• Journal of Korean Academy of Dental Administration
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• v.9 no.1
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• pp.44-50
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• 2021

Owing to the Corona virus (COVID-19) crisis, virtual education has been expanded. Accordingly, this study was conducted to determine the direction of oral health education by examining participants' satisfaction with virtual education and educational media preferences. This study collected data from a Naver Form online survey targeting 290 university students across the country, from May 10 to 31, 2021. The collected data were analyzed using IBM SPSS 20.0. According to the data, satisfaction with virtual classes was 3.36 points in 5-point Likert scale, satisfaction factors were reduced commuting time and money expenditure, and the highest dissatisfaction factor was a decrease in lecture concentration. The media platform that most interested students pursing oral health education was YouTube. The oral health education that participants wished to receive through virtual education included how to prevent tooth decay, how to prevent gum disease, and how to brush teeth. In conclusion, it is necessary to develop various media like Zoom, YouTube, and virtual reality programs so that students feel motivated to utilize oral health education and improve oral health.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.31-33
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• 2009

Face detection using AdaBoost algorithm is capable of processing images rapidly while having high detection rates. It seemed to be the fastest and the most robust and it is still today. Many improvements or extensions of this method have been proposed. However, previous approaches only deal with upright faces. They suffer from limited discriminant capability for rotated faces as these methods apply the same features for both upright and rotated faces. To solve this problem, it is necessary that we rotate input images or make independently trained detectors. However, this can be slow and can require a lot of training data, since each classifier requires the computation of many different image features. This paper proposes a robust algorithm for finding rotated faces within an image. It reduces the computational and sample complexity, by finding common features that can be shared across the classes. And it will be able to apply with multi-class object detection.

• Journal of Engineering Education Research
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• v.26 no.1
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• pp.12-19
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• 2023

With the introduction of the accreditation of engineering programs in Korea, universities affiliated with the programs have opened introductory engineering design courses for first- or second-year students. Since these courses mainly aim at cultivating problem-solving skills through team projects, this type of classes has opened as face-to-face classes. However, from the beginning of 2020, online teaching was recommended or forced on universities due to the COVID-19 pandemic. Thus, effective design of online courses on introductory engineering design was inevitable during the period. In this paper, we introduce a case study of the course in the Department of Computer Science at S University in Fall 2021. Through concrete suggestions on project areas, selection of team members considering grade levels and interest, several systems for prevention of free riding, and carefully designed open-book exams, the course resulted in both high achievements and high satisfaction.

• Journal of Information Technology Applications and Management
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• v.28 no.1
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• pp.33-41
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• 2021

In this study, we estimated the number of secondary COVID-19 infections caused by students with potential transmission potential home. When the existing Monte Carlo method was applied to Korean data, the average number of household members of the second COVID-19 infected was predicted. The summary of this study is as follows. First, in general, the number of secondary infections by students returning home from school is greatly influenced by the virus infection rate of each student group they contact while returning home from school. Korea-based empirical research on this is needed. Second, the number of secondary infections by Korean students was relatively lower than that of previous studies. This can be interpreted as being due to the domestic furniture structure. Third, unlike previous studies that assumed the distribution of secondary infected individuals as normal distribution, assuming a negative binomial distribution, the number of secondary infected individuals was sensitively changed according to the estimated parameters. Interpretation of this result shows that the number of secondary infections may vary depending on the time of decision making, the target region, and the target student group. Finally, according to the results of this analysis, a proposal was made to support education policy decisions.

• Journal of the Korean Society for Library and Information Science
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• v.55 no.4
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• pp.267-291
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• 2021

Due to the global pandemic caused by COVID-19 in 2020, there have been major changes in the education sites. Universities have fully introduced remote learning, which was considered as an auxiliary education, and non-face-to-face classes have become commonplace, and professors and students are making great efforts to adapt to the new educational environment. In order to improve the quality of non-face-to-face lectures amid these changes, it is necessary to study the factors affecting lecture satisfaction. Therefore, This paper presents a new methodology using big data to identify the factors affecting university lecture satisfaction changed before and after COVID-19. We use Topic Modeling method to analyze lecture reviews before and after COVID-19, and identify factors affecting lecture satisfaction. Through this, we suggest the direction for university education to move forward. In addition, we can identify the factors of satisfaction and dissatisfaction of lectures from multiangle by establishing a topic classification model with an F1-score of 0.84 based on KoBERT, a deep learning language model, and further contribute to continuous qualitative improvement of lecture satisfaction.

