• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2021.06a
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• pp.10-13
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• 2021

본 논문에서는 과다 노출된 영상을 영상 간 변환(Image-to-Image Translation)을 위해 설계된 적대적 생성 신경망(Generative Adversarial Network)을 활용하여 복원하는 연구를 수행한다. 과다 노출 복원을 위한 기존의 연구에서 과다 노출 영역 판별, 밝기 회복, 색상 보정 과정을 거치는데, 영상 내 과다 노출 영역을 판별하는 과정에서 임의로 결정하는 파라미터에 의해 복원된 영상 결과가 달라지는 한계점을 극복하기 위해 종단간(End-to-End) 신경망을 학습시켜 과다 노출 영역을 별도의 파라미터 선택과 분할된 과정 없이 한 번에 복원하는 방법을 제안한다. 영상 간 변환 신경망 학습에 필요한 과다 노출 여부로 도메인이 분할된 데이터셋은 게임 소프트웨어를 활용하여 만들어 사용하였다. 본 연구에서는 신경망이 생성한 영상이 실제로 과다 노출 영역을 탐지하여 복원하는 것을 확인하였다. 그리고 과다 노출 영역을 탐지하여 복원하는 과정을 학습 단계별로 확인함으로써 신경망이 실제로 과다 노출 복원 과정을 학습함을 보였다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.321-324
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• 2004

본 논문에서는 유도전동기 고장진단을 위하여 계층적인 하이브리드 뉴럴네트웍을 제안하였다. 시스템의 입출력 데이터에 근거하여 패턴을 분류하고자 할 때 직접적인 분류가 어렵거나 성능이 좋지 않을 경우 적절한 방법을 통하여 변환을 하거나 또는 패턴 분류기의 특성에 맞도록 변환하여 패턴 분류 성능을 향상하는 등 단계별 변환 및 분류 기법을 이용하였다. 제안된 방법에서는 실험에 의해 측정된 전류값을 주기별로 주성분분석(PCA) 기법을 이용하여 입력차원을 축소한 후 이를 조건부 FCM으로 방사기저함수의 초기치를 최적화하여 학습을 하였다. 이는 주성분분석이 가지는 특성을 이용하여 데이터의 특징을 나누었으며 이를 뉴럴네트웍의 학습 기능을 이용하여 모델의 최종 성능을 개선하는 것이다. 각각의 알고리즘이 가지는 특징을 활용하면서도 단점을 계층적으로 보안하여 유도 전동기 고장 진단 성능을 개선하였다. 이를 실제 계측된 유도전동기 데이터를 이용하여 제안된 방법의 유용성을 보이고자 한다.

• Annual Conference on Human and Language Technology
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• 2002.10e
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• pp.98-102
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• 2002

초등학교 교과서에 사용된 어휘의 수준을 보기 위해 교과서에 쓰인 어휘의 사용 빈도를 포함하여 결정에 영향력을 미칠 요소를 파악하고 요소간의 관계를 설립하여 교육용 어휘 설정의 나아갈 방향을 제시하는데 목적이 있다. 7차 교육과정에 있는 초등학교 교과서에서 국어 어휘 교육 관련 항목을 살펴 이들의 단계별 학습 수준의 고려가 이루어져 있는지를 검토하고자 한다. 수준별 교육 과정에서 밝히고 있는 어휘 의미 교육의 위계가 세부적이고 치밀한 수준의 적정성을 바탕으로 하여 구성되어 있는지를 검토하고 초등학교 교육용 어휘 선정의 문제 분석을 통해 기본 어휘와 기초 어휘 분류의 적정 기준과 학습 활동에 있어 언어 사용 능력으로서의 어휘력과 언어 체계 속의 어휘력을 구분할 필요가 있음을 설명하고자 한다.

• Journal of The Korean Association of Information Education
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• v.20 no.5
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• pp.465-474
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• 2016

The present study is aimed to find the effect of the activity of writing a structured reflection journal in the learning process of PBL-based programming on the logical thinking of elementary school students. To achieve the objective, this study carried out an experiment with 59 elementary school students in the 5th grade. They were divided into an experimental group and a control group. The experimental group was applied with PBL-based programming classes by learning step, including learning of the contents, its procedure, and the activities of writing a critical reflection journal while the control group received learning of PBL-based programming including unstructured reflection journal. And then the difference in their logical thinking was compared and analyzed before and after th experiment. The results demonstrated that the experimental group showed a significant difference in logical thinking before and after writing structured reflection journal (ANCOVA) at the significance level of .05, which evidenced writing a structured reflection journal has learning effect. Intergroup comparison of logical thinking also showed that there was learning effect. Those findings suggest that writing a structured reflection journal in the PBL-based programming learning for 5th grade elementary school students has a positive effect on the learners' logical thinking.

