• The Journal of the Convergence on Culture Technology
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• v.5 no.2
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• pp.299-303
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• 2019

This study is one of the preparatory tasks for this researcher to do Emotion Coding on AI. This time, we're doing an Emotion Coding for Sijo "Blue Mountain is My Meaning" by Hwang Jin-yi. Huang Jin-yi is doing Emotion Coding on Blue Mountain and Green Stream in this Sijo. These Emotions code, as seen in Emotion Codon, as in UUU. This phenomenon can be described in the form in which this researcher hypothesized. In other words, this Emotion Coding acts as a catalyst for the formation of an amino acid called phenylalanine. If we continue this research, it is thought that the function of literature, which is more healing, will be utilized in the future of mankind.

• Journal of the Korean Applied Science and Technology
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• v.41 no.3
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• pp.657-665
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• 2024

The purpose of this review is to provide a comprehensive analysis of the intricate relationships between cognitive control, depression, and emotion regulation. Cognitive control, encompassing processes such as attentional control, inhibitory control, and cognitive flexibility, plays a central role in regulating thoughts, behaviors, and emotions in alignment with internal goals and external demands. Depression, characterized by persistent feelings of sadness, hopelessness, and cognitive impairments, is associated with deficits in cognitive control processes. Emotion regulation strategies, such as cognitive reappraisal and expressive suppression, enable individuals to modulate emotional experiences and responses. The bidirectional relationships between cognitive control, depression, and emotion regulation underscore the complexity of cognitive and emotional processes in depression. Understanding these relationships is crucial for developing targeted interventions aimed at promoting cognitive and emotional well-being and preventing depression onset and recurrence. Moreover, recognizing the roles of cognitive control and emotion regulation in depression holds promise for informing clinical practice and enhancing therapeutic interventions. This review highlights the importance of considering cognitive control and emotion regulation in the assessment and treatment of depression and provides insights for future research and clinical practice.

• Journal of The Korean Society of Integrative Medicine
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• v.4 no.1
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• pp.65-72
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• 2016

Purpose : This study was carried out to find out the relationship between emotion intelligence, learning flow and career stress of nursing students and influence factors for career stress. Methods : This study targeted 197 university students in their freshman-senior year attending College of Nursing located in P Metropolitan City. For collected data, real numbers and percentage, mean and standard deviation and multiple regression analysis were carried out by using PASW 21.0 program and the correlation between emotion intelligence, learning flow and career stress was analyzed with Pearson's correlation coefficients. Results : Emotional self-awareness(M=3.80, SD =.71), clear goals(M=3.39, SD=.90) and school environment stress(M=2.97, SD=.96) were found to be high in the degree of emotion intelligence, learning flow and career stress of the subjects. The relationship between emotion intelligence and learning flow showed a positive correlation(r=.489, p<.01) in the correlation between emotion intelligence, learning flow, career stress and emotion intelligence showed a negative correlation with career stress(r=-.204, p<.01). Emotion intelligence and learning flow show that career stress is predicted significantly (${\beta}$ =-.15, p < .01) and explained a career stress variate as 18%(F = 24.5, p < .01). Conclusion : Emotion intelligence of nursing students was found to be very influential on the degree of learning flow or career stress. Based on the results of this study, replication studies on emotion intelligence and career stress are needed and the development of intervention programs to increase emotion intelligence is needed.

• Science of Emotion and Sensibility
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• v.12 no.4
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• pp.381-392
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• 2009

The aim of this study was to develop a research protocol that provides standardized conditioning stimuli in effectively evoking emotion-specific responses in children. The protocol targets five specific emotions(i.e., happiness, sadness, anger, distress, and boredom) by introducing study participants to a combination of music, color, stories, and dolls. This research protocol also includes a self-report emotion assessment scale specially developed for this study to verify the types of emotion induced. Evaluation of the method entailed triangulation of the results from the subjects' self-reported emotional state corresponding to each conditioned stimulus as well as behavioral observations conducted by researchers. Findings suggest that this new protocol effectively evokes five emotions in correspondence to the way it was intended for appropriate emotion induction. Additionally, results showed that female children than male children are more likely to feel boredom; and school-aged children were more likely to react to sadness than pre-school children.

• Journal of Information Technology Applications and Management
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• v.21 no.4
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• pp.35-50
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• 2014

This study examines the relationshipsbetween the antecedents of repurchase intention, with special interest in the role of appraisal emotion and recreation motivation for arts attendance. Appraisal emotion is found to have significant influence on perceived value while recreation motivation is found to directly influence appraisal emotion and perceived value. In a addition to customer satisfaction, peripheral service quality is the only factor that directly affectsrepurchase intention. Arts managers ought to focus on improving the whole experience of performing arts.

