• Science of Emotion and Sensibility
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• v.20 no.4
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• pp.79-88
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• 2017

As the age in which the importance of sensitivity has increased, education for the future generation regarding emotion engineering, affective recognition and cognitive science have taken center stage. We measure human's emotion quantitatively, analyze evaluation and apply them to various services in life, which are based on human technology. Therefore, we need the education which is related to emotion science to cultivate talented people. The goal of this paper is to suggest the possibility of emotion science education and effective methods through development of the STEAM (Science, Technology, Engineering, Arts, Mathematics) program which can teach emotion science to early elementary school students by applying it to pilot classes. For this study, first, we build a program, 'The mind made by figure' for student of early elementary school. The method of STEAM was used in this program, because it is an effective system to educate the emotion science. We recognize the needs and value of this program development through theory and benchmarking of STEAM related to emotion science. And then the contents of class, activities, course book and kit are designed with elementary school textbook of pertinent grade. Secondly, we analyze the result which is applied in two pilot classes of second grade by satisfaction survey and teacher interview. As a result, the average of satisfaction level was very high (4.40/5), Class participation was especially high. Third, we discuss the ability, value and limits of this program based on the result of analysis. The outcome of this research shows that students of early elementary school who have difficulty in understanding science can approach the education program related to emotion science with ease and interest. We hope this education will help students understand emotion science effectively, and to train people to lead the emotion centered era.

• Journal of Korean Academy of Nursing
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• v.37 no.6
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• pp.855-862
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• 2007

Purpose: The purpose of this study was to identify the factors influencing fatigue in patients with chronic obstructive pulmonary disease. Methods: A descriptive correlational study design was used. A convenience sample of 125 subjects was recruited from the outpatient respiratory clinic at a large university hospital. Data was collected from June to October, 2005 using structured questionnaires, an oxygen saturation test, a 6-minute walking test, and a pulmonary function test. Results: Subjects had a slightly low degree of fatigue. The fatigue showed a significant correlation with emotion(r=.589, p= .000), dyspnea(r=.304, p= .001), self-efficacy(r=-.278, p= .002), and symptom experience(r=.238, p= .008). Emotion(34.7%) and dyspnea(5.8%) were significant predictors to explain fatigue. Conclusion: This study provides comprehensive understanding of the influencing factors on fatigue in patients with chronic obstructive pulmonary disease. Nursing interventions to decrease negative emotion and dyspnea for management of fatigue is suggested.

• Journal of the Korean Society of Clothing and Textiles
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• v.45 no.6
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• pp.949-964
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• 2021

Accumulation of high-quality data is crucial for AI learning. The goal of using AI in fashion service is to propose of a creative, personalized solution that is close to the know-how of a human operator. These customized solutions require an understanding of fashion products and emotions. Therefore, it is necessary to accumulate data on the attributes of fashion products and fashion emotion. The first step for accumulating fashion data is to standardize the attribute with coherent system. The purpose of this study is to propose a fashion emotional classification system. For this, images of fashion products were collected, and metadata was obtained by allowing consumers to describe their emotions about fashion images freely. An emotional classification system with a hierarchical structure, was then constructed by performing frequency and CONCOR analyses on metadata. A final classification system was proposed by supplementing attribute values with reference to findings from previous studies and SNS data.

• Korean Journal of Child Studies
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• v.29 no.1
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• pp.257-273
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• 2008

This study examined the development of children's theory of mind by types of false-belief tasks and various mental states. Seventy six 3-, 4-, 5- and 6-year olds were asked to infer others' minds or choose other's behaviors. Ten tasks, including two picture book tasks, were used to tap the children's understanding of various mental states. Results showed that children did well in their understanding of diverse perception and desire, but they did poorly in emotional inference based on false-belief, and second order false-belief. Children performed better in picture book tasks than in classical tasks for the understanding of false-belief and false-belief based emotion.

