• International Journal of Advanced Culture Technology
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• v.7 no.4
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• pp.289-294
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• 2019

As social network service platforms grow and one-person media market expands, people upload their own photos and/or videos through multiple open platforms. However, it can be illegal to upload the digital contents containing the faces of others on the public sites without their permission. Therefore, many people are spending much time and effort in editing such digital contents so that the faces of others should not be exposed to the public. In this paper, we propose an automatic face hiding system called 'autoblur', which detects all the unregistered faces and mosaic them automatically. The system has been implemented using the GitHub MIT open-source 'Face Recognition' which is based on deep learning technology. In this system, two dozens of face images of the user are taken from different angles to register his/her own face. Once the face of the user is learned and registered, the system detects all the other faces for the given photo or video and then blurs them out. Our experiments show that it produces quick and correct results for the sample photos.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.2
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• pp.69-78
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• 2002

This paper addresses a method to automatically detect out a person's face from a given image that consists of a hair and face view of the person and a complex background scene. Out method involves an effective detection algorithm that exploits the spatial distribution characteristics of human skin color via an adaptive fuzzy color classifier (AFCC), The universal skin-color map is derived on the chrominance component of human skin color in Cb, Cr and their corresponding luminance. The desired fuzzy system is applied to decide the skin color regions and those that are not. We use RGB model for extracting the hair color regions because the hair regions often show low brightness and chromaticity estimation of low brightness color is not stable. After some preprocessing, we apply convex-hull to each region. Consequent face detection is made from the relationship between a face's convex-hull and a head's convex-hull. The algorithm using the convex-hull shows better performance than the algorithm using pattern method. The performance of the proposed algorithm is shown by experiment. Experimental results show that the proposed algorithm successfully and efficiently detects the faces without constrained input conditions in color images.

• 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.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.787-793
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• 2022

After COVID-19, with the emergence of social distancing, non-face-to-face services, and home economics, visiting dining out is rapidly being replaced by non-face-to-face dining out. The purpose of this study is to find ways to create a safe dining culture centered on living quarantine in line with the changing trend of the restaurant industry after the outbreak of COVID-19, establish the direction of food culture improvement projects, and enhance the effectiveness of the project. This study used TEXTOM to collect and refine search frequency, perform TF-IDF analysis, and Ucinet6 programs to implement visualization using NetDraw from January 1, 2018 to October 31, 2019 and December 31, 2021, and identified the network between nodes of key keywords. Finally, clustering between them was performed through Concor analysis. As a result of the study, if you check the frequency of searches before and after COVID-19, it can be seen that the COVID-19 pandemic greatly affects the changes in the restaurant industry.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.1
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• pp.55-67
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• 2023

Lightweight face recognition models, as one of the most popular and long-standing topics in the field of computer vision, has achieved vigorous development and has been widely used in many real-world applications due to fewer number of parameters, lower floating-point operations, and smaller model size. However, few surveys reviewed lightweight models and reimplemented these lightweight models by using the same calculating resource and training dataset. In this survey article, we present a comprehensive review about the recent research advances on the end-to-end efficient lightweight face recognition models and reimplement several of the most popular models. To start with, we introduce the overview of face recognition with lightweight models. Then, based on the construction of models, we categorize the lightweight models into: (1) artificially designing lightweight FR models, (2) pruned models to face recognition, (3) efficient automatic neural network architecture design based on neural architecture searching, (4) Knowledge distillation and (5) low-rank decomposition. As an example, we also introduce the SqueezeFaceNet and EfficientFaceNet by pruning SqueezeNet and EfficientNet. Additionally, we reimplement and present a detailed performance comparison of different lightweight models on the nine different test benchmarks. At last, the challenges and future works are provided. There are three main contributions in our survey: firstly, the categorized lightweight models can be conveniently identified so that we can explore new lightweight models for face recognition; secondly, the comprehensive performance comparisons are carried out so that ones can choose models when a state-of-the-art end-to-end face recognition system is deployed on mobile devices; thirdly, the challenges and future trends are stated to inspire our future works.

