• Clinical and Experimental Pediatrics
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• v.61 no.10
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• pp.332-337
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• 2018

Purpose: Bell's palsy is characterized by sudden onset of unilateral facial weakness. The use of corticosteroids for childhood Bell's palsy is controversial. This study aimed to identify clinical characteristics, etiology, and laboratory findings in childhood Bell's palsy, and to evaluate the efficacy of corticosteroid treatment. Methods: We conducted a retrospective analysis of children under 19 years of age treated for Bell's palsy between January 2009 and June 2017, and followed up for over 1 month. Clinical characteristics, neuroimaging data, laboratory findings, treatments, and outcomes were reviewed. Patients with Bell's palsy were divided into groups with (group 1) and without (group 2) corticosteroid treatment. Differences in onset age, sex, laterality, infection and vaccination history, degree of facial nerve palsy, and prognosis after treatment between the groups were analyzed. Results: One hundred patients were included. Mean age at presentation was $7.4{\pm}5.62years$. A total of 73 patients (73%) received corticosteroids with or without intravenous antiviral agents, and 27 (27%) received only supportive treatment. There was no significant difference in the severity, laboratory findings, or neuroimaging findings between the groups. Significant improvement was observed in 68 (93.2%) and 26 patients (96.3%) in groups 1 and 2, respectively; this rate was not significantly different between the groups (P=0.48). Conclusion: Childhood Bell's palsy showed good prognosis with or without corticosteroid treatment; there was no difference in prognosis between treated and untreated groups. Steroid therapy in childhood Bell's palsy may not significantly improve outcomes.

• Journal of information and communication convergence engineering
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• v.18 no.2
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• pp.132-146
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• 2020

Biometric technologies have become widely available in many different fields. However, biometric technologies using existing physical features such as fingerprints, facial features, irises, and veins must consider forgery and alterations targeting them through fraudulent physical characteristics such as fake fingerprints. Thus, a trend toward next-generation biometric technologies using behavioral biometrics of a living person, such as bio-signals and walking characteristics, has emerged. Accordingly, in this study, we developed a bio-signal authentication algorithm using electrocardiogram (ECG) signals, which are the most uniquely identifiable form of bio-signal available. When using ECG signals with our system, the personal identification and authentication accuracy are approximately 90% during a state of rest. When using fingerprints alone, the equal error rate (EER) is 0.243%; however, when fusing the scores of both the ECG signal and fingerprints, the EER decreases to 0.113% on average. In addition, as a function of detecting a presentation attack on a mobile phone, a method for rejecting a transaction when a fake fingerprint is applied was successfully implemented.

• Korean Journal of Child Studies
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• v.17 no.2
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• pp.195-206
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• 1996

The purpose of this study was to observe differences in peer competence by children's personality and to investigate the relationship between peer competence and characteristics of children from poor families. The subjects were 79 parents and their 4- to 6-year-old children at a kindergarten in Seoul. The instruments were Iannotti's facial drawings cards, vignettes, "roster and rating" the Family Environment Scale (FES) and the Family Expressiveness Questionnaire (FEQ). The main results of this study were that girls from poor families had higher levels of peer competence than boys. There was a significant correlation between the peer competence of the children in poverty and family characteristics. The children's gender, knowledge of emotion, and mother's negatively dominant conduct were the factors that indicated children's behavior in peer competence. Family conflict and mother's emotional conduct did not relate to children's knowledge of emotion.

• Journal of the Korea Society of Computer and Information
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• v.13 no.5
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• pp.19-26
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• 2008

In this paper, we converted an RGB into an YCbCr image input from CCD camera and then after compute difference two consecutive images, conduct Glassfire Labeling. We extract an image become ware of motion-change, if the difference between most broad(area) and Area critical value more than critical value. We enforce the detection of facial characteristics to an extracted motion-change images by using AdaBoost algorithm to extract an characteristics.

• Journal of Korea Society of Digital Industry and Information Management
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• v.16 no.4
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• pp.67-74
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• 2020

As the information age develops, Online education and Non-face-to-face work are becoming common. Telecommuting such as tele-education and video conferencing through the application of information technology is also becoming common due to the COVID-19. Unexpected information leakage can occur online when the company conducts work remotely or holds meetings. A system to authenticate users is needed to reduce information leakage. In this study, there are various ways to authenticate remote access users. By applying burn authentication using a biometric system, a method to identify users is proposed. The method used in the study was studied the main component analysis method, which recognizes several characteristics in facial recognition and processes interrelationships. It proposed a method that can be easily utilized without additional devices by utilizing a camera connected to a computer by authenticating the user using the shape and characteristics of the face by using the PCA method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.3
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• pp.1076-1094
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• 2022

Technology for emotion recognition is an essential part of human personality analysis. To define human personality characteristics, the existing method used the survey method. However, there are many cases where communication cannot make without considering emotions. Hence, emotional recognition technology is an essential element for communication but has also been adopted in many other fields. A person's emotions are revealed in various ways, typically including facial, speech, and biometric responses. Therefore, various methods can recognize emotions, e.g., images, voice signals, and physiological signals. Physiological signals are measured with biological sensors and analyzed to identify emotions. This study employed two sensor types. First, the existing method, the binary arousal-valence method, was subdivided into four levels to classify emotions in more detail. Then, based on the current techniques classified as High/Low, the model was further subdivided into multi-levels. Finally, signal characteristics were extracted using a 1-D Convolution Neural Network (CNN) and classified sixteen feelings. Although CNN was used to learn images in 2D, sensor data in 1D was used as the input in this paper. Finally, the proposed emotional recognition system was evaluated by measuring actual sensors.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.3
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• pp.754-774
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• 2023

