• Korean Journal of Human Ecology
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• v.24 no.5
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• pp.645-661
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• 2015

The purpose of this study was to investigate the effects of socio-demographic variables, adult attachment and emotion regulation style on psychological well-being of university students. We conducted a survey on 318 university students in Cheongju-si and Hongseong gun. T-test, Pearson' productive correlation, hierarchical regression analysis were used. The results were as follows: First, there was a significant difference in emotion regulation style according to university student's sex. In other words, females used more support-seeking style than males did. Second, male university students' psychological well-being was high at more active style, less anxiety attachment and avoidant/distractive style, older students, less avoidance attachment, and higher economic status. Third, female university students' psychological well-being was high at less avoidant/distractive style and more active style, older students, less anxiety attachment, and more support-seeking style. In conclusion, emotion regulation style was the strongest factor to increase university student's psychological well-being among other variables. The implications and limitations of this study were discussed.

• Science of Emotion and Sensibility
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• v.12 no.2
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• pp.215-224
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• 2009

This research extracted emotional words for measuring user's emotions expressed while using a cellular phone and a web. And then the emotional words were compared to find out whether the difference in emotional words by the type of products. The results of this study suggest that the hardware-oriented products used for specific purpose such as cellular phone extracted a lot of emotional words related to 'Satisfaction in Usability' and 'Pleasure'. 'Satisfaction in Usability' are conceived satisfying in usability or practicality of product. 'Pleasure' are pleasant emotions expressed while using a product. However the emotional words related to 'Aesthetics' and 'Novelty' were omitted. 'Aesthetics' are expressed by product's appearance and by various visual information while using a product. 'Novelty' are expressed by something that is novel and new that has never been experienced. On the other hand the software-oriented products used rather to find something better and new information than to perform specific tasks such as web extracted a lot of emotional words related to 'Novelty'. Therefore, the results of this research have found evidence that it is desirable to make a set of subjective evaluation scale by the type of products. When making the subjective evaluation scale, it is important to use appropriate emotional words for the purpose of use and the characteristics of those products.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2000.04a
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• pp.126-132
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• 2000

This paper presents a facial expression recognition based on Gabor wavelets that uses a fuzzy C-means(FCM) clustering algorithm and neural network. Features of facial expressions are extracted to two steps. In the first step, Gabor wavelet representation can provide edges extraction of major face components using the average value of the image's 2-D Gabor wavelet coefficient histogram. In the next step, we extract sparse features of facial expressions from the extracted edge information using FCM clustering algorithm. The result of facial expression recognition is compared with dimensional values of internal stated derived from semantic ratings of words related to emotion. The dimensional model can recognize not only six facial expressions related to Ekman's basic emotions, but also expressions of various internal states.

• Science of Emotion and Sensibility
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• v.15 no.1
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• pp.97-104
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• 2012

Recently, a big text data has been produced by users, an opinion mining to analyze information and opinion about users is becoming a hot issue. Of the opinion mining, especially a sentiment analysis is a study for analysing emotions such as a positive, negative, happiness, sadness, and so on analysing personal opinions or emotions for commercial products, social issues and opinions of politician. To analyze the sentiment analysis, previous studies used a mapping method setting up a distribution of emotions using two dimensions composed of a valence and arousal. But previous studies set up a distribution of emotions arbitrarily. In order to solve the problem, we composed a distribution of 12 emotions through carrying out a survey using Korean emotion words list. Also, certain emotional states on two dimension overlapping multiple emotions, we proposed a selection method with Roulette wheel method using a selection probability. The proposed method shows to classify a text into emotion extracting emotion terms from a text.

• Journal of the Korean Society of Food Culture
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• v.38 no.1
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• pp.48-60
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• 2023

The image and emotions associated with Korean food were investigated in 24 food workers (12 Koreans and 12 foreigners) living in Korea. There are a total of 22 terms for the image of Korean food of Koreans and foreigners, including 7 common words, and a total of 33 terms for emotion, including 10 common words. Differences in the images and emotions associated with the perception of Korean food according to the characteristics of the country and region and Korean food experience were established in foreign food workers. In the images of Korean food, Koreans mentioned 'jeong, sharing, balanced, Korean table setting, seasonal (seasonality), yearning, trust', whereas foreigners mentioned 'red, spicy, distinctive flavor, repulsion, sweet, non-salty, tradition and history, and unfamiliarity'. In Korean food emotions, Koreans were "relaxing, friendly, maternal, hospitable, nostalgic, exotic, clean, trust, delicious, touching, and free", whereas foreigners were "happy, appealing, enthusiastic, excited, uncomfortable, worried, adventurous, nervous, joyful, fusion, food-cultural, and amazing".

