• Journal of the Korean Society of Clothing and Textiles
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• v.31 no.9_10
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• pp.1373-1383
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• 2007

The purpose of this study is to find out the dimensions of kidult fashion emotion and identify the influence of socio-psychological characteristics(nostalgic orientation, change inclination, and self-esteem) on kidult fashion emotion. 'Kidult', composite of kid and adult is indicating a group of people who feel nostalgic for and feel attachment to the products that they have been used in their childhood. A questionnaire was prepared in the survey and a total of 474 women in their twenties and thirties who had purchased the kidult fashion products were selected. The research findings are as follows: 1. Kidult fashion emotion can be classified as 5 factors: pursuits of fashion emotion, seeking girlish image emotion, preference for character emotion, seeking fun emotion, and past oriented emotion. 2. Socio-psychological variable that affected kidult fashion emotion is turned out change inclination. 3. The higher the seeking girlish image and pursuit of fashion emotion tendencies, the more they purchase the kidult fashion products. Based on these results, kidult fashion emotions are not the attachment to the past but positive expression of self and individuality.

• Science of Emotion and Sensibility
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• v.13 no.1
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• pp.111-120
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• 2010

Initial stage of emotion has a great influence on building up product image and impression. Because of its influencing effects, measuring initial stage of emotion has potential to be a key factor for designers and marketers to achieve a distinct product concept. While many researchers have studied this topic with the emotion measurement method in product use stage, there are very few cases specialized in the initial stage of emotion. Even though present emotion measurement methods have difficulties to derive accurate user's initial stage of emotion, most case of initial emotion study applies these defective methods. The purpose of this study is to develop initial stage of emotion measurement method and apply this method to real product context. In the design of the initial stage of emotion measurement method, noticeable characteristics of initial stage of emotion were explored and initial emotion measurement framework was presented. Based on this framework, Initial Emotion Measurement System(IEMS) was suggested. This method collects user's eye movement, behavior and verbal data accurately and objectively.

• 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.

• Journal of the Korean Society of Clothing and Textiles
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• v.26 no.5
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• pp.663-674
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• 2002

The objectives of this study were 1) to ascertain whether there was a difference in product performance (expressive or instrumental), which consumer recognized after using, related to consumer involvement toward clothing, 2) to clarify the effect of product performance on consumption emotion(positive or negative), 3) to investigate the effect of consumption emotion on satisfaction, and 4) to find out whether product performance had a direct effect on satisfaction toward product. The study was conducted in three steps. Through the two steps, measurement instruments were developed. At the last step, judgement sampling method were utilized to collect the data and subjects were 614 university students. Confirmatory factor analysis and structural equation model analysis were used to analyze the data. The results were as follows: 1) Consumer involvement had an effect on product performances but it was related to the expressive product performance more than to the instrumental product performance. 2) Product performance had positive influence on positive consumption emotion, while it had negative influence on negative consumption emotion. The results revealed that there were significant relationships between product performance and consumption emotion. 3) Positive consumption emotion had a positive effect on consumer satisfaction, on the other hand negative consumption emotion had a negative effect on consumer satisfaction. 4) Although the direct effects of product performances on satisfaction were larger than the indirect effects, product performance was greatly influential in consumption emotion and consumption emotion was strongly related to consumer satisfaction. Therefore, consumption emotion is an important determinant variable in the process of consumer satisfaction.

• Journal of information and communication convergence engineering
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• v.20 no.3
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• pp.174-180
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• 2022

Emotion recognition is an essential component of complete interaction between human and machine. The issues related to emotion recognition are a result of the different types of emotions expressed in several forms such as visual, sound, and physiological signal. Recent advancements in the field show that combined modalities, such as visual, voice and electroencephalography signals, lead to better result compared to the use of single modalities separately. Previous studies have explored the use of multiple modalities for accurate predictions of emotion; however the number of studies regarding real-time implementation is limited because of the difficulty in simultaneously implementing multiple modalities of emotion recognition. In this study, we proposed an emotion recognition system for real-time emotion recognition implementation. Our model was built with a multithreading block that enables the implementation of each modality using separate threads for continuous synchronization. First, we separately achieved emotion recognition for each modality before enabling the use of the multithreaded system. To verify the correctness of the results, we compared the performance accuracy of unimodal and multimodal emotion recognitions in real-time. The experimental results showed real-time user emotion recognition of the proposed model. In addition, the effectiveness of the multimodalities for emotion recognition was observed. Our multimodal model was able to obtain an accuracy of 80.1% as compared to the unimodality, which obtained accuracies of 70.9, 54.3, and 63.1%.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2012.05a
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• pp.1-2
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• 2012