Wrestling is one of the popular events for modern sports. It is difficult to quantitatively describe a wrestling game between athletes. And deep learning can help wrestling training by human recognition techniques. Based on the characteristics of latest wrestling competition rules and human recognition technologies, a set of wrestling competition video analysis and retrieval system is proposed. This system uses a combination of literature method, observation method, interview method and mathematical statistics to conduct statistics, analysis, research and discussion on the application of technology. Combined the system application in targeted movement technology. A deep learning-based facial recognition psychological feature analysis method for the training and competition of classical wrestling after the implementation of the new rules is proposed. The experimental results of this paper showed that the proportion of natural emotions of male and female wrestlers was about 50%, indicating that the wrestler's mentality was relatively stable before the intense physical confrontation, and the test of the system also proved the stability of the system.

• The korean journal of orthodontics
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• v.39 no.5
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• pp.330-336
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• 2009

Objective: To examine the differences in lateral cephalometric characteristics between patients with dental protrusion and crowding in order to determine what factors affect dental protrusion or crowding while both malocclusion types are caused by large tooth size. Methods: Twenty nine individuals with dental protrusion and 22 individuals with dental crowding were enrolled in this study. All subjects had larger teeth than average and Class I molar relationships. Craniofacial characteristics and hyoid bone positions were determined from lateral cephalograms and compared between the two groups. Results: In the comparisons of craniofacial characteristics, the measurements indicating maxillary length and facial convexity showed greater values in the protrusion group than in the crowding group. Comparisons of hyoid bone positions showed that the hyoid bone was positioned more anteriorly and superiorly in the protrusion group than in the crowding group. Conclusions: The results of the present study indicate that some craniofacial characteristics and tongue position may affect the development of dental protrusion or crowding; when an individual has large teeth, dental protrusion or crowding might be determined according to maxillary growth and tongue position.

• Journal of the Korean Society of Costume
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• v.59 no.1
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• pp.29-46
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• 2009

Aiming at finding symbolistic meanings and characteristics of makeup in Chinese Beijing Opera("BO"), this study formulated a theoretical framework mainly from literature in the Symbolism and symbolistically analyzed materials related to BO makeup from literature, internet web pages and illustrated news concerning performing arts. Main objects to analyze are the characteristics of four main roles in BO and the patterns, symbols, ornaments and traditions of Beijing Opera facial makeup("BOFM"). Four main roles are Sheng, Tan, Ching and Chou, categorized by gender, age, social position and personality. The result to analyze symbolistic meanings and characteristics of makeups for the roles in BO are as follows: the patterns and colors of BOFM function as explanations to help audiences understand each role's personality and dramatic situations as well as provide hints about the development and ending of an opera: that is, BO makeup is a communicative intermediary between audiences and actors in BO. It tends to follow the stereotypes, which conventionally dress and exaggerate the characters of roles, and copy the traditional Chinese perception about colors. Thus, by the metaphysical and typical expression of BOFM, Chinese people have not been pursuing the realism in opera but applying BO makeup to a mutual communication method between audiences and performing artists as to share their collective cultural heritages and spirits. Threfore, BO makeup has been an interacting language between the two entities and grown within the history of BO as a beauty art to highlight a BO by its unique systems, ornaments and beauty.

• Journal of IKEEE
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• v.27 no.4
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• pp.464-471
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• 2023

In this paper, we propose a method to reduce age distortion in facial expression image generation using StyleGAN Encoder. The facial expression image generation process first creates a face image using StyleGAN Encoder, and changes the expression by applying the learned boundary to the latent vector using SVM. However, when learning the boundary of a smiling expression, age distortion occurs due to changes in facial expression. The smile boundary created in SVM learning for smiling expressions includes wrinkles caused by changes in facial expressions as learning elements, and it is determined that age characteristics were also learned. To solve this problem, the proposed method calculates the correlation coefficient between the smile boundary and the age boundary and uses this to introduce a method of adjusting the age boundary at the smile boundary in proportion to the correlation coefficient. To confirm the effectiveness of the proposed method, the results of an experiment using the FFHQ dataset, a publicly available standard face dataset, and measuring the FID score are as follows. In the smile image, compared to the existing method, the FID score of the smile image generated by the ground truth and the proposed method was improved by about 0.46. In addition, compared to the existing method in the smile image, the FID score of the image generated by StyleGAN Encoder and the smile image generated by the proposed method improved by about 1.031. In non-smile images, compared to the existing method, the FID score of the non-smile image generated by the ground truth and the method proposed in this paper was improved by about 2.25. In addition, compared to the existing method in non-smile images, it was confirmed that the FID score of the image generated by StyleGAN Encoder and the non-smile image generated by the proposed method improved by about 1.908. Meanwhile, as a result of estimating the age of each generated facial expression image and measuring the estimated age and MSE of the image generated with StyleGAN Encoder, compared to the existing method, the proposed method has an average age of about 1.5 in smile images and about 1.63 in non-smile images. Performance was improved, proving the effectiveness of the proposed method.