• International Journal of Advanced Culture Technology
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• 제10권4호
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• pp.304-315
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• 2022

The effect on learning satisfaction was compared and analyzed according to the interaction of learners in non-face-to-face classes. 38 students enrolled in the Department of Chemistry Education at G University in Gyeongnam were selected for the study. As a result of analyzing the change in learning satisfaction according to learners' interactions, positive correlations between them were shown in non-face-to-face classes. The type of classes mainly consisted of non-face-to-face real-time classes, and despite the non-face-to-face classes environment, learners focused on classes and put a lot of effort to strengthen learning. Among learners' interactions, the effect of learner-content interaction on learning satisfaction was relatively the highest, while the effect of learner-learner interaction and learner-instructor interaction on learning satisfaction was low. It was found that learners' teaching-learning in non-face-to-face classes relied heavily on learning content, and interactions with fellow learners and instructors were very limited.

• 한국정보통신학회논문지
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• 제26권11호
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• pp.1751-1754
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• 2022

The news articles collected with keyword "non face-to-face" were analyzed through topic modeling applied with LDA algorithm. In this study, collected articles were divided into two periods, period 1(the beginning of COVID-19 spread) and period 2(the end of COVID-19 spread), according to issued date of the articles. The articles of period 1 showed support for non-face-to-face treatment, smart library, the beginning of the online financial era, non-face-to-face entrance exam and employment, stock investment for main topic words. And the articles of period 2 showed conversion to non face-to-face classes, increasing unmanned stores, online finance, education industry, home treatment for main topic words. Also, further issues were discussed through visualization of topic words. These results provide evidence that education and unmanned business in non-face-to-face industries are growing.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2021년도 추계학술발표대회
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• pp.647-650
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• 2021

The most powerful and modern face recognition techniques are using deep learning methods that have provided impressive performance. The outbreak of COVID-19 pneumonia has spread worldwide, and people have begun to wear a face mask to prevent the spread of the virus, which has led existing face recognition methods to fail to identify people. Mainly, it pushes masked face recognition has become one of the most challenging problems in the face recognition domain. However, deep learning methods require numerous data samples, and it is challenging to find benchmarks of masked face datasets available to the public. In this work, we develop a new simulated masked face dataset that we can use for masked face recognition tasks. To evaluate the usability of the proposed dataset, we also retrained the dataset with ArcFace based system, which is one the most popular state-of-the-art face recognition methods.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 학술회의 논문집 정보 및 제어부문 B
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• pp.1006-1009
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• 2003

In this paper, we propose a technique of the recognition of partial face. Most of the research is concentrated on the recognition of whole face Since part of the face area in an image can be damaged or overlapped, face recognition based on partial face is required. PCA and LDA technique is applied to the recognition of partial face. Also, a new method to combine the results of the recognition of parts of the face.

• International Journal of Advanced Culture Technology
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• 제11권1호
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• pp.376-388
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• 2023

After a longitudinal analysis of the data on the college entrance examination of students enrolled in the Department of Chemistry Education at Gyeongnam from 2014 to 2021, the effect on the academic achievement of general chemistry according to the type of college entrance examination was studied. And the impact on the academic achievement of general chemistry according to the type of admission screening in face-to-face and non-face-to-face teaching-learning was also studied. As a result of analyzing the academic achievement of general chemistry by admission process, students admitted through occasional screening showed relatively high grades of A and B at 88.7%, and the ratio of grades of 1~3 of chemistry I in high school was high. On the other hand, in the case of students admitted through regular admission, the ratio of grades of A and B in general chemistry was very high at 94.3%, and the ratio of grades of 3~4 in chemistry I of the College Scholastic Ability Test was high. As a result of analyzing the academic achievement of general chemistry by class type and admission process, it was found that the grades of chemistry I by face-to-face classes had an effect on the academic achievement of general chemistry in non-face-to-face classes. In both admissions, the academic achievement of general chemistry by face-to-face classes was relatively higher than that of non-face-to-face-to-face classes.

• 대한전자공학회논문지SP
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• 제47권1호
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• pp.35-43
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• 2010

고유얼굴 기반 얼굴 인식 방법과 같은 얼굴 형태 기반 얼굴 인식 방법에 사용되는 1차원 PCA는 고차원의 얼굴 형태 데이터 벡터들의 처리로 인하여 부정확한 얼굴 표현과 과도한 계산량을 초래할 수 있다. 이에 개선 방안의 하나로 2차원 PCA 기반 얼굴 인식 방법이 개발되었다. 그러나 단순한 2차원 PCA 적용으로 얻어진 얼굴 표현 모델에는 얼굴 공통 특성 성분과 개인 식별 특성 성분이 모두 포함된다. 얼굴 공통 특성 성분은 오히려 개인 식별 능력을 방해할 수가 있고 또한 인식 처리 시간의 증가를 초래한다. 본 논문에서는 2차원 PCA 적용으로 얻어진 얼굴 특성 공간에서 얼굴 공통 특성 영향이 분리된 얼굴 고유 식별 특성 부분공간 모델을 개발하고 개발된 모델에 기반한 새로운 강인한 얼굴 인식 방법을 제안한다. 제안한 얼굴 고유식별 특성 부분공간 모델 기반 얼굴 인식 방법은 얼굴 고유 식별 특성에만 주로 의존하기 때문에 기존 1차원 PCA 및 2차원 PCA 기반 얼굴 인식 방법보다 얼굴 인식 성능 및 인식 속도에 대해서 더 우수한 성능을 보인다. 이는 다양한 조명 조건하에 다양한 얼굴 자세를 갖는 얼굴 이미지들로 구성된 Yale A 및 IMM 얼굴 데이터베이스를 이용한 실험을 통해 확인하였다.

