• Journal of the Institute of Electronics Engineers of Korea SC
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• v.47 no.1
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• pp.7-16
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• 2010

Face recognition of face images is an active subject in the area of computer pattern recognition, which has a wide range of potential. Automatic extraction of face image of the feature points is an important step during automatic face recognition. Whether correctly extract the facial feature has a direct influence to the face recognition. In this paper, a new method of facial feature extraction based on Discrete Wavelet Transform is proposed. Firstly, get the face image by using PC Camera. Secondly, decompose the face image using discrete wavelet transform. Finally, we use the horizontal direction, vertical direction projection method to extract the features of human face. According to the results of the features of human face, we can achieve face recognition. The result show that this method could extract feature points of human face quickly and accurately. This system not only can detect the face feature points with great accuracy, but also more robust than the tradition method to locate facial feature image.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.831-832
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• 2008

This paper proposes the experimental results and analysis of face recognition on an conventional UMPC(Ultra Mobile Personal Computer). With face images acquired by the embedded camera of UMPC, we detected the facial region by using Adaboost face detector. The detected image was normalized into a $32{\times}32$ pixel sized image for face recognition. We performed face recognition based on PCA (Principal Component Analysis). As experimental results, the TER (Total Error Rate) of face recognition was 19.77%.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.49-52
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• 2002

This paper presents a fast algorithm for face detection from color images on internet. We use Mahalanobis distance between standard skin color and actual pixel color on IQ color space to segment skin color regions. The skin color regions are the candidate face region. Further, the locations of eyes and mouth regions are found by computing average pixel values on horizontal and vertical pixel lines. The geometry of mouth and eye locations is compared to the standard face geometry to eliminate false face regions. Our Method is simple and fast so that it can be applied to face search engine for internet.

• Journal of the Society of Disaster Information
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• v.17 no.4
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• pp.722-732
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• 2021

Purpose: Due to the coronavirus infection-19 (COVID) pendemics, all educational institutions were required to provide full non-face-to-face real-time education, and fire officials were required to provide fire-fighting education by applying non-face-to-face education. In this difficult situation, the National Fire Service Academy tries to find the direction of the non-face-to-face real-time education and suggest ways to improve it through a survey of the status of non-face-to-face real-time education conducted by the NFSA to fire officials. Method: A survey was conducted on fire officials under the theme of "Consciousness Survey for Improving the Quality and Specialization of Non-face-to-face Real-Time Remote Education" and an in-depth analysis was conducted based on the results. Result & Conclusion: First, professors or educational operators shall actively utilize remote education programs suitable for educational characteristics by utilizing various programs. Second, a dedicated notebook for non-face-to-face training should be provided to provide an educational environment where all learners can participate in the training without difficulty. Third, in the case of education and training that requires the use of equipment due to the nature of fire officials' education and training, it is necessary to consider it as a non-face-to-face training place by arranging educational equipment at each fire station. Fourth, it is hard to expect a satisfactory educational effect to cope with practical education with theoretical education. Therefore, facilities and programs that enable non-face-to-face real-time hands-on training should be developed. It is worth considering the proper combination of face-to-face education while maintaining the social distance as much as possible until such non-face-to-face training is possible. Fifth, non-face-to-face education is considered to have high eye fatigue due to the light and electromagnetic waves of the computer screen, and as time goes by, the concentration level decreases. Therefore, it is necessary to form an education time to reduce the eye fatigue of learners and increase concentration through proper class and rest time. Finally, professors should operate a learner participation-oriented education that allows professors and learners to interact rather than one-sided knowledge transfer education. In addition, technical problems of non-face-to-face remote education should be thoroughly prepared through preliminary system checks to ensure that education is not disrupted.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.2
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• pp.81-96
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• 2024