• Science of Emotion and Sensibility
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• v.15 no.4
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• pp.503-516
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• 2012

According to the researches of robot and software agent until now, computational emotion model is dependent on system, so it is hard task that emotion models is separated from existing systems and then recycled into new systems. Therefore, I introduce the Engine of computational Emotion model (shall hereafter appear as EE) to integrate with any robots or agents. This is the engine, ie a software for independent form from inputs and outputs, so the EE is Emotion Generation to control only generation and processing of emotions without both phases of Inputs(Perception) and Outputs(Expression). The EE can be interfaced with any inputs and outputs, and produce emotions from not only emotion itself but also personality and emotions of person. In addition, the EE can be existed in any robot or agent by a kind of software library, or be used as a separate system to communicate. In EE, emotions is the Primary Emotions, ie Joy, Surprise, Disgust, Fear, Sadness, and Anger. It is vector that consist of string and coefficient about emotion, and EE receives this vectors from input interface and then sends its to output interface. In EE, each emotions are connected to lists of emotional experiences, and the lists consisted of string and coefficient of each emotional experiences are used to generate and process emotional states. The emotional experiences are consisted of emotion vocabulary understanding various emotional experiences of human. This study EE is available to use to make interaction products to response the appropriate reaction of human emotions. The significance of the study is on development of a system to induce that person feel that product has your sympathy. Therefore, the EE can help give an efficient service of emotional sympathy to products of HRI, HCI area.

• Science of Emotion and Sensibility
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• v.15 no.1
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• pp.105-120
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• 2012

This study aimed to develop a Korean emotion vocabulary list that functions as an important tool in understanding human feelings. In doing so, the focus was on the careful extraction of most widely used feeling words, as well as categorization into groups of emotion(s) in relation to its meaning when used in real life. A total of 12 professionals (including Korean major graduate students) partook in the study. Using the Korean 'word frequency list' developed by Yonsei University and through various sorting processes, the study condensed the original 64,666 emotion words into a finalized 504 words. In the next step, a total of 80 social work students evaluated and classified each word for its meaning and into any of the following categories that seem most appropriate for inclusion: 'happiness', 'sadness', 'fear', 'anger', 'disgust', 'surprise', 'interest', 'boredom', 'pain', 'neutral', and 'other'. Findings showed that, of the 504 feeling words, 426 words expressed a single emotion, whereas 72 words reflected two emotions (i.e., same word indicating two distinct emotions), and 6 words showing three emotions. Of the 426 words that represent a single emotion, 'sadness' was predominant, followed by 'anger' and 'happiness'. Amongst 72 words that showed two emotions were mostly a combination of 'anger' and 'disgust', followed by 'sadness' and 'fear', and 'happiness' and 'interest'. The significance of the study is on the development of a most adaptive list of Korean feeling words that can be meticulously combined with other emotion signals such as facial expression in optimizing emotion recognition research, particularly in the Human-Computer Interface (HCI) area. The identification of feeling words that connote more than one emotion is also noteworthy.

• Journal of Sasang Constitutional Medicine
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• v.16 no.2
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• pp.44-51
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• 2004

1. Objectives This paper is written for clear understanding on the concepts of 'Deep adherence of the Nature' and 'Sudden explosion of the Emotion' and for intensive comprehension of Mechanism of 'The Exterior Disease' and 'The Interior Disease' by The Nature and the Emotion. 2. Methods The study mainly based on "The exterior disease injured by the Nature, the interior disease injured by the Emotion" and deals with 'Seongmyungron, Sadanron, Hwarkchungron and Jangburon'. 3. Results and conclusions The conclusions as follows (1) Exterior Disease in each constitution breaks out by deep adherence of the Nature. Interior Disease brings out with sudden explosion of the Emotion. (2) 'Deep adherence of the Nature' is the state that the Ear, Eye, Nose, Mouth taking care of environmental frames can't work enoughly because of wrong minds on the Jaw, Breast, Umbilicus, Abdment. 'Sudden explosion of the Emotion' is the state that the Lung, Spleen, Liver, Kidney doing human affairs doesn't do appropriately for each constitution due to negative minds on the Head, Shoulder, Waist, Hip. (3) The result that the Ear, Eye, Nose, Mouth doesn't extract the clear energy from 'Jin, Go, You, Yaek sea' so they are lack of 'Shin, Qi, Hyul, Jeong' causes exterior disease in each constitution. (4) In each constitution, Interior disease results from that the Lung, Spleen, Liver, Kidney fails to bring on the clear juice from 'Lee, Mak, Hyul, Jeong sea', so shortage of 'Jin, go, You, Yaek' results in it.

