• Journal of Technologic Dentistry
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• v.42 no.4
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• pp.379-387
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• 2020

Purpose: This study aimed to explore methods to improve the quality recognition and satisfaction level of non-face-to-face lectures among students in the departments of dental technology and dental hygiene. Methods: This survey was conducted to assess the status and preference of non-face-to-face lectures and the level of awareness and satisfaction regarding the quality of these lectures among 179 students of dental technology and 295 students of dental hygiene. Statistical analyses were performed using frequency analysis, independent sample t-test, one-way ANOVA (post-hoc Duncan), Welch analysis (post-hoc Games-Howell), and hierarchical multiple regression analysis. Results: Factors that affected the ability to assess the quality of non-face-to-face lectures were the department, the method of non-face-to-face lectures, the most preferred method for conducting lectures, the level of awareness regarding the quality of face-to-face lecture, and satisfaction level. It has 71.5% explanatory power. Moreover, factors that influenced the satisfaction level of non-face-to-face lectures included the department, grade, the highest satisfied non-face-to-face teaching method, the most effective theoretical non-face-to-face teaching method, the most preferred teaching methods, and the ability to assess quality of face-to-face lectures. It has 46.8% explanatory power. Conclusion: Non-face-to-face classes should be designed and developed for web-based programs to improve the motivation and achievement level of the students and encourage interaction between the professors and students. Our findings suggest that educators should strive to achieve optimal educational effects by efficiently combining face-to-face and non-face-to-face lectures.

• 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.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.2
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• pp.11-20
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• 2010

In this paper we propose a face detection system which consists of a method of face candidate extraction using skin color and a method of face verification using the feature of facial structure. Firstly, the proposed extraction method of face candidate uses the image segmentation and merging algorithm in the regions of skin color and the neighboring regions of skin color. These two algorithms make it possible to select the face candidates from the variety of faces in the image with complicated backgrounds. Secondly, by using the partial face classifier, the proposed face validation method verifies the feature of face structure and then classifies face and non-face. This classifier uses face images only in the learning process and does not consider non-face images in order to use less number of training images. In the experimental, the proposed method of face candidate extraction can find more 9.55% faces on average as face candidates than other methods. Also in the experiment of face and non-face classification, the proposed face validation method obtains the face classification rate on the average 4.97% higher than other face/non-face classifiers when the non-face classification rate is about 99%.

• Journal of Korea Multimedia Society
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• v.11 no.6
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• pp.777-786
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• 2008

Human face avatar is important information in nowadays, such as describing real people in virtual world. In this paper, we have presented a face avatar creation and warping algorithm by using face feature analysis method, in order to detect face feature, we utilized local mean method based on facial feature appearance and face geometric information. Then detect facial candidates by using it's character in $YC_bC_r$ color space. Meanwhile, we also defined the rules which are based on face geometric information to limit searching range. For analyzing face feature, we used face feature points to describe their feature, and analyzed geometry relationship of these feature points to create the face avatar. Then we have carried out simulation on PC and embed mobile device such as PDA and mobile phone to evaluate efficiency of the proposed algorithm. From the simulation results, we can confirm that our proposed algorithm will have an outstanding performance and it's execution speed can also be acceptable.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.187-194
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• 2021

This paper presents a margin-based face liveness detection method with behavioral confirmation to prevent spoofing attacks using deep learning techniques. The proposed method provides a possibility to prevent biometric person authentication systems from replay and printed spoofing attacks. For this work, a set of real face images and fake face images was collected and a face liveness detection model is trained on the constructed dataset. Traditional face liveness detection methods exploit the face image covering only the face regions of the human head image. However, outside of this region of interest (ROI) might include useful features such as phone edges and fingers. The proposed face liveness detection method was experimentally tested on the author's own dataset. Collected databases are trained and experimental results show that the trained model distinguishes real face images and fake images correctly.

• Journal of Korean Dental Hygiene Science
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• v.4 no.2
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• pp.53-65
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• 2021

Background: To survey and analyze awareness and recognition during a non-face-to-face lecture, and satisfaction with among dental technology students. Methods: Total 179 undergraduates were surveyed from the Department of Dental Technology. Frequency analysis, cross analysis, independent sample t-test, correlation analysis, and multiple regression analysis were used for analyzing statistics. Results: Overall satisfaction with the non-face-to-face lecture was the highest (p=.037) while watching a recorded lecture in the theory curriculum subject. In the case of practical subjects, satisfaction with face-to-face lectures appeared to be higher (p=.039) compared to non-face-to-face lectures. Factors influencing the recognition of non-face-to-face lecture quality included awareness of a place to conduct a class and of face-to-face delivered lecture quality, satisfaction with face-to-face lecture, and satisfaction with non-face-to-face lecture. Factors affecting satisfaction with a non-face-to-face lecture included a place to conduct a class, the most effective theory non-face-to-face class method, the method of having been experienced the most among non-face-to-face lecture methods, and the recognition of non-face-to-face lecture quality. Conclusions: Future educational environment should include combined face-to-face and non-face-to-face lectures. An efficient educational indicator will be needed to evaluate learners' assessments and opinions about online classes, followed by its application to teaching methods.