• 대한화학회지
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• 제66권5호
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• pp.390-404
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• 2022

이 연구는 비대면 및 대면 상황의 논의기반 탐구 과학 수업에서 나타나는 중학생들의 인식론적 사고의 특징 및 변화를 알아보는 것을 목적으로 하였다. 이를 위해 광역시 소재의 중학교 2학년 4개 학급 113명 학생을 대상으로 비대면 상황의 5개 주제와 대면 상황의 5개 주제의 논의기반 탐구 과학 수업을 적용하였다. 비대면 및 대면 상황의 논의기반 탐구 과학 수업 진행에 따른 중학생들의 인식론적 사고 특징 및 변화를 알아보기 위하여 모둠별 의문 만들기 단계의 논의과정에서 나타나는 논의 활동의 특징과 변화를 비교 분석하였다. 연구결과, 비대면 상황의 논의기반 탐구 수업은 대면 상황의 논의기반 탐구 수업과 비교하여 내용에 대한 이해와 증거제시 타당성 항목에서 높은 수준의 사고가 나타났다. 대면 상황의 수업에서는 비대면 상황의 수업보다 주장제시 타당성과 논의과정의 전개 항목에서 높은 수준의 사고를 보였다. 비대면 상황에서는 직접적인 의사소통이 아닌 글을 바탕으로 논의가 이루어지고 이로 부터 지식에 대한 이해를 높일 수 있었고, 대면 상황에서는 모둠원들과 직접적인 의사소통으로 인한 대인 관계에 의해 영향을 받는 사고가 주로 나타났다.

• 대한소아치과학회지
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• 제49권3호
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• pp.310-320
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• 2022

이 연구는 유치 치아형태학 실습을 통해 비대면 수업의 학습 효과를 확인하고자 하였다. 유치 치아형태학이라는 과목명으로 60명의 본과 1학년 학생들은 대면으로 실습수업을 받고 55명의 예과 2학년 학생들은 비대면으로 실습수업을 받았다. 5주간의 실습수업 후 학생들은 실습 과제를 제출했다. 비대면 수업의 학습 효과를 평가하기 위해 1명의 평가자가 실습 과제를 채점했고 Mann-Whitney U 검정 및 chi-square 검정을 사용하여 대면 수업과 비교하였다. 연구 결과 대면 수업에서 실습 점수는 77.43 ± 5.97였고 비대면 수업에서 실습 점수는 76.04 ± 5.83이었다. 유치 치아형태학 실습에서 대면 수업과 비교하여 비대면 수업의 유의미한 차이는 관찰되지 않았다(p > 0.05). 이번 연구로 치아형태학 같은 비교적 실습 도구가 간단한 수업에서 비대면 수업이 대면 수업의 대안으로 사용 가능하다는 결과를 얻었다.

• International Journal of Advanced Culture Technology
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• 제11권2호
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• pp.210-220
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• 2023

We analyzed and compared factors such as changes in the degree of difficulty of concepts presented in Chemistry I textbook, changes in class types (non-face-to-face, face-to-face), etc. on academic achievement by level (upper, middle, and lower). Students from A high school in Gyeongsangnam-do were selected for the subjects of the study. As a result of analyzing the change in the degree of difficulty of concepts, the total score of chemistry I combined by non-face-to-face and face-to-face classes during the second semester was lower than that of the first semester. As a result of analyzing the impact of factors such as changes in conceptual difficulty, changes in class types, etc. on academic achievement by level, students' grades at the 'lower level' by non-face-to-face classes were lower than those by face-to-face classes. In particular, at the lower level of the second semester, there was a large difference in grades between non-face-to-face and face-to-face classes. In the results of these studies, it was found that instructors' active feedback is important to identify difficulties in understanding learning contents for students with low levels of academic achievement and improve them at the same time.

• 한국통신학회논문지
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• 제35권12C호
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• pp.984-994
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• 2010

Pose variation is a critical problem in face recognition. Three-dimensional(3D) face recognition techniques have been proposed, as 3D data contains depth information that may allow problems of pose variation to be handled more effectively than with 2D face recognition methods. This paper proposes a pose-normalized 3D face modeling method that translates and rotates any pose angle to a frontal pose using a plane fitting method by Singular Value Decomposition(SVD). First, we reconstruct 3D face data with stereo vision method. Second, nose peak point is estimated by depth information and then the angle of pose is estimated by a facial plane fitting algorithm using four facial features. Next, using the estimated pose angle, the 3D face is translated and rotated to a frontal pose. To demonstrate the effectiveness of the proposed method, we designed 2D and 3D face recognition experiments. The experimental results show that the performance of the normalized 3D face recognition method is superior to that of an un-normalized 3D face recognition method for overcoming the problems of pose variation.