• Journal of Intelligence and Information Systems
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• v.18 no.1
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• pp.39-57
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• 2012

Recently, due to the introduction of high-tech equipment in interactive exhibits, many people's attention has been concentrated on Interactive exhibits that can double the exhibition effect through the interaction with the audience. In addition, it is also possible to measure a variety of audience reaction in the interactive exhibition. Among various audience reactions, this research uses the change of the facial features that can be collected in an interactive exhibition space. This research develops an artificial neural network-based prediction model to predict the response of the audience by measuring the change of the facial features when the audience is given stimulation from the non-excited state. To present the emotion state of the audience, this research uses a Valence-Arousal model. So, this research suggests an overall framework composed of the following six steps. The first step is a step of collecting data for modeling. The data was collected from people participated in the 2012 Seoul DMC Culture Open, and the collected data was used for the experiments. The second step extracts 64 facial features from the collected data and compensates the facial feature values. The third step generates independent and dependent variables of an artificial neural network model. The fourth step extracts the independent variable that affects the dependent variable using the statistical technique. The fifth step builds an artificial neural network model and performs a learning process using train set and test set. Finally the last sixth step is to validate the prediction performance of artificial neural network model using the validation data set. The proposed model is compared with statistical predictive model to see whether it had better performance or not. As a result, although the data set in this experiment had much noise, the proposed model showed better results when the model was compared with multiple regression analysis model. If the prediction model of audience reaction was used in the real exhibition, it will be able to provide countermeasures and services appropriate to the audience's reaction viewing the exhibits. Specifically, if the arousal of audience about Exhibits is low, Action to increase arousal of the audience will be taken. For instance, we recommend the audience another preferred contents or using a light or sound to focus on these exhibits. In other words, when planning future exhibitions, planning the exhibition to satisfy various audience preferences would be possible. And it is expected to foster a personalized environment to concentrate on the exhibits. But, the proposed model in this research still shows the low prediction accuracy. The cause is in some parts as follows : First, the data covers diverse visitors of real exhibitions, so it was difficult to control the optimized experimental environment. So, the collected data has much noise, and it would results a lower accuracy. In further research, the data collection will be conducted in a more optimized experimental environment. The further research to increase the accuracy of the predictions of the model will be conducted. Second, using changes of facial expression only is thought to be not enough to extract audience emotions. If facial expression is combined with other responses, such as the sound, audience behavior, it would result a better result.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.1
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• pp.142-151
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• 2022

In this paper, a model combined with explanatory artificial intelligence (xAI) models was presented to secure the reliability of machine learning-based sentiment analysis and prediction. The applicability of the proposed model was tested and described using the IMDB dataset. This approach has an advantage in that it can explain how the data affects the prediction results of the model from various perspectives. In various applications of sentiment analysis such as recommendation system, emotion analysis through facial expression recognition, and opinion analysis, it is possible to gain trust from users of the system by presenting more specific and evidence-based analysis results to users.

• The korean journal of orthodontics
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• v.49 no.1
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• pp.3-11
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• 2019

Objective: The purpose of this study was to investigate the influence of heritability on the craniofacial soft tissue cephalometric characteristics of monozygotic (MZ) twins, dizygotic (DZ) twins, and their siblings (SIB). Methods: The samples comprised Korean adult twins and their siblings (mean age, 39.8 years; MZ group, n = 36 pairs; DZ group, n = 13 pairs of the same gender; and SIB group, n = 26 pairs of the same gender). Thirty cephalometric variables were measured to characterize facial profile, facial height, soft-tissue thickness, and projection of nose and lip. Falconer's method was used to calculate heritability (low heritability, $h^2$ < 0.2; high heritability, $h^2$ > 0.9). After principal components analysis (PCA) was performed to extract the models, we calculated the intraclass correlation coefficient (ICC) value and heritability of each component. Results: The MZ group exhibited higher ICC values for all cephalometric variables than DZ and SIB groups. Among cephalometric variables, the highest ${h^2}_{(MZ-DZ)}$ and ${h^2}_{(MZ-SIB)}$ values were observed for the nasolabial angle (NLA, 1.544 and 2.036), chin angle (1.342 and 1.112), soft tissue chin thickness (2.872 and 1.226), and upper lip thickness ratio (1.592 and 1.026). PCA derived eight components with 84.5% of a cumulative explanation. The components that exhibited higher values of ${h^2}_{(MZ-DZ)}$ and ${h^2}_{(MZ-SIB)}$ were PCA2, which includes facial convexity, NLA, and nose projection (1.026 and 0.972), and PCA7, which includes chin angle and soft tissue chin thickness (2.107 and 1.169). Conclusions: The nose and soft tissue chin were more influenced by genetic factors than other soft tissues.

