• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.276-279
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• 2003

Generally, it is known that human beings have both emotion and rationality. Especially, emotion is so subjective that human beings might act in different way for the same environment according to their own emotion. Emotion also plays very important role in communication with someone else. For an agent, even though it is designed to act delicately, when it is designed without internal emotion, it can not interact dynamically just like human beings. In this paper, we suggest an agent which action is effected by not only rationality but also emotion to make it interact with human beings dynamically. It is composed of supervised learning, SOM (Self-Organizing Map) and fuzzy decision.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.2 no.2
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• pp.23-28
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• 2009

This study describes an emotion classification method using two different feature parameters of four-channel EEG signals. One of the parameters is linear prediction coefficients based on AR modelling. Another one is cross-correlation coefficients on frequencies of ${\theta}$, ${\alpha}$, ${\beta}$ bands of FFT spectra. Using the linear predictor coefficients and the cross-correlation coefficients of frequencies, the emotion classification test for four emotions, such as anger, sad, joy, and relaxation is performed with an artificial neural network. The results of the two parameters showed that the linear prediction coefficients have produced the better results for emotion classification than the cross-correlation coefficients of FFT spectra.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.1
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• pp.155-161
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• 2014

This study presents the real-time emotion image contents player to induce the user's emotion efficiently. The emotion image contents player was designed to efficiently induce by giving a change in the color, brightness, saturation of image contents corresponded to the user's emotion. In the emotion recognition module, physiological signal of pulse, skin temperature, skin resistance which based on autonomic nervous system were used. The emotion recognition part used physiological signal of pulse, skin temperature, skin resistance based on autonomic nervous system. The image as emotional contents was used with the 9 kinds emotion area classified in international affective picture system(IAPS). As experimental results, the use's emotion that match the image's emotion with the emotion image contents player was derived 10% more accurately. The emotion contents player is expected to increase emotional feeling between users's emotion and contents emotion duo to the real-time emotion reflection.

• The Journal of the Korea Contents Association
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• v.18 no.9
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• pp.346-356
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• 2018

The Purpose of this study is to examine the effect of communication competence and empathy on stress coping in college students. The research problems were verified by correlation analysis and multivariate regression analysis. A questionnaire survey was conducted on 292 college students. The findings are as follows. First, college students who have high communication competence show more problem-focused coping, social-support seeking coping, and self-soothing coping in stressful conditions, but less emotion-oriented coping and avoidance-oriented coping. Particularly, it is found that behavioral flexibility in communication competence has the greatest effect on problem-focused coping and emotion-oriented coping. Similarly, affiliation/support influences social support seeking coping, interaction management influences self-soothing coping and avoidance-oriented coping. Second, college students who have high empathy are also found more problem-focused coping, social-support seeking coping, and self-soothing coping in stressful conditions. Especially it is found that role-taking in empathy has the greatest effect on problem-focused coping self-soothing coping. Similarly, emotion recognition influences avoidance-oriented coping, emotional resonance influences emotion-oriented coping, authenticity influences social-support seeking coping.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.1
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• pp.162-168
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• 2014

In this study, we propose a emotion sharing system that is sharing users emotion change according to the location of the user where users was shared his emotion information and to the emotion. The system consists of a emotion sharing server and mobile smartphone apps. Emotion smartphone app represent status of emotion and location of users who wants to share emotion at map services based the Google Map API. Emotion sharing server was implemented using a RESTful way to allow emotion sharing between different variety platform besides mobile platforms. Emotion information that is exchanged on a emotion sharing server is stored in an XML fromat. We were confirm emotion sharing system that it could be sharing moving emotion change according to the user's location through map service.

• Journal of Korea Multimedia Society
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• v.17 no.7
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• pp.866-878
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• 2014

On Korean websites, people often use several Korean vowels or consonants solely, which is the way to express emotion. This way of expression has scarcely been examined seriously, though it is one of the most popular online slangs. This is an exploratory study that reveals how and how much these expressions are used on social media. Data crawling technique was used as a way to examine the usage of vowels and consonants in ordinary situations. 6 'Facebook pages' popular among Korean users are selected, and about 2.5 million comments are collected from posts in those pages. 10 expressions, including 'ㅋ(K)', 'ㅎ(H)', 'ㅜ(U)', are counted and analyzed from the collected texts of comments. As a result, several patterns of using vowels and consonants are found. Especially, 'ㅋ(K)' is used much more frequently than other vowels or consonants, and used more continually. It is also found that the patterns of using vowels or consonants in writing comments changes as the mood of posts or the characteristics of Facebook pages.

