• Journal of Oriental Neuropsychiatry
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• v.18 no.2
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• pp.25-34
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• 2007

Objective : This study was done to investigate the differences of HRV(Heart Rate Variability) change as the response to the emotional stimulus in each Sasang constitutions. Method : We investigated 44 healthy volunteers consisted of 10 Soyangin, 14 Soeumin and 20 Taeumin. After diagnosing the Sasang constitution by specialist of Sasang medicine, we measured the baseline emotional state(100 sec) before the stimulus, the changing emotional state(100 sec) while fearful film was being played. And we rechecked the emotional state(100 sec) while taking a rest. At last, volunteers checked the questionnaire for emotional response. We analysed ECG data with HRV-time domain and frequency domain analysis. Results : (1) There were no significant difference in Mean-RR , SDNN between each groups. (2) LF of Taeumin group significantly increased by the emotional stimulation compared with other groups. (3) There was no significant difference in TP, HF, normalized LF, normalized HF, but the variation of each period in Taeumin group was bigger than those of other groups. (4) Soeumin group reported that they felt significant disgust-emotion in the questionnaire compared with other groups. Conclusion : Taeumin group showed significant emotional changes on HRV by fear stimulus film.

• Science of Emotion and Sensibility
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• v.3 no.2
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• pp.29-40
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• 2000

Autonomic and EEG responses were analyzed in 32 college students exposed to visual stimulation with Korean Affective Picture System (KAPS) and 36 students exposed to the International Affective Picture System (IAPS). Cardiac, electrodermal, and electrocortical measures were recorded during 30 sec of viewing affective pictures. The slides intended to elicit basic emotions (fear, anger, surprise, disgust, and sadness) were presented to subjects via Kodak slide-projector. The aim of the study was to differentiate autonomic and EEG responses associated with the same negative valence emotions elicited by KAPS and IAPS stimulation and to identify the influence of cultural relevance on physiological reactivity. The analysis of obtained results revealed significant differences in physiological responsiveness to emotionally negative valence slides from KAPS and IAPS. The typical response profile for all emotions elicited by the KAPS included HR acceleration (except surprise), and increase of electrodermal activity, slow and fast alpha blocking and fast beta power increase in EEG, which was not associated with significant asymmetry (except fast alpha in sadness). Stimulation with the IAPS evoked HR deceleration, specific electrodermal responses with relatively high tonic electrodermal activation, alpha-blocking and fast beta increase, and was accompanied also by theta power increase and marked frontal asymmetry (e.g., fast beta, theta asymmetries in sadness, fast alpha in fear). Physiological responses to fear and anger-eliciting slides from the IAPS were significantly less profound and were accompanied by autonomic and EEG changes more typical for attention rather than negative affect. Higher cardiovascular and electrodermal reactivity to fear emotion observed in the KAPS, e.g., as compared to data with the IAPS as stimuli, can be explained by cultural relevance and higher effectiveness of the KAPS in producing certain emotions such as fear in Koreans.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.1
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• pp.1-5
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• 2009

This paper suggests to apply mirror-reflected method based 2D emotion recognition database to 3D application. Also, it makes facial expression of fuzzy modeling using probability of emotion. Suggested facial expression function applies fuzzy theory to 3 basic movement for facial expressions. This method applies 3D application to feature vector for emotion recognition from 2D application using mirror-reflected multi-image. Thus, we can have model based on fuzzy nonlinear facial expression of a 2D model for a real model. We use average values about probability of 6 basic expressions such as happy, sad, disgust, angry, surprise and fear. Furthermore, dynimic facial expressions are made via fuzzy modelling. This paper compares and analyzes feature vectors of real model with 3D human-like avatar.

• Journal of Digital Contents Society
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• v.18 no.8
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• pp.1537-1542
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• 2017

Emotion plays a key role in both generating and understanding narrative. In this article we analyzed the emotions represented in a movie script based on 8 emotion types from the wheel of emotions by Plutchik. First we conducted manual emotion tagging scene by scene. The most dominant emotions by manual tagging were anger, fear, and surprise. It makes sense when the film script we analyzed is a thriller-genre. We assumed that the emotions around the climax of the story would be heightened as the tension grew up. From manual tagging we could identify three such duration when the tension is high. Next we analyzed the emotions in the same script using Python-based NLTK VADERSentiment tool. The result showed that the emotions of anger and fear were most matched. The emotion of surprise, anticipation, and disgust, however, scored lower matching.