• Journal of the Korean Society of Clothing and Textiles
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• v.38 no.6
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• pp.810-822
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• 2014

This study investigated the effects of sociocultural influence and body image on appearance enhancement behavior (facial management, clothing selection, and weight/figure management). For data collection, a questionnaire was administrated to 378 female college students in Seoul and Gyeonggi-do from May $23^{rd}$ to June $10^{th}$ 2013. A SPSS 18.0 statistics package was used to analyze data along with descriptive statistical analysis, frequency analysis, factor analysis, reliability analysis, and regression analysis and frequency analysis. The results were as follows. First, sociocultural influences were divided into three factors: media influence, peer influence, and parental influence. Overall sociocultural influences had positive effects on appearance enhancement behavior. Second, body image was divided into: appearances-management, body-satisfaction and body confidence. Sociocultural influences had a significant effect on overall body image. Third, body image positively affected overall appearance enhancement behavior.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.5
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• pp.9-13
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• 2020

Sasang Constitutional Medicine is a traditional Korean medicine optimized for personalized medicine, and despite its effective clinical efficacy, the inaccuracy of constitutional diagnosis has been pointed out as a limitation. To improve the accuracy, a constitutional analysis algorithm based on quantitative data was developed. In this study, a constitutional analysis experience system applied with the algorithm was developed and repeatability was evaluated. The system analyzes the constitution of the experiencer by collecting front and side facial images, audio, and questionnaire and calculating the integrated constitution probability value. To evaluate the repeatability of the probability values of the system was performed five times each for three people, and the coefficient of variation was 4.778%, indicating that the repeatability was sufficient. The system could contribute to the promotion of the awareness of Sasang medicine.

• Journal of Acupuncture Research
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• v.31 no.1
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• pp.149-158
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• 2014

Objectives : The aim of this study is to investigate the influence of anxiety and depression on motor recovery of acute Bell's palsy to estimate how much psychological factors affect the clinical prognosis. Methods : A total of 20 inpatients with acute unilateral Bell's palsy within 1 week of onset participated in this study. The severity of participants' facial palsy was measured by Yanagihara(Y-system) score, FDI and House-Brackmann scale at the time of 1 week and 3 weeks from the onset. The motor recovery of acute Bell's palsy is defined as ${\Delta}Y$-system during 2 weeks. Beck anxiety scale(BAI) and the center for epidermiologic studies depression scale(CES-D) were adopted to assess anxiety and depression, respectively. Correlation analysis and linear regression analysis were conducted between ${\Delta}Y$-system and prognostic factors including anxiety and depression. Results : Significant associations were found between ${\Delta}Y$-system and depression(CES-D) but no significant associations were found between ${\Delta}Y$-system and other prognostic factors, hypertension, diabetes, postauricular pain, disgeusia, age, degree of initial palsy and anxiety(BAI). And a regression equation with 0.295 for coefficient of determination was obtained. Through this analysis, the ${\Delta}Y$-system can be predicted using regression equation which cover 29.5 % of depression index(CES-D). Conclusion : Depression is a significant clinical prognostic factor on motor recovery of acute Bell's palsy. So, Bell's palsy treatment should be combined with psychological care and support.

• Journal of Digital Convergence
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• v.17 no.6
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• pp.433-438
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• 2019

This study investigated the effects of young children's emotional reading ability on prosocial behavior. The participants in this study were 192 young children's. From December 17, December 27, 2018, after conducting a survey on emotional reading ability and prosocial behavior of infants, the data was analyzed using the SPSS WIN 22.0 program for pearson correlation analysis and regression analysis. The results of the analysis suggest the following: First, there were significant relationships between young children's emotional reading ability and prosocial Behavior. Second, young children's emotional reading ability affected prosocial behavior. In conclusion, this study is believed to be the basis for the development of programs to improve emotional reading ability and promote prosocial behavior.

• The KIPS Transactions:PartB
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• v.18B no.6
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• pp.385-388
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• 2011

Patients' privacy protection is a heated issue in medical business, as medical information in digital format transmit everywhere through networks without any limitation. A current protection method for brain images is to deface from the brain image for patient's privacy. However, the defacing process often removes important brain voxels so that the defaced brain image is damaged for medical analysis. An ad-hoc method is proposed to conceal patient's identification by adding cylindrical mask, while the brain keep all important brain voxels. The proposed lossless deformation of brain image is verified not to loose any important voxels. Futhermore, the masked brain image is proved not to be recognized by others.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.1
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• pp.85-92
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• 2020

Deep learning shows outstanding performance in image and video analysis, such as object classification, object detection and semantic segmentation. In this paper, it is analyzed that the performances of deep learning models can be affected by characteristics of train dataset. It is proposed as a method for selecting activation function and optimization algorithm of deep learning to classify facial expression. Classification performances are compared and analyzed by applying various algorithms of each component of deep learning model for CK+, MMI, and KDEF datasets. As results of simulation, it is shown that genetic algorithm can be an effective solution for optimizing components of deep learning model.

• Maxillofacial Plastic and Reconstructive Surgery
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• v.18 no.3
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• pp.396-410
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• 1996

This study was carried out to evaluate the distribution and the degree of the asymmetry existed in normal persons and asymmetric patients, and to investigate the changes of asymmetric patients after orthognathic surgery. The analysis was performed with the posteroanterior cephalometric radiography of 60 normal persons and 31 facial asymmetric patients. The results were as follows : 1. The degree of normal asymmetry existed in normal persons was not significant except MF and Me measurements. 2. The degree of normal asymmetry according to sex difference was not significant except cranial base area. 3. When normal persons were compared to asymmetric patients, there were more measurements which presented significant asymmetry on mandible than on maxilla. 4. When postoperative state was compared to preoperative state, the degree of asymmetry were usually decreased except AGO and GA measurements, especially the Cd, MF, Me, and Cd-Me measurements decreased significantly. 5. When postoperative state was compared to normal persons, 4 measurements of mandible approached significantly the measurements of normal persons.