This study analyzed the differences in the effects on entrepreneurship and entrepreneurial willingness of college students under the coronavirus pandemic by dividing theoretical education into practical education, face-to-face education, and non-face-to-face education, and analyzed the differences in the effects on entrepreneurship and entrepreneurship willingness according to the education method. This study conducted entrepreneurship education for 552 students at a comprehensive university in Chungcheong-do, Korea, and analyzed the sample by dividing it into theoretical and practical education, face-to-face education, and non-face-to-face education. In addition, a two-way repeated measures ANOVA was conducted to determine whether there were differences in the entrepreneurship education course operation form according to the pre- and post-education time points. The results showed that, first, the difference between the effectiveness of entrepreneurship education before and after theoretical and practical education was significant, and the entrepreneurship of practical education was higher than that of theoretical education after education. In the test of pre- and post-training differences in entrepreneurial intention, the difference in effectiveness was significant only in practical training. Second, the results of the repeated measures ANOVA analysis of the course operation type of theoretical and practical courses according to the difference between the pre- and post-education time points showed that there were differences in the entrepreneurship effectiveness of theoretical and practical courses according to the time point of education. Third, the difference in the effectiveness of entrepreneurship education according to face-to-face and non-face-to-face education was significant, and only the effect of non-face-to-face education on entrepreneurial intention was significant before and after education. Fourth, the results of repeated measures ANOVA analysis of face-to-face and non-face-to-face course operation type showed that the effect of face-to-face and non-face-to-face entrepreneurship education differed depending on the time of education. The pre-post difference in entrepreneurial intention was significant only for the non-face-to-face program. The implication of this study is that in order to increase the effectiveness of entrepreneurship and entrepreneurial will among university students, it is necessary to expand the amount of practical classes in which students actively participate in activities related to entrepreneurship. In addition, in order to increase the effectiveness of entrepreneurial will, a non-face-to-face education method that utilizes the metaverse space and increases the role of each student can contribute to increasing the effectiveness of entrepreneurial will.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.3
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• pp.176-191
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• 2021

Non-face-to-face lectures have become a necessity rather than an option since COVID-19, and in order to improve the quality of university education, it is necessary to explore the properties of non-face-to-face lectures and make active efforts to improve them. This study, focusing on this, aims to provide basic data necessary for decision-making for non-face-to-face lecture design by analyzing the relative importance and execution satisfaction of non-face-to-face lecture attributes for professors and students. Based on previous research, a questionnaire was constructed by deriving 4 factors from 1st layer and 17 from 2nd layer attributes of non-face-to-face lectures. A total of 180 valid samples were used for analysis, including 60 professors and 120 students. The importance of the non-face-to-face lecture properties was calculated by obtaining the weights for each stratified element through AHP(Analytic Hierachy Process) analysis, and performance satisfaction was calculated through statistical analysis based on the Likert 5-point scale. As a result of the AHP analysis, both the professor group and the student group had the same priority for the first tier factors, but there was a difference in the priorities between the second tier factors, so it seems necessary to discuss this. As a result of the IPA(Importance Performance Analysis) analysis, the professor group selected the level of interaction as an area to focus on, and it was confirmed that research and investment in teaching methods for smooth interaction are necessary. The student group was able to confirm that it is urgent to improve and invest in the current situation so that the system can be operated stably by selecting the system stability. This study uses AHP analysis for professors and students groups to derive relative importance and priority, and calculates the IPA matrix using IPA analysis to establish the basis for decision-making on future face-to-face and non-face-to-face lecture design and revision. It is meaningful that it was presented.

• The Journal of the Korea Contents Association
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• v.21 no.6
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• pp.804-813
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• 2021

The purpose of this study was on the learning satisfaction of dental hygiene students according to the face-to-face and non-face-to-face teaching methods in the COVID-19 educational environment. A self-reported questionnaire was completed by 122 dental hygiene students of G University located in Gwangju from October to November, 2020. The general characteristics, instructional characteristics, teaching methods, and learning satisfaction were investigated, and the collected data were analyzed using SPSS 18.0. The effective practical teaching method chosen by the students was face-to-face, and there was a significant difference according to the class choice. The learning satisfaction according to the general characteristics showed a significant difference in the preferred practice method for improving instrument technique. The face-to-face classes showed significantly higher learning satisfaction in terms of checking on doing well study during class and the convenience. In addition, as a result of analyzing the factors influencing learning satisfaction, the choice of face-to-face class was confirmed as a significant variable. Therefore, in order to increase the learning satisfaction of students, it is necessary to design a class that essentially includes face-to-face class when planning a practice class.