• Journal of Korea Society of Industrial Information Systems
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• v.12 no.3
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• pp.60-68
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• 2007

In this paper, we propose an automatic facial expressions recognition system to analyze facial expressions (happiness, disgust, surprise and neutral) using tree structures based on heuristic rules. The facial region is first obtained using skin-color model and connected-component analysis (CCs). Thereafter the origins of user's eyes are localized using neural network (NN)-based texture classifier, then the facial features using some heuristics are localized. After detection of facial features, the facial expression recognition are performed using decision tree. To assess the validity of the proposed system, we tested the proposed system using 180 facial image in the MMI, JAFFE, VAK DB. The results show that our system have the accuracy of 93%.

• Journal of the Korea Society of Computer and Information
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• v.11 no.4 s.42
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• pp.207-219
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• 2006

The purpose of this study is to provide to alternatives to improve the relationship of local community resident of the rural-urban consolidation districts in analyzing the case of Jeollanamdo Suncheon city that has consolidated for around 10 years since 1th January 1995. The method of this study is to survey 335 number of Suncheon residents. The evaluation criteria about relationship of local community resident. used in this study were the unity of residents, the reconciliation of residents, and the satisfying degree of public administrative services. According to this survey. aspect of reconciliation of residents, access of administrative organ, unity of residents. satisfying degree of residents and administrative information are showed a little the positive effect. But locational preference of disgust facilities are appeared ordinary and negative sight.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.8
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• pp.199-208
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• 2019

The escape theory is the theory of problem behavior such as suicide. The purpose of this study is to investigate the causes of gaming disorder, which has been attracting attention as a typical youth problem, through escape theory. Suicide theory is a process in which the problem triggered by the negative external environment flows into internal attribution and self-criticism, and this leads to a process leading to problematic behavior with disgust self-awareness. This process was applied to the environment, psychology, and behavior of adolescents. As a result, the lack of affection and consistency of the parents resulted in negative external environment, which affected the self-esteem of children by creating a negative external environment. And low self-esteem caused negative emotions, lowered self control, and confirmed to induce game addiction. The results of this analysis show that game addiction has a structure similar to obsessive behaviors such as binge eating and shopping addiction explained through the escape theory model and it is necessary to concentrate more on the environmental psychological factors for game addiction research.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.3
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• pp.333-340
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• 2022

The COVID-19 has made everyone anxious and people need to keep their distance. It is necessary to conduct collective assessment and screening of college students' mental health in the opening season of every year. This study uses and trains a multi-layer perceptron neural network model for deep learning to identify facial emotions. After the training, real pictures and videos were input for face detection. After detecting the positions of faces in the samples, emotions were classified, and the predicted emotional results of the samples were sent back and displayed on the pictures. The results show that the accuracy is 93.2% in the test set and 95.57% in practice. The recognition rate of Anger is 95%, Disgust is 97%, Happiness is 96%, Fear is 96%, Sadness is 97%, Surprise is 95%, Neutral is 93%, such efficient emotion recognition can provide objective data support for capturing negative. Deep learning emotion recognition system can cooperate with traditional psychological activities to provide more dimensions of psychological indicators for health.

• 모자간호학회지
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• v.4 no.1
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• pp.41-51
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• 1994