• Proceedings of the Korean Society of Computer Information Conference
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• 2017.07a
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• pp.356-357
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• 2017

프로그래밍 언어 수업은 단계별 학습 특성으로 인해 이전 단계를 이해하지 못하면 그 다음 단계로 넘어가는데 어려움이 많아, 학습 공백기를 갖는 복학생들에게는 복학 후 수업 적응에 보다 큰 어려움이 있다. 이러한 어려움을 극복하고 수업 적응 효과를 높이기 위해서는 수업 시작 전 이전 수업 내용 및 운영 방법 등을 알 수 있는 적절한 기회와 방법이 필요하다. 본 연구에서는 사전교육 프로그램을 프로그래밍 수업에 적용한 후 설문조사를 실시하여 사전교육 프로그램이 복학생들의 프로그래밍 언어 수업에 대한 적응 효과 및 만족도를 높이는 긍정적인 효과가 있었음을 조사 분석하였다.

• Journal of Korean Home Economics Education Association
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• v.23 no.1
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• pp.87-111
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• 2011

The purpose of this study was to develop and evaluate practical problem-based Home Economics lesson plans applying to the multiple intelligence teaching learning strategy, focused on the unit 'Nutrition & Meals' of middle school Home Economics subject matter. To achieve this purpose, the lesson plans were developed and evaluated from the 72 middle school students in Chongju after implementing the instruction. The data from the questionnaire were analyzed by SPSS/WIN 12.0 and content analysis. The results were as follows: First, the objectives of practical problem-based 'Nutrition & Meals' Instruction using multiple intelligence teaching strategy were to understand the importance of nutrition and health in an adolescent period and to develop good eating habits. The Practical Problem was 'What should I do for good eating habits?' and the learning contents were healthy life, the kinds and functions of nutriments, food pyramid and a food guide. The learning activities were progressed by various types of teaching and learning methods including 8 types of multiple intelligence teaching strategy. The lesson plans were developed according to the process of practical problem solving model. 6 periods of lesson plans and worksheets were developed. Second, the practical problem-based instruction using multiple intelligence teaching-learning strategy were evaluated to increase students' positive learning attitudes, motivation, and good eating habits.

• Journal of Korea Entertainment Industry Association
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• v.14 no.8
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• pp.467-476
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• 2020

The purpose of this study is as a base study for improving the quality of online classes through multilateral analysis that examines the learning outcoms of educational quality and learning emotions on non-face-to-face online classes at Technical Colleges To this study, from March 1, 2020 to August 31, 2020, a survey was conducted on 1,000 students of H Technical Colleges located in the metropolitan area. The collected data were statistically processed using the SPSS Statistics 18.0 program, t-validation were performed to reveal awareness of online class also correlation analysis and multiple regression analysis were performed to reveal the relation and influence of factors related to quality of instruction, learning emotions, learning outcomes. First, there was a statistically significant difference in perception of online classes by gender and grade. Second, there was a positive correlation between the educational quality, learning emotions, and learning outcomes for online classes. Third, among the learning outcomes, the factors that influence the achievement were the educational content and positive emotions, and the factors that influence the satisfaction among the learning outcomes were the educational content and the learning environment.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.7
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• pp.807-812
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• 2015

Lifelong education is a periodic keyword. For a lifelong learner friendly education, university should provide the adult learners with the efficient academic administrative service. A university should support them in learning a series of graded lifelong study and come up with the convenience of continuous learning, maintaining the educational operation as a lifelong education university. A local government induces the regional economy reinvigoration from setting the lifelong learning conditions of the city. In this paper, I suggest a policy management scheme for opening training courses of 3D printing and CAD professionals training module as a non-degree reeducation programs for the lifelong learners that reflects the industrial milieu of the local community.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.35-42
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• 2021

The college English teaching-learning model in this study is intended to effectively apply dictogloss activities to enhance competencies such as communication, self-directedness, and cooperation by upgrading the utilization of various online platform functions. Dictogloss is a language teaching and learning activity that combines four functions (listening, speaking, reading, and writing) of communication. College English classes in this study focus on communication-oriented integrated English education. In this study, the teaching and learning is an online-based English integrated teaching-learning method based on constructivism theory. The model presented the roles of learners and teachers according to the seven procedures.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.3
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• pp.367-371
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• 2006

Multilayer percepteon has the advantage of learning their optimal parameters and efficiency. However, MLP shows some drawbacks when dealing with high dimensional data within the input space. Also, it Is very difficult to find the optimal parameters when the input data are highly correlated such as large scale face dataset. In this paper, we propose a novel technique for face recognition based on LDA and local MLP. To resolve the main drawback of MLP, we calculate the reduced features by LDA in advance. And then, we construct a local MLP per group consisting of subset of facedatabase to find its optimal learning parameters rather than using whole faces. Finally, we designed the face recognition system combined with the local MLPs. From various experiments, we obtained better classification performance in comparison with the results produced by conventional methods such as PCA and LDA.