, focus group interview was implemented to confirm the effectiveness of that based on interaction, satisfaction, and interests. As a result of this study, interaction, satisfaction, and interests of students will be improved through the use of electronic textbook and it is anticipated self-directed learning ability will be improved. Also, we anticipate that the students' learning effectiveness will be enhanced.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.38 no.4
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• pp.11-19
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• 2001

In this paper, we study the convergence property of iterative learning control (ILC). First, we present a new method to prove the convergence of ILC using sup-norm. Then, we propose a new type of ILC algorithm adopting intervalized learning scheme and show that the monotone convergence of the output error can be obtained for a given time interval when the proposed ILC algorithm is applied to a class of linear dynamic systems. We also show that the divided time interval is affected from the learning gain and that convergence speed of the proposed learning scheme can be increased by choosing the appropriate learning gain. To show the effectiveness of the proposed algorithm, two numerical examples are given.

• The KIPS Transactions:PartD
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• v.13D no.3 s.106
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• pp.369-376
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• 2006

This paper presents a new method of significantly improving conventional Bayesian statistical text classifier by incorporating accelerated EM(Expectation Maximization) algorithm. EM algorithm experiences a slow convergence and performance degrade in its iterative process, especially when real online-textual documents do not follow EM's assumptions. In this study, we propose a new accelerated EM algorithm with uncertainty-based selective sampling, which is simple yet has a fast convergence speed and allow to estimate a more accurate classification model on Naive Bayesian text classifier. Experiments using the popular Reuters-21578 document collection showed that the proposed algorithm effectively improves classification accuracy.

• The Journal of Society for e-Business Studies
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• v.18 no.3
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• pp.177-193
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• 2013

The study investigated how did Credu pioneer Korean e-Learning market and reinforce their core competencies and how did they promote business diversification analyzing type of learning motives and examining Credu real cases. Under the fierce competition in the current e-Learning market, Credu has maintained their core competencies and strengthened an active communication channels with customers with focusing on investment to core businesses. Credu has introduced more adventurous and challenging products and services with creating a new model for the types of learning motives. This study could introduce the new perspective about the type of learning motives in e-Learning area. Also, the case study of successful e-Learning company, Credu, could contribute to make more spread e-Learning market techniques in this field in practice.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.40 no.2
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• pp.19-25
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• 2003

For a class of multi-input multi-output nonlinear systems which perform a given task repetitively, an extended type of a direct leaning control (DLC) is proposed using the information on the (vector) relative degree of a multi-input multi-output system. Existing DLC methods are observed to be applied to a limited class of systems with the relative degree one and a new DLC law is suggested which can be applied to systems having higher relative degree. Using the proposed control law, the control input corresponding to the new desired output trajectory is synthesized directly based on the control inputs obtained from the learning process for other output trajectories. To show the validity and the performance of the proposed DLC, simulations are performed for trajectory tracking control of a two-axis SCARA robot.

• Journal of IKEEE
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• v.24 no.4
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• pp.991-997
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• 2020

Reinforcement learning has been applied mainly in sequential decision-making problems. Especially in recent years, reinforcement learning combined with neural networks has brought successful results in previously unsolved fields. However, reinforcement learning using deep neural networks has the disadvantage that it is too complex for immediate use in the field. In this paper, we implemented path planning algorithm for mobile robots using Q-learning, one of the easy-to-learn reinforcement learning algorithms. We used real-time Q-learning to update the Q-table in real-time since the Q-learning method of generating Q-tables in advance has obvious limitations. By adjusting the exploration strategy, we were able to obtain the learning speed required for real-time Q-learning. Finally, we compared the performance of real-time Q-learning and DQN.