• International Journal of Advanced Culture Technology
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• v.10 no.4
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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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.11
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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.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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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.

• Proceedings of the KIEE Conference
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• 2003.11c
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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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• v.11 no.1
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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.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.1
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• pp.35-43
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• 2010

1D PCA utilized in the face appearance-based face recognition methods such as eigenface-based face recognition method may lead to less face representative power and more computational cost due to the resulting 1D face appearance data vector of high dimensionality. To resolve such problems of 1D PCA, 2D PCA-based face recognition methods had been developed. However, the face representation model obtained by direct application of 2D PCA to a face image set includes both face common features and face distinctive identity features. Face common features not only prevent face recognizability but also cause more computational cost. In this paper, we first develope a model of a face distinctive identity feature subspace separated from the effects of face common features in the face feature space obtained by application of 2D PCA analysis. Then, a novel robust face recognition based on the face distinctive identity feature subspace model is proposed. The proposed face recognition method based on the face distinctive identity feature subspace shows better performance than the conventional PCA-based methods (1D PCA-based one and 2D PCA-based one) with respect to recognition rate and processing time since it depends only on the face distinctive identity features. This is verified through various experiments using Yale A and IMM face database consisting of face images with various face poses under various illumination conditions.

• Journal of the Korean Chemical Society
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• v.66 no.5
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• pp.390-404
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• 2022

The purpose of this study was to analyze the characteristics and changes in epistemic thinking when an argument-based inquiry science class was applied in no face-to-face and face-to-face situations. Participants of this study were 113 8th grade students of four classes from a coed educational middle school in a metropolitan city. Data collection was made over one semester during which ten argument-based inquiry science lessons on five subjects were conducted in both no face-to-face and face-to-face context. As a result of comparing and analyzing students' epistemic thinking in the argumentation of each group's generating question stage, the no face-to-face classes showed higher understanding of contents and more evidence suggestion validity than face-to-face classes did. Claim validity and categories of process in argumentation were higher in face-to-face classes than No face-to-face classes. Students were able to improve their understanding of knowledge through writing by discussing rather than direct communication in no face-to-face situations, and in face-to-face situations, students showed that their thoughts were influenced by interpersonal relationships with the group members.

• Journal of the korean academy of Pediatric Dentistry
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• v.49 no.3
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• pp.310-320
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• 2022

This study aimed to evaluate the academic effectiveness of non-face-to-face classes in deciduous tooth morphology practice. Under the course name dental morphology, a total of 60 dental students took face-to-face classes while 55 pre-dental students took non-face-to-face classes. Students were required to submit their practical assignments after 5 weeks of practical classes. To evaluate the academic effectiveness of non-face-to-face classes, practical assignments were scored by an evaluator and compared with face-to-face classes using the Mann-Whitney U test and the chi-square test. The results showed that the practical score in face-to-face classes was 77.43 ± 5.97 and the practical score in non-face-to-face classes was 76.04 ± 5.83. There was no significant difference in the academic effectiveness of face-to-face classes compared to non-face-to-face classes in deciduous tooth morphology practice (p > 0.05). This study suggests that non-face-to-face classes on introductory practice such as the dental morphology course can provide comparable quality to the education taught in traditional face-to-face classes.

• International Journal of Advanced Culture Technology
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• v.11 no.2
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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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.12C
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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.