• Proceedings of the Korean Statistical Society Conference
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• 2003.10a
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• pp.69-72
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• 2003

The paper considers partial least squares (PLS) as a new dimension reduction technique for the feature vector to overcome the small sample size problem in face recognition. Principal component analysis (PCA), a conventional dimension reduction method, selects the components with maximum variability, irrespective of the class information. So PCA does not necessarily extract features that are important for the discrimination of classes. PLS, on the other hand, constructs the components so that the correlation between the class variable and themselves is maximized. Therefore PLS components are more predictive than PCA components in classification. The experimental results on Manchester and ORL databases show that PLS is to be preferred over PCA when classification is the goal and dimension reduction is needed.

• Journal of the Korea Society of Computer and Information
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• v.15 no.5
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• pp.67-74
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• 2010

E-learning technology which effectively supports the learning methodologies between students and professors and which provides location and time benefits to students is being researched now a days. However, E-learning classes produce bad effects comparing with offline classes in learning procedures including scholastic achievements. Bad effects of E-learning system could be proxy attendance, lack of concentration, and bad attitude of students. These environmental problems must be solved first to achieve the advantages of E-learning technology. To get rid of these problems, in this paper, we proposed a mechanism which provides effective learning progress by using face authentication method. This mechanism supervise the student by using real time face recognition which prevents proxy attendance, illegal activities, and student's absences.

• The Korean Journal of Emergency Medical Services
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• v.26 no.1
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• pp.71-85
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• 2022

Purpose: This study aimed to investigate the current status of non-face-to-face education at universities for paramedicine and measure students' education satisfaction after the coronavirus infectious disease 2019 (COVID-19) outbreak. Methods: A cross-sectional survey was conducted for paramedic students at the Chungcheong and Honam areas using Google Forms. Convenience sampling was used. A structured questionnaire was created and modified according to Park and Choi's test tool developed to review online lectures and practical courses. Results: A total of 202 students responded to the survey. The satisfaction level of online lectures was 3.06±1.12 (n=202) out of 5. Students experiencing online lectures responded that it was difficult to focus on the class, and the overall quality and lecture delivery should be improved. They also experienced technical difficulties. The satisfaction level of practical course lectures was 3.24±1.04 (n=133) out of 5. It was higher than those of other types of classes because it was conducted by the more familiar face-to-face lecture. Conclusion: This study has shown that the universities and instructors have examined a variety of methods in paramedic education after the COVID-19 pandemic. However, further research and consideration are required to improve paramedic education during the COVID-19 pandemic.

• Journal of the Korea Society of Computer and Information
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• v.16 no.4
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• pp.83-91
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• 2011

The purpose of this thesis was to implement effective blended PBL(Problem-Based Learning) systems for information communication ethics education. Online learning and face-to-face classes were systematically combined for achieving the teaching-learning goals. And the main module for online learning run on Moodle, an open source learning management system. To examine educational effectiveness of the proposed systems, an experimental study was conducted through the method to the subject of two class in the second-grade of university located in ${\bigcirc}{\bigcirc}$ city. For experiment 60 students(treatment group=30, control group=30) are participated. And they were assigned to one of ten subgroups, comprising of six students, respectively. The results of this study are follows, First, the education using proposed blended PBL method is more effective in cultivating consciousness of information communication ethics than the education using face-to-face PBL learning method. Second, learners who participated in the proposed blended PBL more experienced various effects of PBL, such as (1) Improvement of problem solving ability, (2) Understanding of cooperative learning than the other learners who participated in the face-to-face PBL.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.1
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• pp.196-204
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• 2008

In this paper, we propose an efficient method to classify human facial impression using frontal face image. The features that represent the shape of eye, jaw and face are used. The proposed method employs PCA, LDA and SVM in series. PCA is used to project the feature space to a low dimensional subspace. LDA produces well separated classes in a low dimensional subspace even under severe variation. This results in good discriminating power for classification. SVM is used to classify the data. Human face has been classified for 8 facial impressions. The experiments have been performed for many face images, and show encouraging result.