• The Journal of Korea Robotics Society
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• v.4 no.3
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• pp.210-217
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• 2009

This paper introduces a design of multi-dimensional complex emotional model for various complex emotional expression. It is a novel approach to design an emotional model by comparison with conventional emotional model which used a three-dimensional emotional space with some problems; the discontinuity of emotions, the simple emotional expression, and the necessity of re-designing the emotional model for each robot. To solve these problems, we have designed an emotional model. It uses a multi-dimensional emotional space for the continuity of emotion. A linear model design is used for reusability of the emotional model. It has the personality for various emotional results although it gets same inputs. To demonstrate the effectiveness of our model, we have tested with a human friendly robot.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.213-215
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• 2007

This paper introduces an emotional behavior decision model for intelligent service robots. An emotional model should make different behavior decisions according to the purpose of the robots. We propose an emotional behavior decision model which can change the character of emotional model and make different behavior decisions although the situation and environment remain the same. We defined each emotional element such as reactive dynamics, internal dynamics, emotional dynamics, and behavior dynamics by state dynamic equations. The proposed system model is a linear system. If you want to add one external stimulus or behavior, you need to add just one dimensional vector to the matrix of external stimulus or behavior dynamics. The case of removing is same. The change of reactive dynamics, internal dynamics, emotional dynamics, and behavior dynamics also follows the same procedure. We implemented the proposed emotional behavior decision model and verified its performance.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.8
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• pp.760-768
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• 2007

This paper introduces an emotional behavior decision model based on linear system for intelligent service robots. An emotional model should make different behavior decisions according to the purpose of the robots. We propose an emotional behavior decision model which can change the character of intelligent service robots and make different behavior decisions although the situation and environment remain the same. We defined each emotional element such as reactive dynamics, internal dynamics, emotional dynamics, and behavior dynamics by state dynamic equations. The proposed system model is a linear dynamic system. If you want to add one external stimulus or behavior, you need to add just one dimensional vector to the matrix of external stimulus or behavior dynamics. The case of removing is same. The change of reactive dynamics, internal dynamics, emotional dynamics, and behavior dynamics also follows the same procedure. We implemented a cyber robot and an emotional head robot using 3D character for verifying the performance of the proposed emotional behavior decision model.

• Journal of Internet Computing and Services
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• v.19 no.6
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• pp.125-132
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• 2018

In this paper, we design a programming education model that uses emotional intelligence and apply the model to programming education in elementary school. In our previous work, we found that there is a meaningful correlation between emotional intelligence and programming ability. In this paper, as a follow-up study, we design a programming education model based on a storytelling model and emotional intelligence. In order to test the performance of the proposed model, we applied our proposed model to the 5th grade elementary school students who have no programming experience. Based on extensive survey work and statistical analysis, we found that the experimental group by the programming education using the emotional intelligence got a statistically significant higher achievement than the comparative group by the traditional programming education. We hope that our model will be helpful in programming education in schools.

• The Journal of Industrial Distribution & Business
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• v.12 no.1
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• pp.31-46
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• 2021

Purpose: The purpose of the study is to analyze the characteristics of emotional intelligence and the variables related to emotional intelligence in a comprehensive manner. In addition, the study intends to present research trends and future research directions of emotional intelligence in a Korean context by analyzing the effects of emotional intelligence and its mechanisms. Research Design, Data, and Methodology: 77 KCI listed studies were selected for the analysis, and the research perspective of emotional intelligence, measurement instruments, empirical research and research methods were analyzed. In addition, research directions were suggested based on the analysis results. Results: The results of the analysis were as follows: First, previous researchers used the ability model of emotional intelligence the most. Second, Previous studies tended to focus on behavioral factors as dependent variables affected by emotional intelligence, in addition to attitudes, affection. Third, there were few studies on the antecedents of emotional intelligence, however, most studies dealt with the consequences of emotional intelligence. Fourth, few studies dealt with moderators between emotional intelligence and dependent variables. Fifth, on the research type, most studies were quantitative studies, however, a few of them were qualitative studies (Literature review, in-depth interview). Sixth, with regard to the analysis level, almost all studies were conducted on the individual level of emotional intelligence, and most studies featured a cross-sectional research design (longitudinal research design was rare). Conclusion: First, from the perspective of emotional intelligence, additional research should be focused on not only the ability model of emotional intelligence but also on the trait model or the mixed model in the future. Second, since emotional intelligence is a multidimensional construct, it is necessary to study the profile of emotional intelligence by employing people-centered as well as variable-centered methods. Third, with regard to empirical studies, additional research is needed with respect to not only the emotional intelligence of the subordinate, but also the emotional intelligence of the supervisor (leader) and the emotional intelligence of the group. Fourth, it is necessary to actively utilize not only cross-sectional design but also longitudinal design, and qualitative research and meta-analysis methods should also be adopted.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1025-1030
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• 2005

