• Archives of design research
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• v.16 no.4
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• pp.443-452
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• 2003

This study is to find out the possibility of applying the Blended Learning which combines the advantage of face-to-face classroom instruction and e-Learning to design education. This Blended Loaming Model has five steps such as 'prepare, teach, show, interact, and collaborate'. It is designed by the learning decision points (performance outcomes, content stability and structure, audience size, and so on) and the characteristics of delivery methods(asynchronous, synchronous). This research is based on the learners' satisfaction data of each step. The number of the participants is 27 and a questionnaire with 21 items is administered. Ten items of them are designed with 5-point Likert scales and the rest of them ask learners describe the reason of their selection. The result show that learners are satisfied with the blended learning than the off-line classroom. It is expected that the blended learning can be a substitute of the off-line classroom for the effectiveness of design education.

• Journal of Korea Game Society
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• v.4 no.3
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• pp.49-54
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• 2004

The social interest for collaborative teaming and educational game has been increased. In this paper, we investigated the educational value of collaborative teaming and game. Based on this investigation, we propose an educational on-line game model for collaborative teaming. Although the proposed model is still conceptual design, it sufficiently shows that on-line RPG game can be a good collaborative teaming method for young children. We will perform a comparison study on the teaming achievement between the two methods: 1) the on-line game proposed in this paper, 2) the conventional educational method performed in normal school.

• Communications of Mathematical Education
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• v.19 no.4 s.24
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• pp.769-785
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• 2005

The affirmative feature which web based learning and problem based learning in the self directed learning having on-line and off-line study it amalgamates in connection Blended Learning method and specially in mathematics subject as a service course. We introduce a model of BL lecture of Mathematics and tried to find a new way for the quality improvement of university education.

• 한국정보교육학회:학술대회논문집
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• 2005.08a
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• pp.13-20
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• 2005

본 논문에서는 on-line을 통한 교육방법의 하나인 e-learning(Web Based Instruction)을 활용한 음악과 수업모형을 개발하여 교육적 활용 효과를 검증하였다. 웹 기반 교수학습 자료를 구축하고 각종 학습 자료를 탑재하여 수업에 활용하였으며, 교육 효과를 보다 정확히 알아보기 위해 수준별(상,중,하) 3개 그룹으로 나누어 e-learning 기법을 적용 사전평가 및 사후평가를 통하여 얻어진 결과를 통계 처리하여 검증하였다. 본 논문에서는 학습자의 능력과 필요에 따라 능동적인 학습이 이루어지도록 하였다. 개별학습, 반복학습 및 자기주도적 학습을 진행할 수 있도록 구성하였으며, 그 결과 구체적이고 실질적인 학습 효과를 얻을 수 있었다. e-learning 활용수업을 실시한 실험 집단 전체에서 off-line 수업을 실시한 통제집단보다 학습 성취도에 있어서 효과적인 것을 확인할 수 있었다. 상위, 중위 그룹의 학생들에게는 웹 기반 교수학습 활용수업이 학습효과에 있어서 큰 차이가 없었지만 하위 그룹의 학생들에게는 크게 효과적인 것으로 나타났다.

• International Journal of Contents
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• v.1 no.2
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• pp.10-12
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• 2005

Along with development of the Internet, education is achieved on-line actively. Therefore, interest about computer aided learning is growing. By a lot of advantages such as expense and time-saving side, this type of learning is widening area gradually. In this paper we discuss some of the learning technology, such as e-learning, m-learning, and u-learning.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.343-346
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• 1996

A new method for on-line induction motor fault detection is presented in this paper. This system utilizes unsupervised-learning clustering algorithm, the Dignet, proposed by Thomopoulos etc., to learn the spectral characteristics of a good motor operating on-line. After a sufficient training period, the Dignet signals one-phase ground fault, or a potential failure condition when a new cluster is formed and persists for some time. Since a fault condition is found by comparison to a prior condition of the machine, on-line failure prediction is possible with this system without requiring information on the motor of load characteristics.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.14 no.1
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• pp.52-57
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• 2005

In the foe of global competition, the requirements for the continuously increasing productivity, flexibility and quality(dimensional accuracy, mechanical properties and surface properties) have imposed a mai or change on steel manufacturing industries. Indeed, one of the keys to achieve this goal is the automation of the steel-making process using AI(Artificial Intelligence) techniques. The automation of hot rolling process requires the developments of several mathematical models for simulation and quantitative description of the industrial operations involved. In this paper, an on-line training neural network for both long-term teaming and short-term teaming was developed in order to improve the prediction of rolling force in hot rolling mill. This analysis shows that the predicted rolling force is very closed to the actual rolling force, and the thickness error of the strip is considerably reduced.

• Proceedings of the KIEE Conference
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• 2004.07e
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• pp.27-29
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• 2004

This paper presents improved teaching and learning Gill for easily analysis tool of load flow of power system. This GUI includes not only contingency analysis function, but also calculating power loss from transmission line flow. The Gill is friendly for study for power system operation and control because picture provide a better visualizing of relationships between input parameters and effect than a tabula type result. This Gill enables topology and the output data of load flow for line outages to be shown on same picture page. Users can input the system data for power flow on the the picture and can easily see the the result diagram of bus voltage, bus power, line flow. It is also observe the effects of different types of variation of tap, shunt capacitor, loads level, line outages. Proposed Gill has been studied on the Ward-Hale 6-Bus system.

• The Journal of Korea Robotics Society
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• v.14 no.1
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• pp.1-7
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• 2019

Recently, smart factories have attracted much attention as a result of the 4th Industrial Revolution. Existing factory automation technologies are generally designed for simple repetition without using vision sensors. Even small object assemblies are still dependent on manual work. To satisfy the needs for replacing the existing system with new technology such as bin picking and visual servoing, precision and real-time application should be core. Therefore in our work we focused on the core elements by using deep learning algorithm to detect and classify the target object for real-time and analyzing the object features. We chose YOLO CNN which is capable of real-time working and combining the two tasks as mentioned above though there are lots of good deep learning algorithms such as Mask R-CNN and Fast R-CNN. Then through the line and inside features extracted from target object, we can obtain final outline and estimate object posture.

• The KIPS Transactions:PartA
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• v.16A no.5
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• pp.403-410
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• 2009

In this paper, we present an on-line quiz authoring software that helps teachers create an intelligent on-line quiz. It is designed to give each student appropriate diagnostic report using Bayesian inference networks that represent the relationships among knowledge-items. Once the authors design and edit quizzes in quiz authoring page, the authoring tool automatically produces a knowledge-model based on Bayesian inference network, on-line quizzes, and student report pages. It turns out that the on-line quizzes generated by this tool help students identify their weak parts of subject, make learning strategies for the next learning steps and carry out supplementary learning for their weak knowledge-items.