• Research in Community and Public Health Nursing
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• v.28 no.4
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• pp.482-493
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• 2017

Purpose: This study aims to investigate the individual and environmental factors related to emotional/behavioral problems to early adolescence in Korea by applying multilevel modeling. Methods: From the database of the 2014 Korean Child and Youth Panel Survey (KCYPS), the researchers selected 1,977 adolescents who are in the second year of middle school. Multilevel model analysis was performed to estimate the impact of relevant factors at the individual and environmental levels. Results: At the individual level, the significant factors associated with emotional/behavioral problems included BMI and study tendency in boys, and drinking, study tendency and economic levels in girls. At the environmental level, the significant factor associated with emotional/behavioral problems included relationship with the teacher. Conclusion: The emotional/behavioral problems of early adolescence are influenced not only by the individual factors but also by the environment factor. Therefore, the environment surrounding the adolescents should also be considered to prevent emotional/behavioral problems.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.11
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• pp.1496-1505
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• 2018

The technology of emotion recognition is necessary for human computer interaction communication. There are many cases where one cannot communicate without considering one's emotion. As such, emotional recognition technology is an essential element in the field of communication. n this regard, it is highly utilized in various fields. Various bio-sensor sensors are used for human emotional recognition and can be used to measure emotions. This paper proposes a system for recognizing human emotions using two physiological sensors. For emotional classification, two-dimensional Russell's emotional model was used, and a method of classification based on personality was proposed by extracting sensor-specific characteristics. In addition, the emotional model was divided into four emotions using the Support Vector Machine classification algorithm. Finally, the proposed emotional recognition system was evaluated through a practical experiment.

• Korean Journal of Childcare and Education
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• v.14 no.6
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• pp.241-255
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• 2018

Objective: The purpose of this research was to examine the moderating effect of children's negative emotionality on the relationship between maternal attitude toward children's emotional expression based on the differential susceptibility model. Methods: Participants were 216 preschool children including 116 boys and 100 girls from day care centers and preschools located in Chungchung province and Seoul. EAS was used to measure the children's negative emotionality. The children's empathy quotient was used to measure empathy. Mothers reported their attitude toward children's emotional expression. Results: The results revealed that the association between empathy and maternal suppression of children's emotional expression was significant only for the children with high levels of negative emotionality. Moreover, the magnitude of association between empathy and maternal acceptance of children's emotional expression was greater for high levels of negative emotionality. Conclusion/Implications: It was concluded that these findings supported the differential susceptibility model.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.3
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• pp.395-400
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• 2011

In this paper, we propose an study of the facial emotion recognition considering the dynamical variation of emotional state in facial image sequences. The proposed system consists of two main step: facial image based emotional feature extraction and emotional state classification/recognition. At first, we propose a method for extracting and analyzing the emotional feature region using a combination of Active Shape Model (ASM) and Facial Action Units (FAUs). And then, it is proposed that emotional state classification and recognition method based on Hidden Markov Model (HMM) type of dynamic Bayesian network. Also, we adopt a Harmony Search (HS) algorithm based heuristic optimization procedure in a parameter learning of HMM in order to classify the emotional state more accurately. By using all these methods, we construct the emotion recognition system based on variations of the dynamic facial image sequence and make an attempt at improvement of the recognition performance.

• The Journal of Korean Academic Society of Nursing Education
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• v.28 no.3
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• pp.305-316
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• 2022

Purpose: The purpose of this study was to construct a structural equation model of organizational commitment in hospital nurses based on a job demands-resources model and to confirm the moderating effect(s) according to the nurses' generation. Methods: The model was constructed of the exogenous variables of social support, emotional intelligence, emotional labor, and job conflict and the endogenous variables of burnout, job engagement, and organizational commitment. The participants were 560 hospital nurses working in 3 general hospitals. Data were collected from August 1 to September 30, 2021, and analyzed using SPSS Window 23.0 and IBM AMOS 23.0. Results: The strongest factor directly influencing hospital nurses' organizational commitment was social support. In a multiple group analysis, nurses' generation had a partial moderating effect. In a generation-specific analysis, the Z generation group was higher than the X and Y generation groups in the variables of emotional labor and burnout related to organizational commitment. Conclusion: Based on the findings of this study, to improve hospital nurses' organizational commitment, social support is needed as an important management strategy. At the organizational level, we need to develop ways to improve organizational commitment by reducing the emotional labor and burnout of Generation Z.