• International Journal of Computer Science & Network Security
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• v.23 no.9
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• pp.47-54
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• 2023

For Bengali music emotion classification, deep learning models, particularly CNN and RNN are frequently used. But previous researches had the flaws of low accuracy and overfitting problem. In this research, attention-based Conv1D and BiGRU model is designed for music emotion classification and comparative experimentation shows that the proposed model is classifying emotions more accurate. We have proposed a Conv1D and Bi-GRU with the attention-based model for emotion classification of our Bengali music dataset. The model integrates attention-based. Wav preprocessing makes use of MFCCs. To reduce the dimensionality of the feature space, contextual features were extracted from two Conv1D layers. In order to solve the overfitting problems, dropouts are utilized. Two bidirectional GRUs networks are used to update previous and future emotion representation of the output from the Conv1D layers. Two BiGRU layers are conntected to an attention mechanism to give various MFCC feature vectors more attention. Moreover, the attention mechanism has increased the accuracy of the proposed classification model. The vector is finally classified into four emotion classes: Angry, Happy, Relax, Sad; using a dense, fully connected layer with softmax activation. The proposed Conv1D+BiGRU+Attention model is efficient at classifying emotions in the Bengali music dataset than baseline methods. For our Bengali music dataset, the performance of our proposed model is 95%.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.152-157
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• 2008

The human uses the optic plentifully that an emotion the human knowledge. by the light it perceives the object and we live middle of color together. The color is close relation in our life. against a color from in many the optic information it is sensitive and it accepts. Therefore if expresses a emotion with color, human knowledge there is a probably of accepting intuition. The purpose of this dissertation to The emotion expression which uses a hue and the hue which leads the relationship research of emotion. In emotional circle of Plutchik, It selects the emotion where becomes the basic and the hue which similar has an impression and feature from the Harris of Moses Harris it searches emotion to use a hue circle with the method which it makes the emotion it expresses. Examines satisfaction of hue and emotion for emotion expression. The magnetic pole of emotion continuously comes in, There must be it will be able to confirm change of many emotion as a real-time. The shooting game the magnetic pole of multi emotion continuously comes in, Because it will be able to confirm the change of emotion as a real-time, suitable the applies for the research of emotion expression Consequently, The application it tried with character hue of shooting game.

• The Research Journal of the Costume Culture
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• v.22 no.1
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• pp.73-85
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• 2014

The purpose of the study was to investigate whether customer perception on internet fashion shopping mall characteristics influences positive emotion on internet shopping and relationship formation. For data collection, a questionnaire was administrated from February 20th to March 3th in 2012 to 362 adults who have purchased the products from internet fashion shopping mall. The analysis explores the effect of internet shopping mall characteristics on positive shopping emotion and relationship quality. It also tests the mediation effect of positive shopping emotion for the influence of internet fashion shopping mall characteristics on relationship quality. The results are as follows. First, the perceived internet fashion shopping mall characteristics had positive effects on relationship quality. Second, the perceived internet fashion shopping mall characteristics had positively effects on positive shopping emotion. Third, the effect of positive shopping emotion had positive effects on relationship quality. Fourth, the effect of perceived internet fashion shopping mall characteristics on relationship quality, mediated by positive shopping emotion, was shown to be none.

• Journal of the Korea Computer Graphics Society
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• v.24 no.4
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• pp.1-9
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• 2018

We propose an emotional training framework that can determine the initial symptom of schizophrenia by using emotional analysis method through facial expression change. We use Emotion API in Microsoft to obtain facial expressions and emotion values at the present time. We analyzed these values and recognized subtle facial expressions that change with time. The emotion states were classified according to the peak analysis-based variance method in order to measure the emotions appearing in facial expressions according to time. The proposed method analyzes the lack of emotional recognition and expressive ability by using characteristics that are different from the emotional state changes classified according to the six basic emotions proposed by Ekman. As a result, the analyzed values are integrated into the image color transfer framework so that users can easily recognize and train their own emotional changes.