• The Research Journal of the Costume Culture
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• v.17 no.3
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• pp.459-471
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• 2009

The purpose of the study is to examine the effect of VMD image appropriateness in apparel shopping contexts. Two competing models are utilized. The first model is developed from the emotion-cognition theory which explains that environmental cues(i.e., VMD image appropriateness) generate consumers' emotion, and in turn, consumers' behaviors. The second model is developed based on the cognitive theory of emotions and posits that environmental cues stimulates consumers' cognitive perceptions of retail environments, subsequently influencing consumers' emotional and behavioral response. A 2(VMD image appropriateness: high vs. low) between-subjects factorial design experiment was conducted. Female college students(n=592) participated in the experiment. Using structural equation modeling the study found that the emotion-cognition model better explains the effect of VMD image appropriateness on consumers' emotional, cognitive, and behavioral responses.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11b
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• pp.762-766
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• 2002

This paper describes the emotion recognition algorithm using HMM(Hidden Markov Model) method. The relation between the mechanic system and the human has just been unilateral so far. This is the why people don't want to get familiar with multi-service robots of today. If the function of the emotion recognition is granted to the robot system, the concept of the mechanic part will be changed a lot. Pitch and Energy extracted from the human speech are good and important factors to classify the each emotion (neutral, happy, sad and angry etc.), which are called prosodic features. HMM is the powerful and effective theory among several methods to construct the statistical model with characteristic vector which is made up with the mixture of prosodic features

• Journal of IKEEE
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• v.24 no.4
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• pp.998-1003
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• 2020

In this paper, an emotion training method using emotional adaptation is proposed to improve the performance of the existing emotion recognition system. For emotion adaptation, an emotion speech model was created from a speech model without emotion using a small number of training emotion voices and emotion adaptation methods. This method showed superior performance even when using a smaller number of emotional voices than the existing method. Since it is not easy to obtain enough emotional voices for training, it is very practical to use a small number of emotional voices in real situations. In the experimental results using a Korean database containing four emotions, the proposed method using emotional adaptation showed better performance than the existing method.

• 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.

• Culinary science and hospitality research
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• v.20 no.5
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• pp.111-118
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• 2014

This study sought to describe the relationships among physical environment, self-congruity, positive emotion, and revisit intentions in the coffeehouse setting. This study adopted second-order factor of physical environment in a structural equation model, imploying trend(fashion), cleanliness, reliability, spatial, convenience, and appropriacy as the second-order factors. The conceptual model in this study used responses from 338 college students who visited coffeehouse at least once in the past month. The proposed relationships were analyzed using SPSS 20.0 and AMOS 6.0. The results of data analysis indicated that the six secondorder factors of physical environment significantly affected coffeehouse visitor's self-congruity and positive emotion, and self-congruity as well as positive emotion significantly influenced revisit intentions. Further discussion and theoretical/practical implications of the findings along with directions for future studies are provided. In essence, the findings highlight significant role of coffeehouse's physical environment toward self-congruity and positive emotion in the formation of customer's revisit intentions in the coffeehouse context.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.05a
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• pp.199-202
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• 2001

We, Human beings, use both powers of reason and emotion simultaneously, which surely help us to obtain flexible adaptability against the dynamic environment. We assert that this principle can be applied into the general system. That is, it would be possible to improve the adaptability by covering a digital oriented information processing system with an analog oriented emotion layer. In this paper, we proposed a vertical slicing model with an emotion layer in it. And we showed that the emotion-based control allows us to improve the adaptability of a system at least under some conditions.

• Child Studies in Asia-Pacific Contexts
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• v.4 no.1
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• pp.1-12
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• 2014

Emotion is a central feature of social interactions. In this study, we examined age-related changes in emotion expressiveness and emotion knowledge and how young children's emotion expressiveness and knowledge were related. A total of 300 children attending a daycare center contributed data for the study. Observation and interview data relevant to measures of emotion expressiveness and knowledge were collected and analyzed. Both emotion knowledge and expressed positive affect increased with age. Older preschool children expressed positive affect more frequently than did younger preschoolers. Older preschool children also labeled, recognized, and provided plausible causes mores accurately than did younger preschool children. In addition, we tested whether children's errors on the free labeling component conform to the structural model previously suggested by Bullock and Russell (1986) and found that preschool children were using systematic strategies for labeling emotion states. Relations between emotion expressiveness and emotion knowledge generally were not significant, suggesting that emotional competence is only gradually constructed by the child over the preschool years.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.6
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• pp.35-46
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• 2011

In this paper, we proposed the method of emotion recognition using staged classification model and Fisher's linear discriminant. By organizing the staged classification model, the proposed method improves the classification rate on the Fisher's feature space with high complexity. The staged classification model is achieved by the successive combining of binary classification model which has simple structure and high performance. On each stage, it forms Fisher's linear discriminant according to the two groups which contain each emotion class, and generates the binary classification model by using Adaboost method on the Fisher's space. Whole learning process is repeatedly performed until all the separations of emotion classes are finished. In experimental results, the proposed method provides about 72% classification rate on 8 classes of emotion and about 93% classification rate on specific 3 classes of emotion.

• Asia pacific journal of information systems
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• v.27 no.1
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• pp.38-53
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• 2017

As sensor technologies and image processing technologies make collecting information on users' behavior easy, many researchers have examined automatic emotion recognition based on facial expressions, body expressions, and tone of voice, among others. Specifically, many studies have used normal cameras in the multimodal case using facial and body expressions. Thus, previous studies used a limited number of information because normal cameras generally produce only two-dimensional images. In the present research, we propose an artificial neural network-based model using a high-definition webcam and Kinect to recognize users' emotions from facial and bodily expressions when watching a movie trailer. We validate the proposed model in a naturally occurring field environment rather than in an artificially controlled laboratory environment. The result of this research will be helpful in the wide use of emotion recognition models in advertisements, exhibitions, and interactive shows.

• Korean Journal of Human Ecology
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• v.18 no.6
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• pp.1209-1219
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• 2009

The purpose of this study examined the path model of maternal emotional expression, temperament and self-esteem on emotion regulation among children. The subjects were 487 5th and 6th graders. Data was gathered through questionnaires reported by children and their mothers and analyzed by structural equation modeling. The results showed that children's 'activity level' temperament and maternal negative emotional expression directly affected maladaptive emotion regulation. Children's 'emotionality' temperament and maternal positive emotional expression directly affected adaptive emotion regulation. Children's 'approach-flexibility' temperament and self-esteem directly affected both maladaptive and adaptive emotion regulation. Maternal emotional expression and children's self-esteem mediated between children's temperament and emotion regulation. Additionally, the most important variable predicting children's maladaptive emotion regulation was the children's 'activity level' temperament, and the most important variable for adaptive emotion regulation was the children's 'emotionality' temperament.