• Proceedings of the Korean Society of Computer Information Conference
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• 2021.01a
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• pp.85-87
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• 2021

컴퓨터 전공자들의 프로그래밍 개발 중심의 팀 프로젝트 수업은 프로그래밍 개발 능력과 팀원들 간의 협업 능력을 키울 수 있는 수업으로서, 기존에는 대면수업을 통해 교수자와 학습자간 그리고 팀을 이룬 학습자들 간에 긴밀한 상호작용으로 진행되어왔다. 그러나 2020년 COVID-19의 확산으로 대부분의 대학 수업들이 비대면 방식으로 진행됨에 따라 팀 프로젝트 수업 역시 비 대면으로 운영되어야 했으며 팀 활동을 위해 다양한 온라인 커뮤니케이션 방법이 모색되어야 했다. 본 연구에서는 팀 프로젝트 수업을 기존의 대면 수업으로 운영하였을 경우와 비대면 방식으로 운영하였을 때 학습자들이 느끼는 학습 효과에 대해 비교해보고자 한다. 대면 수업과 비대면 수업에 참여했던 학습자들을 대상으로 설문을 실시하여 팀 프로젝트 수업을 통한 학습 이해도, 수업 흥미도, 학습자간의 소통의 원활성, 수업 참여의 적극성 그리고 전체적인 수업 만족도에 대한 설문 결과를 비교 분석하였다. 향후 포스트 코로나 시대에는 대면과 비대면의 하이브리드 커뮤니케이션 방식이 대세를 이룰 것으로 예측되고 있는 만큼 대학 수업 방식에도 변화가 필요할 것이며 본 연구는 이를 위한 기초 연구로 활용될 수 있다.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.13-23
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• 2021

This study requires SW education that can adapt to the advent of the fourth industrial revolution and the new normal environment of COVID-19 pandemic. Small and powerful smartphones, which have become a necessity in digital society, are designed and applied to create apps with useful apps or artificial intelligence modules that have been trained with data using the App Inventor program as a good teaching tool. After conducting the class in a blended method that combines face-to-face and non-face methods, the survey questioned the technical and cognitive maturity of artificial intelligence and the pros and cons of blended software classes. We also found changes in career orientation, which is intended to explore SW-related talent occupations that require a lot of demand in terms of national development before and after artificial intelligence classes. Significant results were reached in three of the sub-elements. Even in non-face-to-face situations, it is expected that an app vendor software education program using artificial intelligence will be provided to the actual site.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.187-192
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• 2021

The purpose of this study is a method to discover problems and improve them by analyzing the status of software education of A primary school conducted by online class. The coronavirus infection-19(COVID-19) pandemic, which began in early 2020, has continued to delay the start of the new semester. Finally, on April 9, 2020, the first semester began with online class. While progressing non-face to face online class, most students said they had difficulties. Students solved difficulties in class with Internet searches or program hints, not teachers. In the post-class self-evaluation, most students answered that there was no increase in coding skills. To solve this problem, the school rents additional smart devices to student. schools should have real-time interactive classes. After covid 19, online class became a paradigm for classes. Therefore, software education will also require research and development of curriculum and teaching learning methods suitable for online classes.

• Journal of the korean academy of Pediatric Dentistry
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• v.23 no.3
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• pp.615-623
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• 1996

Face mask is an extraoral appliance which used to protract maxilla, and can help in the correction of moderately severe class IlI malocclusions by the anterior displacement of the maxilla and maxillary dentition, and possibly restricting or changing the direction of the growth of the mandible. In three cases the results were followed. 1. Anterior crossbite was corrected 2. Maxilla & maxillary dentition were displaced forwardly. 3. Lingual tipping of the mandibular incisors, and backward & downward rotation of mandible were performed. 4. Acceptable improvement in the class III profile was performed.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.43-49
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• 2004

The classification time required by conventional multi-class SVMs(Support Vector Machines) greatly increases as the number of pattern classes increases. This is due to the fact that the needed set of binary class SVMs gets quite large. In this paper, we propose a method to reduce the number of classes by using nearest neighbor rule (NNR) in the principle component analysis and linear discriminant analysis (PCA+LDA) feature subspace. The proposed method reduces the number of face classes by selecting a few classes closest to the test data projected in the PCA+LDA feature subspace. Results of experiment show that our proposed method has a lower error rate than nearest neighbor classification (NNC) method. Though our error rate is comparable to the conventional multi-class SVMs, the classification process of our method is much faster.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.32 no.2
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• pp.146-152
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• 2022

Objectives: The purpose of this study is to confirm whether there is a factor to affect the evaluation of fit test of a 2nd class half masks using a OPC test method. Methods: Total 34 adults including Males and Females were tested using OPC-based fit testing equipment while wearing a 2nd class half filtered mask. Results: 1. The result of measuring face dimensions using different tools such as a 3D scanner and digital calipers revealed that the variation of lip width was not statistically significant because there was only a difference of about 4 mm. However, it showed that a difference in face length was statistically significant enough with 10 mm(p<0.000). 2. The fit factor for each exercise stage according to gender was the highest at 124.54(p<0.001) in Step 3, and the fit factor was the lowest at 73.75 in Step 1. 3. In the evaluation of the degree of fit factor according to gender, female passed 67.44%, which was higher than the value in male(p<0.038). 4. The acceptance rate of the group having a face length of shorter than 110 mm was 91.67%. On the other hand, the acceptance rate of the group with a face length of longer than 110 mm was 47.27%(p<0.000). 5. The fit test was possible because the fit factor with 2nd class half masks corresponding to FFP1(Filtering Face Piece 1) was passed 55% or more. Conclusions: The test results showed that using a 2nd class half filtered mask, it is important to wear a properly designed mask so that face size does not affect the fit factor.