The purposes of this study were to identify responses of nursing students following clinical maternity nursing practice, to develop data of further effective clinical maternity nursing practice, to understand nursing students perceive the natural maturation process toward pregnancy delivery and puerperal process, to help the nursing students achieve personality growth and development through clinical maternity nursing practice. The subjects were 35 senior nursing students from the Department of Nursing Science of Chung-Ang University. The data were collected from the 1st semester (Feb.22$\sim$June 9) to the 2nd semester(Aug.23$\sim$Nov.10), 1993 through self-reporting using an open ended questionnaire about perception and feelings regarding the normal delivery process. The data analysis used descriptive method. Results of the study were as follows : 1. Following clinical practice in maternity nursing, the responses of the nursing students were collected included both positive and negative aspects. The positive responses were classified in to four categories and each category included subgroups. One group, labelled as $\ulcorner$The birth of noble life$\lrcorner$ had a subgroup, (I felt the mystery and wonder of life), another group, $\ulcorner$After delivery, comfort and satisfaction$\lrcorner$ with the subgroup (I can bear to see the comfort and relief beyond pain) (C/S is better than vaginal delivery) (Very easy), the 3rd group, $\ulcorner$ I realized family friendship and support$\lrcorner$ with subgroup (Honorable, Magnificient) (I thank my parents ) (It's good to looking at my husband's support), and the 4th group, $\ulcorner$The birth of a healthy baby$\lrcorner$, with its subgroup, (baby looks pretty and healthy). 2. The negative responses were classified in eight categories and each category included subgroups. One group labelled as $\ulcorner$Fear$\lrcorner$, had subgroups of (Terrible, Horrible) (Shock) (Dread), another group, $\ulcorner$Tension$\lrcorner$, and its subgroup, (I became tense about stories heard before clinical practice), the 3rd group, $\ulcorner$surprise$\lrcorner$ and its subgroup (I was surprised at the delivery process), the 4th group, $\ulcorner$Power lessness$\lrcorner$ and its subgroup, (I watched the labor pain impatiently), the 5th group $\ulcorner$Apathy$\lrcorner$ ; and its subgroup, (I didn't feel the empathy for the labor pain of the pregnant women), the 6th group, $\ulcorner$Disgust$\lrcorner$ and its subgroup, (Disgust, Embarrassed), the 7th group, $\ulcorner$Inevitable destiny$\lrcorner$ and its subgroups (necessity of self-sacrifice and difficulty) (I accepted it as a women's destiny) (I can't do it), the last group, $\ulcorner$There seems to be trouble$\lrcorner$ and its subgroup, (It seems to have been a little too hard for mother and baby). Suggestions for further studies are as follows : 1. Nursing students should receive intensive education about $\ulcorner$The birth of noble life$\lrcorner$ $\ulcorner$After delivery, comfort and satisfaction$\lrcorner$ $\ulcorner$I realized family friendship and support$\lrcorner$ $\ulcorner$The birth of a healthy baby$\lrcorner$, so that a more positive attitude can be developed before clinical maternity nursing. 2. Nursing students should be given an orientation which is reality based and related clinical maternity nursing (using for A.V. Materials), so that they will not feel they tension, of the negative categories. 3. Nursing students should be received articles on Pain Relief Method, so that they will be prepared activie and positive in the clinical practice, and therefore they will not feel the powerlessness, of the negative categories. 4. F/U for responses of nursing students should be checked following clinical maternity nursing to evaluate the effects of the instruction.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.73-85
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• 2013

Nowadays, in today's information society, the importance of the knowledge service using the information to creative value is getting higher day by day. In addition, depending on the development of IT technology, it is ease to collect and use information. Also, many companies actively use customer information to marketing in a variety of industries. Into the 21st century, companies have been actively using the culture arts to manage corporate image and marketing closely linked to their commercial interests. But, it is difficult that companies attract or maintain consumer's interest through their technology. For that reason, it is trend to perform cultural activities for tool of differentiation over many firms. Many firms used the customer's experience to new marketing strategy in order to effectively respond to competitive market. Accordingly, it is emerging rapidly that the necessity of personalized service to provide a new experience for people based on the personal profile information that contains the characteristics of the individual. Like this, personalized service using customer's individual profile information such as language, symbols, behavior, and emotions is very important today. Through this, we will be able to judge interaction between people and content and to maximize customer's experience and satisfaction. There are various relative works provide customer-centered service. Specially, emotion recognition research is emerging recently. Existing researches experienced emotion recognition using mostly bio-signal. Most of researches are voice and face studies that have great emotional changes. However, there are several difficulties to predict people's emotion caused by limitation of equipment and service environments. So, in this paper, we develop emotion prediction model based on vision-based interface to overcome existing limitations. Emotion recognition research based on people's gesture and posture has been processed by several researchers. This paper developed a model that recognizes people's emotional states through body gesture and posture using difference image method. And we found optimization validation model for four kinds of emotions' prediction. A proposed model purposed to automatically determine and predict 4 human emotions (Sadness, Surprise, Joy, and Disgust). To build up the model, event booth was installed in the KOCCA's lobby and we provided some proper stimulative movie to collect their body gesture and posture as the change of emotions. And then, we extracted body movements using difference image method. And we revised people data to build proposed model through neural network. The proposed model for emotion prediction used 3 type time-frame sets (20 frames, 30 frames, and 40 frames). And then, we adopted the model which has best performance compared with other models.' Before build three kinds of models, the entire 97 data set were divided into three data sets of learning, test, and validation set. The proposed model for emotion prediction was constructed using artificial neural network. In this paper, we used the back-propagation algorithm as a learning method, and set learning rate to 10%, momentum rate to 10%. The sigmoid function was used as the transform function. And we designed a three-layer perceptron neural network with one hidden layer and four output nodes. Based on the test data set, the learning for this research model was stopped when it reaches 50000 after reaching the minimum error in order to explore the point of learning. We finally processed each model's accuracy and found best model to predict each emotions. The result showed prediction accuracy 100% from sadness, and 96% from joy prediction in 20 frames set model. And 88% from surprise, and 98% from disgust in 30 frames set model. The findings of our research are expected to be useful to provide effective algorithm for personalized service in various industries such as advertisement, exhibition, performance, etc.