• Geomechanics and Engineering
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• v.37 no.4
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• pp.323-339
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• 2024

If the pressure exerted on the face of a tunnel excavated by TBM exceeds a threshold, it leads to failure of the soil or rock masses ahead of the tunnel face, which results in heaving the ground surface. In the current research, the upper bound method of limit analysis was employed to calculate the blow-out pressure of tunnels excavated in rock masses obeying the Hoek-Brown nonlinear criterion. The results of the proposed method were compared with three-dimensional finite element models, as well as the available methods in the literature. The results show that when σ_ci, m_i, and GSI increase, the blow-out pressure increases as well. By doubling the tunnel diameter, the blow-out pressure reduces up to 54.6%. Also, by doubling the height of the tunnel cover and the surcharge pressure exerted on the ground surface above the tunnel, the blow-out pressure increased up to 74.9% and 5.4%, respectively. With 35% increase in the unit weight of the rock mass surrounding the tunnel, the blow-out pressure increases in the range of 14.8% to 19.6%. The results of the present study were provided in simple design graphs that can easily be used in practical applications in order to obtain the blow-out pressure.

• 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.

• Journal of the Korean Society of Clothing and Textiles
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• v.29 no.7 s.144
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• pp.959-967
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• 2005

The color of apparels has the interaction of the face skin colors of the wearers. This study was carried out to classify the face skin colors of Korean males into several similar face skin colors in order to extract favorable colors which flatter to their face skin colors. The criterion that select the new subjects who have the classified face skin colors have to be decided. With color spectrometer, JX-777, face skin colors of subjects were measured quantitatively and classified into three clusters that had similar hue, value and chroma with Munsell Color System. Sample size was 418 Korean males and other 15 of new males subjects. Data were analyzed by K-means cluster analysis, ANOVA, Duncan multiple range test, Stepwise discriminant analysis using SPSS Win. 12. Findings were as follows: 1. 418 subjects who have YR colors were clustered into 3 kinds of face skin color groups. 2. Discriminant variables of face skin colors was 4 variables : L value of forehead, v value of cheek, c value of forehead, and b value of cheek from standardized canonical discriminant function coefficient 1 and c value of forehead, L value of forehead, b value of cheek. and L value of cheek from standardized canonical discriminant function coefficient 2. 3. Hit ratio of type 1 was $92.3\%$, of type 2 was $96.5\%$ and of type 3 was $92.6\%$ by the canonical discriminant function of 4 variables. 4. The canonical discriminant function equation 1 and 2 were calculated with the unstandardized canonical discriminant function coefficient and constant, the cutting score, and range of the score were computed. 5. The criterion that select the new subjects who have the classified face skin colors was decided.

• Journal of the Korean Geotechnical Society
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• v.28 no.4
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• pp.79-89
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• 2012

This paper presents experimental and numerical studies on the closure ratio of tunnel face to reduce pressure and displacement occurring at tunnel face during tunnel excavation. In experimental study, model tests are carried out according to the closure ratio of tunnel face and tunnel depth. Model test results are analyzed and interpreted by numerical calculation in order to verify results obtained from experimental and numerical studies. It is clearly found that tunnel face stability increases with the increase of the closure ratio of tunnel face. The results also show that tunnel face is stable when the closure ratio of tunnel face is larger than 80%. This research will be very useful to develop the economical tunnel face closing system.

• Tribology and Lubricants
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• v.27 no.5
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• pp.240-248
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• 2011

Mechanical face seal installed in primary heat transport pump used for heavy water reactor prevents leakage of working fluid using thin working fluid film between primary seal ring and mating ring. If the leakage of working fluid exceeds the allowable volume, serious accident can be happened by the trouble of primary heat transport pump. The thinner fluid film exists between primary seal ring and mating ring, the less working fluid leaks out. On the other hand, if the thickness of fluid film is not enough, the life of mechanical face seal will be reduced by friction and wear. Therefore appropriate design is necessary to maximize the performance and life of mechanical face seal. In this study, numerical analysis using finite volume method was conducted to investigate the performance of mechanical face seals which have same deep straight groove and 11 different net coning values. As results, equilibrium clearance between primary seal ring and mating ring, leakage volume of working fluid, friction torque on sealing surface and stiffness of working fluid film were obtained. With increasing net coning value, equilibrium clearance and leakage volume increase, and friction torque and stiffness of fluid film decrease.