• Maxillofacial Plastic and Reconstructive Surgery
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• v.34 no.1
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• pp.26-33
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• 2012

Purpose: The golden ratio has been used for a long time to objectify and quantify 'beauty'. Dr. Marqurardt claims that the golden ratio can be applied in the maxillofacial field as well. The purpose of this study was to evaluate the diagnostic significance of using a facial 'phi' mask for analyzing Korean faces with characteristics of Class I, II, and III malocclusion. Methods: We studied twenty five Korean celebrities' frontal facial photos (10 males, 15 females) and 90 malocclusion patients' frontal facial photos (30 patients in each malocclusion classification: Class I, Class II, and Class III). Patients who received orthodontic treatment at Samsung Medical Center were selected for this study. After superimposition of the selected facial photo and facial 'phi' mask using Adobe Photoshop CS3, the ratio of the entire facial area, mid facial area, lower facial area and horizontal and vertical lengths were measured. Results: The facial ratio in photos of Korean faces showed larger vertical and horizontal ratios than the facial 'phi' mask with golden ratio, regardless of skeletal malocclusion (entire face: 115%, lower face: 125% larger than the mask). The results of the frontal photos of Class I, II, and III malocclusion patients using facial 'phi' mask showed that the vertical length and frontal face area was more significantly influenced by the area of the lower face than the midface. This means that the lower face has larger proportions in the facial areas. Conclusion: The ratio of facial 'phi' mask is matched with the ideal facial appearance that the contemporary Korean general public is seeking. Thus, the facial 'phi' mask may be a convenient tool for esthetic analysis of Korean faces. Reducing the area of the lower face is esthetically more desirable for almost all Korean people when planning orthognathic surgery.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.783-788
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• 2003

In this paper, we present a new approach to detect and recognize human face in the image from vision camera equipped on the mobile robot platform. Due to the mobility of camera platform, obtained facial image is small and pose-various. For this condition, new algorithm should cope with these constraints and can detect and recognize face in nearly real time. In detection step, ‘coarse to fine’ detection strategy is used. Firstly, region boundary including face is roughly located by dual ellipse templates of facial color and on this region, the locations of three main facial features- two eyes and mouth-are estimated. For this, simplified facial feature maps using characteristic chrominance are made out and candidate pixels are segmented as eye or mouth pixels group. These candidate facial features are verified whether the length and orientation of feature pairs are suitable for face geometry. In recognition step, pseudo-convex hull area of gray face image is defined which area includes feature triangle connecting two eyes and mouth. And random lattice line set are composed and laid on this convex hull area, and then 2D appearance of this area is represented. From these procedures, facial information of detected face is obtained and face DB images are similarly processed for each person class. Based on facial information of these areas, distance measure of match of lattice lines is calculated and face image is recognized using this measure as a classifier. This proposed detection and recognition algorithms overcome the constraints of previous approach [15], make real-time face detection and recognition possible, and guarantee the correct recognition irregardless of some pose variation of face. The usefulness at mobile robot application is demonstrated.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.5
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• pp.648-654
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• 2009

In this paper, a method called bilateral diagonal 2DLDA is proposed for face recognition. Two methods called Dia2DPCA and Dia2DLDA were suggested to reserve the correlations between the variations in the rows and columns of diagonal images. However, these methods work in the row direction of these images. A row-directional projection matrix can be obtained by calculating the between-class and within-class covariance matrices making an allowance for the column variation of alternative diagonal face images. In addition, column-directional projection matrix can be obtained by calculating the between-class and within-class covariance matrices making an allowance for the row variation in diagonal images. A bilateral projection scheme was applied using left and right multiplying projection matrices. As a result, the dimension of the feature matrix and computation time can be reduced. Experiments carried out on an ORL face database show that the proposed method with three different distance measures, namely, Frobenius, Yang and AMD, is more accurate than some methods, such as 2DPCA, B2DPCA, 2DLDA, etc.

• Journal of Korea Society of Industrial Information Systems
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• v.14 no.5
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• pp.43-51
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• 2009

In this paper, we propose an efficient method of face retrieval by using PCA(principal component analysis) based features. The coarse-to-fine strategy is adopted to sort the retrieval results in the lower dimensional eigenface space and to rearrange candidates at high ranks in higher dimensional eigenface space. To evaluate similarity between a query face image and class reference image, we utilize the PD (projection distance), MQDF(modified quadratic distance function) and MED(minimum Euclidean distance). The experimental results show that the proposed method which rearrange the retrieval results incrementally by using projection distance is efficient for face image retrieval.