This paper deals with the emotional model of the software-robot. The software-robot requires several capabilities such as sensing, perceiving, acting, communicating, and surviving. and so on. There are already many studies about the emotional model like KISMET and AIBO. The new emotional model using the modified friendship scheme is proposed in this paper. Quite often, the available emotional models have time invariant human respond architectures. Conventional emotional models make the sociable robot get around with humans, and obey human commands during robot operation. This behavior makes the robot very different from real pets. Similar to real pets, the proposed emotional model with the modified friendship capability has time varying property depending on interaction between human and robot.

• Journal of the Korea Society of Computer and Information
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• v.20 no.12
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• pp.137-143
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• 2015

This study is looking to do a new model which overcomes emotional isolation phenomenons of aged people through using an advanced technology in our community approaching an aging society. Senior welfare has been oriented to economically, medically supported welfare model so far. An ageing society going on, even if the scale of welfare cost is bigger and bigger, the level of satisfaction has been decreasing. This is the fact that the expansion of economical support for the aged in emotional alienation is not only a solution for them suffering from emotional isolation phenomenons, which requires a new model for senior welfare. Above all, because the senior welfare oriented to economically, medically supported welfare model can not be continued any more, a new model is required to be sustainable in national finance. This study has a purpose that recovers emotional life of the aged, improves their quality of life, and offers emotional welfare model to be sustainable economically.

• Journal of Korean Academy of Nursing
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• v.49 no.3
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• pp.307-316
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• 2019

Purpose: This study was conducted to investigate the influence of emotional expressivity, emotional intelligence, affectivity, job autonomy, social support, and emotional labor on clinical nurses' individual well-being and to provide guidelines for interventions and strategies for its improvement. Methods: The sample consisted of 207 nurses recruited from a general hospital in Korea. The participants completed a structured self-report questionnaire comprising measures of emotional expressivity, emotional intelligence, positive affectivity, negative affectivity, job autonomy, supervisor support, coworker support, deep acting, surface acting, emotional exhaustion, and job satisfaction. Data were analyzed using SPSS statistics 22.0 and AMOS 22.0. Results: The final model was a good fit for the data based on the model fit indices. In the path analysis, surface acting, negative affectivity, supervisor support, and coworker support had statistically significant effects on emotional exhaustion, explaining 29.0% of the variance. Deep acting, emotional exhaustion, positive affectivity, and emotional intelligence had statistically significant effects on job satisfaction, explaining 43.0% of the variance. Conclusion: Effective strategies to improve clinical nurses' individual well-being should focus on surface acting, deep acting, affectivity, social support, and emotional intelligence. The results of this study can be utilized as base data to manage emotional labor and improve clinical nurses' individual well-being.

• Science of Emotion and Sensibility
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• v.20 no.1
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• pp.75-82
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• 2017

We propose a novel method for modeling emotional dimensions using expansion of Russell's (1980) emotional dimensions (Circumplex Model). The Circumplex Model represents emotional words in two axes (Arousal, Valence). However, other researchers have insisted that location of word in Russell's model which is expressed by single point could not represent exact position. Consequently, it is difficult to apply this model in engineering fields (such as Science of Emotion & Sensibility, Human-Computer-Interaction, Ergonomics, etc.). Therefore, we propose a new modeling method which expresses emotional word not as a single point but as a region. We conducted survey to obtain actual data and derived equations using ellipse formula to represent emotional region. Furthermore, we applied ANEW and IAPS which are commonly used in many studies to our emotional model using pattern recognition algorithm. Using our method, we could solve problems with Russell's model and our model is easily applicable to the field of engineering.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.7
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• pp.1557-1564
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• 2010

In this paper, we propose a maximum entropy-based emotion recognition model using the individual average difference of emotional signal, because an emotional signal pattern depends on each individual. In order to accurately recognize a user's emotion, the proposed model utilizes the difference between the average of the input emotional signals and the average of each emotional state's signals(such as positive emotional signals and negative emotional signals), rather than only the given input signal. With the aim of easily constructing the emotion recognition model without the professional knowledge of the emotion recognition, it utilizes a maximum entropy model, one of the best-performed and well-known machine learning techniques. Considering that it is difficult to obtain enough training data based on the numerical value of emotional signal for machine learning, the proposed model substitutes two simple symbols such as +(positive number)/-(negative number) for every average difference value, and calculates the average of emotional signals per second rather than the total emotion response time(10 seconds).