• Proceedings of the Korean Society of Computer Information Conference
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• 2012.07a
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• pp.253-254
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• 2012

피아노 학습프로그램은 PC기반 자율학습의 형태로서 프로그램을 이용하여 효율적인 학습 성취도와 학습만족 도를 충족시키기는 데에 그 목적이 있다. 본 논문에서는 피아노 자율 학습프로그램의 체계, 기능설계, 모듈설계 등의 내용을 기술하고 있다. 프로그램은 올바른 학습과 평가 기준에 부합되도록 프로그램에서 정한 이수체계에 따라 각 단계마다 이론학습과 평가과정으로 구성되도록 개발하였다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2014.01a
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• pp.245-246
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• 2014

본 논문에서는 외장 전자 바이올린과 PC기반 자율학습 프로그램을 이용한 바이올린 연주 자율학습 방법을 제안한다. 외장 전자바이올린은 ATmega128 마이크로컨트롤러, 버튼, 그리고 전선으로 운지, 현과 활을 구현하였고, 블루투스 무선통신으로 PC와 데이터통신을 수행한다. PC 프로그램은 외장 전자바이올린의 연주정보를 수신하고 MIDI를 이용하여 바이올린 소리를 출력한다. 그리고 바이올린 연주에 필요한 정보를 화면에 출력하고 연주 오류 여부를 제시함으로써 저학년 학생이 바이올린 자율학습하는데 어려움 없이 이용할 수 있도록 하였다.

• Journal of the Korea Society of Computer and Information
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• v.16 no.11
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• pp.85-93
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• 2011

The music education improves the creative talent, social skills and academic achievement of the students. For the efficient music education, the learner centered study is highly recommended rather than the passive education, which supports self-control in selecting teaching materials, learning patterns and speed. For the successful self learning, it is requested to develop the collaborative educational learning tools, especially electronic collaborators such as H/W and S/W. Though there exist many commercialized electronic instruments and the PC MIDI based softwares, these tools have some limits and problems for the primary student to learn playing the musical instrument by himself. In this paper, we propose a supporting tool implementation method using an electronic keyboard instrument with USB Interface and PC-based software to help the primary student to learn playing the musical instrument. We implemented an electronic keyboard instrument module compactly and at low cost using a PIC18F4550 MCU. PC based software was developed to edit musical score, process the MIDI information, and interact with the electronic keyboard instrument module. This tool can offer a similar keyboard instrument environment and can be incorporated with self learning contents.

• Journal of the Korea Convergence Society
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• v.9 no.10
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• pp.523-531
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• 2018

The purpose of this study based on descriptive research is to examine the influences on the self-regulated learning ability due to nursing students' achievement-goal and to make sure mediating effect of autonomous support of professor. A convenience sample of 294 nursing students were recruited from a college in C province from April to May, 2018. Data are analyzed using SPSS/WIN 21.0 program. As a result, it is turned out that there are positive correlation between mastery goal, performance approach goal, self-regulated learning ability and autonomous support of professor. In the Sobel test results, autonomous support of professor had a partial mediating effect between mastery goal and self-regulated learning ability(Z=3.922, p<.001). So, a new teaching method should be developed through the convergence of related factors of self - regulated learning ability.

• Journal of Digital Convergence
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• v.15 no.3
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• pp.99-106
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• 2017

The purpose of the study is to explore the relationship among learning motive, job creativity, major satisfaction and school satisfaction of enrolled students in 2 vocational schools in Seoul. Hypotheses based on the relevant literature are tested. Job creativity was found to be positively influenced by learning motives and autonomy. Intrinsic learning motive and autonomy affect student's major satisfaction, but extrinsic learning motive was found to have negative effects on major satisfaction as autonomy trait was irrelevant to school satisfaction. Vocational college programs offer mainly technical and on-the-job training unlike general colleges. Thus, students are psychologically sensitive to school programs and multidisciplinary approach is needed.

• The KIPS Transactions:PartB
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• v.8B no.6
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• pp.675-684
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• 2001

This paper describes a method for stemming of Korean language by using unsupervised learning from raw corpus. This technique does not require a lexicon or any language-specific knowledge. Since we use unsupervised learning, the time and effort required for learning is negligible. Unlike heuristic approaches that are theoretically ungrounded, this method is based on widely accepted statistical methods, and therefore can be easily extended. The method is currently applied only to Korean language, but it can easily be adapted to other agglutinative languages, since it is not language-dependent.

• The Korean Journal of Applied Statistics
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• v.15 no.2
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• pp.251-267
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• 2002

Self Organizing Maps(SOM) by Kohonen is very fast algorithm in neural networks. But it doesn't show sure rules of training results. In this paper, we introduce to Bayesian Learning for Self Organizing Maps(BLSOM) which combines self organizing maps with Bayesian learning. So it supports explanatory power of models and improves prediction. BLSOM has global optima anywhere but SOM has not. This is proved by experiment in this paper.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.9
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• pp.999-1004
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• 2014

This intelligent keyboard instrument self learning system developed in this study consists of smartphone based learning application and keyboard-instrument auxiliary module. The keyboard instrument auxiliary module receives playing information of the instrument through smartphone application and bluetooth communication. Then the module shows it through LED display so that the relationship between the keyboard and scale could be easily recognized even for beginners. Also, this system provides saving function and analyzing function of user's performance data, making learning more effective.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.261-262
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• 2019

본 논문에서는 신경망 모델에 키보드를 통한 주행 학습을 이용하여 자율 주행을 할 수 있는 시스템을 개발하였다. 주어진 트랙에서 키보드의 방향키를 통해 전진, 후진 등 5가지의 상태로 RC카를 수동 제어하고, 제어시 카메라를 통해 얻어진 이미지를 저장해, 키 제어 데이터와 이미지 데이터를 학습시켜서 자율 주행을 할 수 있는 시스템을 구현하였다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2019.11a
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• pp.87-88
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• 2019

최근 기계학습 기술의 급속한 발전에 힘입어 자율주행을 위한 객체 인식 및 처리 기술 역시 비약적으로 발전하고 있다. 그러나 이러한 기계학습의 성능은 모델의 구조와 학습용 데이터의 품질에 영향을 받는다. 특히 주행환경을 잘 표현하는 학습데이터가 중요한데 전혀 새로운 도로, 주행환경, 장애물, 정적 혹은 동적 객체 등을 마주하면 정확도와 안정성에서 부정적인 영향을 받을 수 있는 것이다. 해외의 주행 데이터들에 크게 의존하고 있는 우리나라의 현실에 비춰 볼 때 국내 환경에 맞는 학습데이터를 쉽고 효율적으로 확보/관리/분석할 수 있게 하는 환경의 구축이 시급하다. 따라서 본 논문에서는 자율주행을 위한 기계학습 데이터를 효과적으로 관리하고 분석하기 위한 소프트웨어를 설계하고 개발하였다. 구체적으로는 수집된 영상들을 관리하는 기능, 영상에 존재하는 노이즈 제거 및 화질 개선 처리 기능, 학습 및 검증을 위한 메타 정보 태깅 기능, 태깅 정보의 통계적 분석 기능들을 포함한다. 개발한 소프트웨어는 우리나라에서 자체 촬영한 자율주행 학습 영상들에 대해 딥러닝 모델들을 학습하고 검증하는데 활용할 예정이다.