• The Journal of the Korea Contents Association
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• v.20 no.9
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• pp.558-576
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• 2020

The purpose of the research was to verify the mediating effect of social support and cognitive emotional regulation strategy when office worker's emotional expressive ambivalence influences on interpersonal stress. A survey was conducted with 422 office workers from August to September of 2018. SPSS, AMOS and Mplus were used for descriptive statistics, correlation analysis, verification of structural equation modeling and mediated effect. There was a partial mediating effect in emotional expressive ambivalence of self-defense model, a complete mediating effect in relational emotional expressive ambivalence model. In both self-defense and relational emotional expressive ambivalence model, double mediation effect of passing through support and cognitive emotional regulation strategy in the relationship between emotional expressive ambivalence and interpersonal stress was significant. This study sought ways to reduce interpersonal stress by increasing the level of perception of social support and using adaptive cognitive emotional control strategies for office workers.

• Journal of the Korea Society of Computer and Information
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• v.25 no.4
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• pp.133-140
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• 2020

Emotional analysis is an application of opinion mining that analyzes opinions and tendencies of people appearing in unstructured text. Recently, emotional analysis of social media has attracted attention, but social media contains newly-created words and slang, so it is not easy to analyze with existing emotional analysis. In this study, I design a new emotional analysis system to solve these problems. The proposed system is possible to analyze various emotions as well as positive and negative in social media including newly-created words and slang. First, I collect newly-created words and slang related to emotions that appear in social media. Then, expand the existing emotional model and use it to quantify the degree of sentiment in emotional words. Also, a new sentiment dictionary is constructed by reflecting the degree of sentiment. Finally, I design an emotional analysis system that applies an sentiment dictionary that includes newly-created words and an extended emotional model.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.5
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• pp.134-139
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• 2008

In this paper, we propose a story generation system using multi emotional agents. The proposed multi emotional agents are equipped with multiple emotional model so that it can be used as individually personalized agents that can generates unique storylines. Basically these kinds of multi emotional agents are easily employed as Avatar or NPC in computer games. In the proposed system, emotional agents are used as actor or actress whose characters and preferences are different each other. The storylines generated using the proposed system are realistic since the characters are emotional as humans.

• Journal of IKEEE
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• v.24 no.4
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• pp.998-1003
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• 2020

In this paper, an emotion training method using emotional adaptation is proposed to improve the performance of the existing emotion recognition system. For emotion adaptation, an emotion speech model was created from a speech model without emotion using a small number of training emotion voices and emotion adaptation methods. This method showed superior performance even when using a smaller number of emotional voices than the existing method. Since it is not easy to obtain enough emotional voices for training, it is very practical to use a small number of emotional voices in real situations. In the experimental results using a Korean database containing four emotions, the proposed method using emotional adaptation showed better performance than the existing method.

• Korean Journal of Culture and Social Issue
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• v.27 no.4
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• pp.475-503
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• 2021

The purpose of this study is to clarify the constructs of emotion suppression and help understanding on the multidimensional nature of emotion suppression by classifying constructs for suppression according to the KMW model. Also, this study examined the gender differences of emotion suppression. For this purpose, 657 adult male and female subjects were evaluated for attitude toward emotions, and difficulty in emotional regulation, as well as depression, state anger and daily stress scale. As a result of the exploratory factor analysis on the scales related to the emotion suppression factors, the emotion suppression factors corresponding to each stage of the KMW model were found to be 'distraction against emotional information, 'difficulty in understanding and interpretation of emotions', 'emotion control beliefs', 'vulnerability on emotional expression beliefs'. Next, the study participants were classified by performing a cluster analysis based on each emotion suppression factor. As a result, four clusters were extracted and named 'emotional control belief cluster', 'emotional expression cluster', 'emotional attention failure cluster', and 'general emotional suppression cluster'. As a result of examining the average difference of male depression, depression, state anger, and daily stress for each group, significant differences were found in all dependent variables. As a result of examining whether there is a difference in the frequency of emotional suppression clusters according to gender, the frequency of emotional suppression clusters was high in men, and the ratio of emotional expression clusters was high in women. Finally, it was analyzed whether there was a gender difference in the effect of the emotional suppression cluster on psychosocial adaptation, and the implications were discussed based on the results of this study.