• Science of Emotion and Sensibility
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• v.15 no.1
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• pp.121-132
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• 2012

Recently, interest in emotional technology has escalated and its application has extended to many fields, from both an industrial (product) and service (culture, tourism, medical, education, advertising) perspective. Moreover, culture has become a fundamental aspect of modern industry, playing key roles in: gaming, exhibitions, performances, sports, tourism, design, edutainment, as well as various content distribution industries. The prospect of applying emotional technology for cultural content industries makes up for more than half of the 'plan-manufacture-distribution-marketing' process, and thereby also serves as driving force for the growth of a nation. The primary objective of the following research is analyze successful cases from the past through utilization of emotional technology, and to speculate on efficient directions for future research into developing emotional contents. To achieve this, some of the key terms have been defined and elaborated for the sake of clarity. The terms are as follows: emotion, emotion engineering, science of emotion, emotional technology, and emotional contents. Furthermore, studies were conducted based on the six different fields surrounding CT R&D to observe how projects involving emotional technology have succeeded both on a national and global scale. Based on this analysis, this research aims to develop personalized 'Concierge' service-providing contents, contents designed to maximize performance ability of humans, and contents that could be controlled simply via emotion to effectively spread the culture of Korea by focussing on 'fusion' content development. The following research data may hopefully serve as a basic reference to industries navigating towards emotional content development.

• Journal of the Korea Society of Computer and Information
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• v.22 no.7
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• pp.75-82
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• 2017

Correct prediction of emotion is essential for developing advanced health devices. For this purpose, neural network has been successfully used. However, interpretation of how a certain emotion is predicted through the emotion prediction neural network is very tough. When interpreting mechanism about how emotion is predicted by using the emotion prediction neural network can be developed, such mechanism can be effectively embedded into highly advanced health-care devices. In this sense, this study proposes a novel approach to interpreting how the emotion prediction neural network yields emotion. Our proposed mechanism is based on HRV (heart rate variability) measurements, which is based on calculating physiological data out of ECG (electrocardiogram) measurements. Experiment dataset with 23 qualified participants were used to obtain the seven HRV measurement such as Mean RR, SDNN, RMSSD, VLF, LF, HF, LF/HF. Then emotion prediction neural network was modelled by using the HRV dataset. By applying the proposed mechanism, a set of explicit mathematical functions could be derived, which are clearly and explicitly interpretable. The proposed mechanism was compared with conventional neural network to show validity.

• Journal of Institute of Convergence Technology
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• v.1 no.2
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• pp.1-5
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• 2011

It is known that as many as 15-20 in 10,000 children are diagnosed with autistic spectrum disorder. A framework of the treatment system for children with autism using affective computing technologies was proposed by Chung and Yoon. In this paper, a prototype for the framework is proposed. It consists of emotion stimulating module, multi-modal bio-signal sensing module, treatment module using virtual reality, and emotion recognition module. Primitive experiments on emotion recognition show the usefulness of the proposed system.

• Science of Emotion and Sensibility
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• v.15 no.1
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• pp.133-140
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• 2012

We designed a novel individualization process for improving personal emotion recognitions in real time. The designed individualization process was performed by a neutralization algorithm of physiological signals, a subjective emotion reflection of a user updated by personal emotion rules in real time. The physiological signals such as PPG(Photoplethysmography), GSR(Galvanic skin reflex), and SKT(Skin temperature) were measured and analyzed to estimate an emotion states of users. Regulating the emotion status using by emotion rules was performed by reflecting subjective evaluations. The agreement of emotion recognition between of individualization and non-individualization method was estimated by 10 undergraduates (5 females, mean age: $22.1{\pm}2.2$) of Sangmyung University. During the emotion recognition test, 45 images were randomly presented to each participant five times. In results, the proposed individualization process showed the agreement of 71.67 % which was five times higher than when the process was not applied. Therefore, in this study, we demonstrated that the individualization process was significantly useful for customizing emotion recognitions of personal users in real time. The individualization process will be able to improve satisfactions in various emotion related applications and services in the nearer future.

• Journal of Broadcast Engineering
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• v.27 no.6
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• pp.940-943
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• 2022

This study aims to analyze the Korean dataset by performing Korean sentence Emotion Analysis in the radio listeners' text messages collected personally. Currently, in Korea, research on the Emotion Analysis of Korean sentences is variously continuing. However, it is difficult to expect high accuracy of Emotion Analysis due to the linguistic characteristics of Korean. In addition, a lot of research has been done on Binary Sentiment Analysis that allows positive/negative classification only, but Multi-class Emotion Analysis that is classified into three or more emotions requires more research. In this regard, it is necessary to consider and analyze the Korean dataset to increase the accuracy of Multi-class Emotion Analysis for Korean. In this paper, we analyzed why Korean Emotion Analysis is difficult in the process of conducting Emotion Analysis through surveys and experiments, proposed a method for creating a dataset that can improve accuracy and can be used as a basis for Emotion Analysis of Korean sentences.