• Archives of design research
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• v.17 no.2
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• pp.199-208
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• 2004

In cyberspace based on internet, users constitute communities and interact one another. Avatar means not only the other self but also the 'another being' that describes oneself in the cyberspace. If user's avatar shows expressive faces and behaves according to his thinking and emotion, he will have a feel of reality much more in the cyberspace. If avatar's countenances can be animated by just typing characters in avatar-based chat communication, the user is able to express his emotions more effectively. In this study, emotion-expressing vocabulary is analyzed and classified. Emotion-expressing vocabulary is essential to develop self-reactive avatar system in which avatar's countenances are automatically converted according to the words typed by users at chat. The results are as follows; First, emotion-expressing vocabulary selected out of Korean adjectives and intransitive verbs is made up of 209 words and is classified into 25 groups. Second, there are only 2 groups out of the 25 groups for positive expressions and others are for negative expressions. Therefore, negative expressions are more abundant than positive expressions in Korean vocabulary. Third, avatar's countenances are modelled according to the 25 groups by using the Quantification Method 3. The result shows that the emotion-expressing vocabulary has dose relations with avatar's countenances and is useful to communicate users' emotions. However, this study has some limits, in that Korean linguistical structure - the whole meaning of context - cannot be interpreted quantitatively.

• Journal of Internet Computing and Services
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• v.9 no.5
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• pp.99-108
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• 2008

This paper proposes an image retrieval system which integrates metadata, contents, and emotions in textile images. First, the proposed system searches images using metadata. Among searched images, the system retrieves similar images based on color histogram, color sketch, and emotion histogram. To extract emotion features, this paper uses emotion colors which was proposed on 160 emotion words by H. Nagumo. To enhance the user's convenience, the proposed textile image retrieval system provides additional functions as like enlarging an image, viewing color histogram, viewing color sketch, and viewing repeated patterns.

• Science of Emotion and Sensibility
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• v.21 no.2
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• pp.61-72
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• 2018

Different types of traditional Korean clothes (Hanbok) are appearing in the market with the increasing interest of culture consumers. In order to turn traditional Korean clothes into everyday clothes that adequately reflect various demands of culture consumers, it is important to satisfy both functional and emotional aspects of clothing. However, there is lack of existing studies on emotions of culture consumers while wearing traditional Korean clothes. In this study, 28 emotional words regarding traditional Korean clothes were extracted by applying the Delphi method and conformity rating survey to 182 emotional words reported in existing studies and references from areas such as psychology, linguistics, and sensibility engineering. The 28 selected emotional words can be used to express emotions felt by culture consumers about traditional Korean clothes. Also, words were grouped based on the correlation according to factor analysis. Based on common characteristics, the emotional words were classified into 6 categories of 'pleasure,' 'aesthetic sense,' 'harmony,' 'novelty,' 'likability,' and 'stability.' These 6 emotional categories were concluded to represent emotions of consumers about traditional Korean clothes. The 28 emotional words and 6 representative emotions noted in this study can be used as basic data for measuring emotions of culture consumers of traditional Korean clothes. A future study task is to design a detailed assessment scale to measure emotions of culture consumers about traditional Korean clothes using representative emotions.

• Science of Emotion and Sensibility
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• v.24 no.2
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• pp.75-80
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• 2021

Do happy applicants achieve more? Although it is well established that happiness predicts desirable work-related outcomes, previous findings were primarily obtained in social settings. In this study, we extended the scope of the "happiness premium" effect to the artificial intelligence (AI) context. Specifically, we examined whether an applicant's happiness signal captured using an AI system effectively predicts his/her objective performance. Data from 3,609 job applicants showed that verbally expressed happiness (frequency of positive words) during an AI interview predicts cognitive task scores, and this tendency was more pronounced among women than men. However, facially expressed happiness (frequency of smiling) recorded using AI could not predict the performance. Thus, when AI is involved in a hiring process, verbal rather than the facial cues of happiness provide a more valid marker for applicants' hiring chances.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.11
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• pp.4819-4825
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• 2011

This study tried to find out whether character patterns of elderly people are related to stress resistance using brain waves, personal physiological index of cranial nerves. The data were gathered by 1,108 seniors(age 65 and over) who were requested to check brain waves from September, 2007 to December, 2010 in Korean Institute for Research of Psychiatry. 552 of the subject showed the propensity to positive behavior, 556 of them showed the propensity to negative behavior. 735 of the subject showed the propensity to cheerful emotion, 373 of them showed the propensity to depressed emotion. As a result the propensity of emotion was significantly related to the stress resistance, but not the propensity of behavior. In other words, the propensity to cheerful emotion showed higher average stress resistance index than the propensity to depressed emotion. So the person who has the propensity to cheerful emotion can cope with stress better. This study shows the propensity to emotion is related to stress resistance. The influence of the propensity to emotion and how it works should to be studied.