• Journal of the Korean Chemical Society
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• v.54 no.5
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• pp.643-649
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• 2010

In this study, the relationships among high school students' epistemological views on theory and data, science process skills, the perceptions of the preferred laboratory learning environment and attitudes toward laboratory work were investigated. The results indicated that science process skills, all subcategories of the perceptions of the preferred laboratory learning environment (student cohesiveness, open-endedness, integration, rule clarity, and material environment) and attitudes toward laboratory work were significantly correlated with epistemological views on theory and data. The results of multiple regression analysis revealed that science process skills, open-endedness and material environment and attitudes toward laboratory work significantly predicted epistemological views on theory and data.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.171-179
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• 2013

Recognition and image processing technology depends on illumination variation. One of the most important factors is the parameters of algorithms. When it comes to select these values, the system has different types of recognition accuracy. In this paper, we propose performance improvement of the eye tracking system that depends on some environments such as, people, location, and illumination. Optimized threshold parameter was decided by using reinforcement learning. When the system accuracy goes down, reinforcement learning used to train the value of parameters. According to the experimental results, the performance of eye tracking system can be improved from 3% to 14% by using reinforcement learning. The improved eye tracking system can be effectively used for human-computer interaction.

• Annual Conference on Human and Language Technology
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• 2023.10a
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• pp.505-509
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• 2023

개체명 인식은 주어진 텍스트에서 특정 유형의 개체들을 식별하고 추출하는 작업이다. 일반적인 딥러닝 기반 개체명 인식은 사전에 개체명들을 모두 정의한 뒤 모델을 학습한다. 하지만 실제 학습 환경에서는 지속적으로 새로운 개체명이 등장할 수 있을뿐더러 기존 개체명을 학습한 데이터가 접근이 불가할 수 있다. 또한, 새로 모델을 학습하기 위해 새로운 데이터에 기존 개체명을 수동 태깅하기엔 많은 시간과 비용이 든다. 해결 방안으로 여러 방법론이 제시되었지만 새로운 개체명을 학습하는 과정에서 기존 개체명 지식에 대한 망각 현상이 나타났다. 본 논문에서는 지식증류를 활용한 지속학습이 한국어 개체명 인식에서 기존 지식에 대한 망각을 줄이고 새로운 지식을 학습하는데 효과적임을 보인다. 국립국어원에서 제공한 개체명 인식 데이터로 실험과 평가를 진행하여 성능의 우수성을 보인다.

• Journal of The Korean Association For Science Education
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• v.18 no.2
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• pp.201-208
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• 1998

Although cooperative learning strategies in many subject areas have been found to be effective, the effect of cooperative learning on academic achievement in science laboratory setting is not clear. Reported results on the effects of the strategies for higher achieving students are not also consistent. In this study, the cooperative learning strategies emphasizing student-centered learning which included higher order thinking activities were used in a elementary school science course. The cooperative and traditional learning groups were selected from fifth-grade classes, and taught about dissolution and solution for 16 class periods. The effects of the cooperative learning strategies upon students' academic achievement, science process skill, the attitude toward science instruction, and the perceptions of classroom environment were investigated. Two-way ANCOVA results revealed that the test scores of academic achievement and science process skill for the cooperative learning group were significantly higher than those of the traditional learning group. No interaction between the instruction and the level of previous achievement was found. The perceptions of confliction were higher in cooperative learning group. In the attitude toward science instruction and the perceptions of participation, however, no significant difference between the two groups was found. Educational implications are discussed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.515-517
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• 2013

본 논문에서는 잡음 환경 하에서 남녀 성별인식이 가능한 신경회로망에 의한 화자종속 음성인식 알고리즘을 제안한다. 본 논문에서 제안한 음성인식 알고리즘은 남성화자 및 여성화자를 인식하기 위하여 LPC 켑스트럼 계수를 사용하여 신경회로망에 의하여 학습된다. 본 실험에서는 백색잡음 및 자동차잡음에 대하여 신경회로망의 네크워크에 대한 인식결과를 나타낸다. 인식실험의 결과로부터 백색잡음에 대해서는 최대 96% 이상의 인식률, 자동차잡음에 대해서는 최대 88% 이상의 인식률을 구하였다.

• Journal of The Korean Association For Science Education
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• v.35 no.1
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• pp.27-35
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• 2015

General education is changed by accepting the change in education environment to digital generation, emphasis about student-centered education, and change of teacher's role. E-learning has taken center stage as an effective learning environment but the problems are drawn for the absence of interaction that is important in learning. In this study, on the basis of questionnaire results about learning using website, we operated blended-learning where students come and go in cyberspace and physical space to set up the lesson environment for emphasizing interaction. We selected a control group (N=40) and an experimental group (N=40) from second grade students in a middle school for this research. General instructor-led lessons were implemented in the control group and blended-learning lessons to emphasize interaction between teacher and students were implemented in the experimental group. The experiments were applied to eight class-hours in 'characteristics of matter' unit. We implemented Test of Science Related Attitude (TOSRA) to the students before and after the lessons and administered questionnaire for checking attitude changes and perception in students. The results of the test show that the experimental group students were more encouraged and became more confident and curious about scientific learning than the control group students. The analysis of the interview and results of TOSRA show that blended-learning provided guidance and feedback by the teacher to the experimental group students more than the control group students. Blended-learning is suggested as a learning-method that is helpful in improving scientific attitude in students because it enables them to express their experiences without limit of time-space and promote interaction between teacher and students.

