• Korean Journal of Culture and Social Issue
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• v.14 no.1_spc
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• pp.187-221
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• 2008

Although academic interest, the intersection of cognition, emotion, and motivation, is a primary goal of learning and mediates the effects of learning, the present learning environment is full of impeding factors which undermine learner's interests in learning situation. The purpose of this study is to examine current state of academic interests of Korean students and to identify several potential causes of developmental declines in academic interests. It has been consistently found that academic interests in various school subjects decrease with age and grade in school. Three potentially contributing factors to the observed loss of academic interests are mainly discussed: deprived autonomy, severe competition, and normative evaluation. Based on theories on interest and motivation, and empirical findings, various prescriptions are also suggested for designing an interest-based learning environment in order to trigger and enhance learner's academic interests.

• Proceedings of the Korean Information Science Society Conference
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• 1999.10b
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• pp.66-68
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• 1999

본 논문에서는 정보여과 시스템에서 웹 페이지를 수집하고 여과하는 과정과 사용자 프로파일을 학습하는 과정에 하이퍼링크 정보를 이용하는 방법을 제안한다. 사용자가 원하는 웹 페이지를 추천하기 위해 사용자 프로파일을 하이퍼링크 정보를 이용해 만들고 사용자의 반응(feedback)에 따라 사용자 프로파일을 조정한다. 가중치 조정에 있어서 학습 효과를 높이기 위해 사용자가 반응을 보인 웹 페이지에서 출발해 링크로 연결된 모든 페이지에 대해 깊이에 따라 가중치를 조정하는 가중치 전파 알고리즘(Weight Propagation Algorithm)을 제안한다. 적은 사용자의 반응으로도 프로파일 내의 많은 페이지에 영향을 줄 수 있어 높은 학습 효과를 기대할 수 있다.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.411-415
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• 1994

An adaptive learning control scheme by use of multilayer neural networks for compensating for uncertainties in nonlinear dynamic system is examined. Multilayer neural networks are introduced to map the uncertainties in nonlinear dynamics and perform nonlinear state feedback. Parameters of neural networks are adjusted by conventional back-propagation algorithms modified with the projection operation. Effectiveness of the proposed scheme for tracking control are demonstrated through computer simulations.

• Proceedings of the Acoustical Society of Korea Conference
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• 1997.06a
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• pp.13-16
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• 1997

본 논문에서는 Bayesian 결정 이론을 이용한 기존의 Radial Basis Function Networks 이되는 출력층에서 선형 조합되는 것과는 다른 형태의 방법을 제안하고자 한다. 제안하고자 하는 방법은 은닉층의 출력값과 가중치와의 곱해진 값이 출력층의 입력으로 들어오는데 이들 입력신호를 경쟁을 통하여 가장 큰 값만을 출력신호 인정하는 방법이다. 이런 경우에 파라미터 갱신을 할 때도 모든 가중치를 다 갱신하는 것이 아니라 출력되는 은닉층에 연결된 가중치만을 갱신하게된다. 이렇게 할 경우 계산량 감소뿐만 아니라 학습시간을 단축할 수 있다는 장점이 있다. 그리고 제안한 방법을 이용할 경우 비선형 분류문제에서도 우수한 성능결과를 확인 할 수 있었으며 기존의 RBFN rhk Wiener Filter와 성능을 비교하였다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.121-124
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• 1997

In this paper, applications of self-recurrent neural networks based of adaptive controller to position control of flexible robot link are considered. The self-recurrent neural networks can be used to approximate any continuous function to any desired degree of accuracy and the weights are updated by feedback-error learning algorithm. Therefore, a comparative analysis was mode with linear controller through an simulation. The results are presented to illustrate the advantages and improved performance of the proposed position tracking controller over the conventional linear controller.

• International Journal of Control, Automation, and Systems
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• v.6 no.4
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• pp.583-595
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• 2008

In this paper, we introduce a fuzzy nonlinear feedback approach to the control of a class of chaotic dynamical systems. The fuzzy Parallel Distributed Compensation with Reduced Rule Base approach (PDC_RRB) is proposed. The design procedure is conceptually simple and considered to a nonlinear optimal and robust control problem due to the nonlinear nature of the Takagi-Sugeno (TS) fuzzy system. Simulation results are provided to show the effictiveness of the proposed methodology.

• Journal of Engineering Education Research
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• v.19 no.1
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• pp.37-46
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• 2016

The purposes of the study were to examine engineering students' concerns and problems while they were choosing a project topic in interdisciplinary collaboration and to suggest ways to support them in an early stage of collaboration phase. To answer the research questions, we conducted a case study with engineering participants in GCTI 2015, an interdisciplinary collaborative and creative group project. Multiple data sources including focus group interviews, online survey and researchers' observation notes were used to triangulate research findings. We found four main concerns of engineering students. These concerns include (1) lack of self-efficacy, (2) limited resources, (3) lack of shared, meaningful, and common goals, and (4) lack of content knowledge. Based on these concerns we proposed four supports in an early stage of the collaborative project. These supports includes (1) implementing an orientation program, (2) providing opportunities for social interactions, (3) providing expert feedback, and (4) providing consultation for team building.

• International Journal of Contents
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• v.16 no.2
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• pp.19-29
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• 2020

In the era of noble technology, virtual reality (VR) has been adopted in various fields, with the advantages of VR in education being confirmed through numerous studies. In skill development training education, humans or equipment that interact with the trainee are crucial and currently VR is more preferred. In this study, six projects were selected and reviewed in-depth visualizing the use of VR in training and its potential. Comparison between the learning actions of training in the virtual and real environments were conducted. Training through VR is location-dependent, time-dependent, safe, and reversible. VR application is also determined by the preps and feedback-providing functionality which must be emphasized. All the advantages of VR in skill development training make it an opportunity provider. This article can be used by those developing VR projects for skill development training.

• Journal of Korea Multimedia Society
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• v.19 no.5
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• pp.826-836
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• 2016

Mastering a musical instrument for an unskilled beginning learner is not an easy task. It requires playing every note correctly and maintaining the tempo accurately. Any music comes in two forms, a music score and it rendition into an audio music. The proposed method of assisting beginning music players in both aspects employs two popular pattern recognition methods for audio-visual analysis; they are support vector machine (SVM) for music score recognition and hidden Markov model (HMM) for audio music performance tracking. With proper synchronization of the two results, the proposed music learning assistant system can give useful feedback to self-training beginners.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.40 no.8
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• pp.816-824
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• 1991

It is well known that dynamic control is needed for fast and accurate control. Neural networks are ideal for representing the strongly nonlinear relationship in the dynamic equations including complex unmodeled effects. It thus creates many advantages over conventional methods such as simple, fast and accurate control through neural network's inherent learning and massive parallelism. In this paper, dynamic control of the full six degrees of freedom of an industrial robot arm will be presented using neural networks. Moreover, through application to a real robot the usefulness of neurocontrol is demonstrated. The back propagation and feedback-error learning is used to train the neurocontroller. Simulated control of a PUMA 560 arm demonstrates that it moves at high speed with good accuracy and generalizes over untrained trajectories as well as adapt to unforseen load changes and sensor noise.