• The Journal of Information Systems
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• v.29 no.4
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• pp.45-56
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• 2020

Purpose The purpose of this study is to present the direction of efficient e-learning education through the importance and satisfaction survey of learners of non-face-to-face video lectures. Therefore, by grasping the degree of satisfaction of the importance ratio through the IPA analysis method, we try to present improvement measures for insufficient education methods. Design/methodology/approach For IPA analysis, we conducted an online survey of four universities and analyzed 154 samples. The analysis method used SPSS, and through the wordcloud analysis method of R, the suggestions for the non-face-to-face lecture method felt by learners were analyzed to derive implications for improving the quality of education. Findings As a result of the overall satisfaction survey for the entire non-face-to-face class, the factors with the greatest dissatisfaction are listed as follows. Complaints about the adequacy of learning materials and activities (quiz, discussion, assignments, etc.), Complaints about how to use the produced content, and complaints about announcements about class management (lecture schedule, lecture method) were identified in order. The factors of dissatisfaction were clear in the non-face-to-face class where interactive communication was impossible or insufficient. In addition to the lack of quick Q&A, there seems to have been a phenomenon of some neglect.

• Proceeding of Spring/Autumn Annual Conference of KHA
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• 2009.04a
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• pp.230-235
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• 2009

In our country, the application of the design method of face to face dimension in wall-slab apartment has passed 10 years. So MC design method has fixed in the design step to some degree. In Design and Work Execution of House the exclusive area of the apartment was calculated by face to face dimension. And the term of face to face dimension was known broadly to clients, construction company, etc. But design method of face to face dimension is not to simply extend the room size so far as wall depth in design process but to ensure the actual space should be considered with efficient use and assembly of building components. That is to say, Design method of face to face dimension is not to be defined by design step but to be related with construction and maintenance. However in construction process the point of face to face design method was not understood even now. So the purpose of this study was to extract the effect and question of face to face design method in construction process by survey of actual condition of structure and construction quality, and compare this result with existing construction method. The following project of this study is to survey of actual condition of interior components such as gypsum board, windows & doors etc. Therefore this study is to induce architectural long-life through architectural standardization construction and component's exchange, and, by the subject of the study on Apartment to have design guideline and basis for joining part between Gypsumboard and windows.

• Journal of the Korean housing association
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• v.20 no.4
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• pp.31-38
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• 2009

In our country, the application of the design method of face to face dimension in wall-slab apartment has passed 10 years. So MC(Modular Coordination) design method has fixed in the design step to some degree. In Design and Work Execution of House the exclusive area of the apartment was calculated by face to face dimension. And the term of face to face dimension was known broadly to clients, construction company, etc. But design method of face to face dimension is not to simply extend the room size so far as wall depth in design process but to ensure the actual space should be considered with efficient use and assembly of building components. That is to say, Design method of face to face dimension is not to be defined by design step but to be related with construction and maintenance. However in construction process the point of face to face design method was not understood even now. So the purpose of this study was to extract the effect and question of face to face design method in construction process by survey of actual condition of structure and construction quality, and compare this result with existing construction method. The following project of this study is to survey of actual condition of interior components such as gypsum board, windows & doors etc. Therefore this study is to induce architectural long-life through architectural standardization construction and component's exchange, and, by the subject of the study on Apartment to have design guideline and basis for joining part between Gypsumboard and windows.

• Proceedings of the Korea Contents Association Conference
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• 2003.11a
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• pp.223-226
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• 2003

When we detect side-view face in color image, we decide a candidate face region using skin-tone color, and confirm to the face by template matching. Cang Wei use a left and a right template of face, calculate to similarity value by hausdorff method, and decide the final side-view face. It has a characteristic that side-view face is wide spreading neck region. To get exactly result, face region is separated vertically by 3 pixel unit, and matched template. In this paper, we assume that a side-view face is a right side-view or a left side-view face. We separate a half of the candidate face region vertically, and regard a left side as left candidate face, a right side as right candidate face by template matching. This method detect faster than Gang Wei method.