• 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.

• Journal of Distribution Science
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• v.17 no.1
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• pp.95-103
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• 2019

Purpose - Recently, many theoretical researches suggested that arts-based marketing strategies provide many benefits for marketers to differentiate their brand or product from others. However, there has been little research focusing on consumers' response types from artwork (artifact-emotion appraisal; A-emotion vs. represented world-emotion appraisal; R-emotion). In order to deepen our understanding of arts-based marketing strategies, we addressed a research question related to how artwork-provoked consumers' emotional response can impact the perceived evaluation of art infused products. Research design, data, and methodology - To answer the research question, we conducted a pretest and one experimental study. The experimental study was 2(art-provoked response type: A-emotion vs. R-emotion) by 2(emotional valence: positive vs. negative) by 2(produce type: hedonic vs. utilitarian) mixed design. The art-provoked response type and emotional valence were between-subject design and product type was within subject design. For the experimental study, 108 undergraduate students and graduate students were randomly assigned to one of 4 conditions (A-emotion-positive, A-emotion-negative, R-emotion-positive, R-emotion-negative). Participants reported their evaluation of art-infused product and other items for a manipulation check. Results - The major results from the experimental study are as follow. First, participant's art-provoked response type influenced evaluation of art infused products differently. More specifically, the effect of emotional valence of artwork on product evaluation was not significant in A-emotion. However, in R-emotion, relative to the product with artwork provoked negative emotional valence, the product with artwork provoked positive emotional valence elicited significantly higher product evaluation. Second, product type also affected the art infusion effect significantly. Particularly, the differential effect of participant's art-provoked response type on product evaluation revealed when it is for a utilitarian product, but not for a hedonic product. Conclusions - Theoretically, the findings of this study expand academic research on art infusion. And the findings also can be extrapolated to generate lots of implication for marketers. In sum, when they plan art marketing strategies to build the favorable relationship with their customers, they need to consider customers' response type of an infused art and product type.

• Journal of Korea Society of Digital Industry and Information Management
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• v.13 no.2
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• pp.87-98
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• 2017

The advancements in scientific technology and information network in the 21st century allow us to easily acquire a desired knowledge. In the midst of today's informatization, globalization, and cultural diversification, adolescents experience emotional confusion while accommodating diverse cultures and information. This study aimed at examining three aspects of character suggested by the Ministry of Education, which are ethics, sociality, and emotion, and the actual sub-factors required for character education. To that end, a survey was conducted with adolescents who were at a character-building age, and social network analysis (SNA) was performed to determine the effect of character education on the sub-factors. The statistics program SPSS was used to investigate the general traits of the subjects and the validity of the research variables. The 2-mode data that were finally selected were converted to 2-mode data using NetMinder 4, which is a network analysis tool. Furthermore, a data network was established based on a quasi-network that represents the relationships between ethics, sociality, and emotion. The results of this study showed that the subjects considered honesty and justice to be the sub-domains of the ethics domain. In addition, they identified sympathy, communication, consideration for others, and cooperation as the sub-domains of the sociality domain. Finally, they believed that self-understanding and self-control were the sub-domains of the emotion domain.