• Journal of Korean Home Economics Education Association
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• v.18 no.2 s.40
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• pp.29-45
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• 2006

This study was to investigate the perception of middle school students on the management of the curriculum $\ulcorner$Technology Home Economics$\lrcorner$ according to the 7th National Curriculum. The subjects were 494 third grade students from middle schools located in Seoul, in order to inquire into their perceptions through the questionnaire. The collected data was analyzed with the descriptive statistics, Pearson Chi-Square, t-test, and one-way ANOVA by SPSS Win ver. 12.0 program. The major findings were as follows: Firstly there were gender differences on the interests for the subject of $\ulcorner$Technology Home Economics$\lrcorner$. The girls who were interested in the subject were much more numerous than the boys, but only in the technology part of it, the boys were more interested than the girls. Secondly the students recognized that the experiment & practice for learning $\ulcorner$Technology Home Economics$\lrcorner$ was important. They, however, recognized that its operation in school was not enough to understand the contents. The higher a student viewed the importance of the experiment & practice on $\ulcorner$Technology Home Economics$\lrcorner$, the higher his perception of its usefulness in real life. Thirdly the highest ranking of its usefulness for the contents of the subject $\ulcorner$Technology Home Economics$\lrcorner$ was identified as 'the Computer and Information Processing' and 'the Nutrients and Diet in Adolescence'. These findings suggest that the importance of the experiment & practice was enhanced and the gender differences on the usefulness of the experiment & practice on the each units were considered in order to increase the degree of the students' interest and usefulness of the $\ulcorner$Technology Home Economics$\lrcorner$

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.2
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• pp.19-26
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• 2009

This paper studies on the recognition rate change with respect to illumination variance and the confidence level of PCA(Principal Component Analysis) based face recognition by measuring the cumulative match score of CMC(Cumulative Match Characteristic). We studied on the confidence level of the algorithm under illumination changes and selection of training images not only by testing multiple training images per person with illumination variance and single training image and but also by changing the illumination conditions of testing images. The experiment shows that the recognition rate drops for multiple training image case compared to single training image case. We, however, confirmed the confidence level of the algorithm under illumination variance by the fact that the training image which corresponds to the identity of testing image belongs to upper similarity lists regardless of illumination changes and the number of training images.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.1354-1357
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• 2013

최근 다양한 센서들이 일상생활에 활용되어, 일정한 환경에서 사람의 행동을 분류하고 인식하기 위한 연구들이 활발하게 진행되고 있다. 본 연구에서는 2개의 진동센서 값과 1개의 적외선 센서 값을 은닉 마코프 모델에 적용하여 침대 위에 있는 사람의 3가지 행동유형-눕기, 뒤척임, 일어나기-을 분류하고자 한다. 3개 센서 값의 특징들을 기초로 은닉 마코프 모델에 학습시키고, 특징집합과 학습 데이터량을 변화시키면서 사람의 행동유형에 대한 인식 실험을 수행하였다. 특징 개수 혼합에 따른 인식률의 차이는 거의 없는 것으로 나타났으나, 학습 데이터량을 증가시켜 가면서 수행한 실험에서는 인식률이 평균 78.127%로 향상되는 성과를 거두었다.

• Proceedings of the Korea Information Processing Society Conference
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• 2006.05a
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• pp.315-318
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• 2006

본 논문에서는 TV OSD(On Screen Display) 메뉴 자동검증 시스템에서 문자패턴의 실시간 인식을 위한 방법론을 고찰한다. 이는 일반적인 문자인식 문제와는 달리 시스템 환경에 대한 몇 가지 가정과 제약조건을 고려해야 한다. 예컨대 문제의 특성상 카메라 및 TV 제어 기기부의 동작과 연동하는 작업 스케쥴링 기능과 실시간 분석기능 등의 요건은 시스템개발을 복잡하게 하는 반면, 주어진 OSD 메뉴 데이터로부터 검증과정은 미지 패턴에 대한 인식과정을 단순화하여 일종의 판정(decision) 문제로 고려될 수 있게 한다. 본 연구에서는 인식의 방법론으로서 수정된 구조의 FMM 신경망을 적용한다. 이는 하이퍼박스 기반의 패턴 분류기로서 간결하면서도 강력한 학습기능을 제공한다. 기존의 FMM 모델이 갖는 단점인 학습패턴에서 특징분포와 빈도를 고려하지 못한다는 점을 개선하여, 특징과 하이퍼박스간의 가중치 요소를 고려한 활성화 특성을 정의한다. 또한 실제 데이터를 사용한 실험결과를 통해 제안된 이론의 유용성을 고찰한다.