• Journal of Science Education
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• v.46 no.1
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• pp.40-52
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• 2022

Daily science classes, which have been continued as part of the spread of participatory science culture, has taken the lead in popularizing science as an effective out-of-school experiential and research activity. However, due to the recent COVID-19 situation, daily science classes have also become an environment in which there is no choice but to switch to non-face-to-face or to combine face-to-face and non-face-to-face education. Therefore, in this study, we examine how elementary school students participating in the non-face-to-face daily science class program change their usual fields of interest, perception of science and technology, interest about science, and scientific competency. In addition, the educational effectiveness of the non-face-to-face daily science class improved by comparing the differences in perceptions of students and parents, and future operation plans were sought. As a result of the study, after participating in the non-face-to-face daily science class program, students' interest in science and technology development, future technology, environmental pollution, and social media increased, and their interest in games decreased. Also, students' interest in science and technology activities, interest in science, and scientific competency also increased. This shows that non-face-to-face daily science class education is effective. Therefore, it was suggested that it is necessary to diversify the learning topics and content levels of the daily science class program, to expand the opportunities of non-face-to-face science education for underprivileged learners, and to develop and share science content using the latest media.

• Journal of Industrial Convergence
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• v.19 no.6
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• pp.123-129
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• 2021

This Study is to identify factors that affect the interaction between professors and university students and their satisfaction with non-face-to-face lectures. The subjects were 348 university student who attended from October 5 to October 23, 2020. The statistics program was SPSS win 22.o. Among the expected benefits of non-face-to-face classes, the temporal benefit was 3.69 points, the expected benefit of the learning effect was 3.46 points, and the technical familiarity was 3.47 points. Satisfaction with non-face-to-face classes was found to be 3.58 points. Factors affecting the satisfaction of lectures in non-face-to-face classes were expected benefits of learning effect, university satisfaction, technical familiarity, expected benefits over time, and the number of non-face-to-face classes desired for the next semester. Learning effect The higher the expected benefit, the higher the university satisfaction, the higher the technical familiarity, the higher the expected temporal benefit, the higher the number of non-face-to-face classes desired for the next semester, the higher the satisfaction with the non-face-to-face class lectures. Therefore, it was confirmed that the role of the instructor was important in the interaction between the instructor and university students in the non-face-to-face class and the satisfaction of the lecture.

• The Journal of Korean Medicine
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• v.42 no.1
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• pp.1-11
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• 2021

Objectives: This pilot study aimed to evaluate the agreement between traditional face-to-face Korean medicine (KM) pattern identification and non-face-to-face KM pattern identification using the data from related questionnaires, tongue image, and pulse features in patients with cancer. Methods: From January to June 2020, 16 participants with a cancer diagnosis were recruited at the one Korean medicine hospital. Three experienced Korean medicine doctors independently diagnosed the participants whether they belong to the cold pattern or not, heat pattern or not, deficiency pattern or not, and excess pattern or not. Another researcher collected KM pattern related data using questionnaires including Cold-Heat Pattern Identification (CHPI), tongue image analysis system, and pulse analyzer. Collected KM pattern related data without participants' identifier was provided for the three Korean medicine doctors in random order, and non-face-to-face KM pattern identification was carried out. The kappa value between face-to-face and non-face-to-face pattern identification was calculated. Results: From the face-to-face pattern identification, there were 13/3 cold/non-cold pattern, 4/12 heat/non-heat pattern, 14/2 deficiency/non-deficiency pattern, and 0/16 excess/non-excess pattern participants. In cold/non-cold pattern, kappa value was 0.455 (sensitivity: 0.85, specificity: 0.67, accuracy: 0.81). In heat/non-heat pattern, the kappa value was 0.429 (sensitivity: 0.75, specificity: 0.72, accuracy: 0.75). The kappa value of deficiency/non-deficiency and excess/non-excess pattern was not calculated because of the few participants of non-deficiency, and excess pattern. Conclusions: The agreement between traditional face-to-face pattern identification and non-face-to-face pattern identification seems to be moderate. The non-face-to-face pattern identification using questionnaires, tongue, and pulse features may feasible for the large clinical study.