• The Journal of Korean Institute for Practical Engineering Education
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• v.4 no.2
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• pp.171-175
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• 2012

Recently, the research on ICT (Information and Communication Technology), which cognizes and communicates human's emotion through information technology, is increasing. For instance, there are researches on phones and services that perceive users' emotions through detecting people's voices, facial emotions, and biometric data. In short, emotions which were used to be predicted only by humans are, now, predicted by digital equipment instead. Among many ICT researches, research on emotion recognition from face is fully expected as the most effective and natural human interface. This paper studies about sensitivity ICT and examines mechanism of facial expression recognition system as an example of sensitivity ICT.

• Science of Emotion and Sensibility
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• v.24 no.4
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• pp.91-106
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• 2021

Although personality and culture have been employed as independent predictors of emotion regulation, less is known about the interplay between them. Thus, the present study tests their interaction by focusing on the match between personality (public self-consciousness) and culture (valuing independence vs. interdependence) in modulating an emotion regulation strategy, namely, emotion suppression, on Facebook. Furthermore, relationship concern related to the expression of positive and negative emotions on Facebook is explored as a potential underlying mechanism. An online survey on Facebook users in the United States (n = 320) and South Korea (n = 336) was conducted through two professional survey companies. The results revealed that the positive association between public self-consciousness and emotion suppression was stronger among respondents who value interdependence (vs. independence), which led to a significant interaction between the two predictors. Furthermore, public self-consciousness was associated with emotion suppression through relationship concern for the expression of positive, but not negative, emotions. Furthermore, this mediated relationship was stronger among respondents who value interdependence (vs. independence). Lastly, the study discussed the importance of exploring the interplay between personality and culture and the implication of dialectic emotions.

• Journal of Distribution Science
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• v.10 no.2
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• pp.19-28
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• 2012

Rapidly growing sales amount and the number of discount stores caused many side effects and sensitive issues in Korea. Because these severe competition due to more expensive cost just like excessive increase in advertising and location selection, and these caused completely ruined small merchants as well as passed on to the consumer. This Study focused on competitiveness of discount store in Korea to the perspective of college students, as explored the relationships between marketing communication and store loyalty. And, examined for two moderating effect, 1) consumers' value separated by hedonic value and utilitarian value between marketing communication and store loyalty, and 2) consumers' value separated by hedonic value and utilitarian value between marketing communication and consumption emotion. Finally, this study examined for mediating effect of consumption emotion between marketing communication and store loyalty. In order to verify the relationship, moderating and mediating effects, data were collected from 130 college students in Whasung, Gyeonggi Province to test theoretical model and its hypotheses. Findings are as followed : First, analysis showed that factors such as advertisement(β =.221, p<.05), publicity(β =.513, p<.01), sales promotion(β =.234, p<.01), word of mouth(β =.627, p<.01) and physical environment(β =.339, p<.01) for marketing communication in the discount store have statistically significant positive effect on store loyalty. But the result of regression analysis for which factors are more impact in marketing communication between store loyalty showed that word of mouth(β =.53, p<.01) is only statistically significant. Second, publicity(β =-.895, p<.05), the sub-dimension of marketing communication shows only statistically significant negative moderating effect on store loyalty. But, the results of the moderating effect of value between marketing communication and consumption emotion verified that utilitarian value show statistically significant, specifically advertisement(β =.294, p<.01), physical environment(β =.418, p<.01), sales promotion(β =.245, p<.01), word of mouth(β =.414, p<.01) and publicity(β =1.137, p<.05), respectively. And hedonic value show statistically significant, specifically advertisement(β =.286, p<.01), physical environment (β =.418, p<.01), sales promotion(β =.236, p<.01) and word of mouth(β =.420, p<.01), respectively. But publicity(β =.145, p=.119) is not statistically significant. Finally, the results verified mediating effect for consumption emotion between all factors for marketing communication and store loyalty showed that factors such as advertisement, publicity, word of mouth and physical environment for marketing communication except sales promotion were statistically significant fully mediated in advertisement, and partially mediated in publicity, word of mouth and physical environment. This testified that the consumption emotion had the most important factor to enhance store loyalty to the perspective of College students. These results can provide important implications and invaluable tips for planning marketing strategies and gaining access to new potential customers. Implications and future research directions are also discussed.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.4
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• pp.717-724
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• 2020

Due to the important role played by emotion in human interaction, affective computing is dedicated in trying to understand and regulate emotion through human-aware artificial intelligence. By understanding, emotion mental diseases such as depression, autism, attention deficit hyperactivity disorder, and game addiction will be better managed as they are all associated with emotion. Various studies for emotion recognition have been conducted to solve these problems. In applying machine learning for the emotion recognition, the efforts to reduce the complexity of the algorithm and improve the accuracy are required. In this paper, we investigate emotion Electroencephalogram (EEG) feature reduction and classification using Stack AutoEncoder (SAE) and Long-Short-Term-Memory/Recurrent Neural Networks (LSTM/RNN) classification respectively. The proposed method reduced the complexity of the model and significantly enhance the performance of the classifiers.