• The Journal of Korea Robotics Society
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• v.2 no.2
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• pp.119-128
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• 2007

Emotion interaction between human and robot is an important element for natural interaction especially for service robot. We propose a hybrid emotion generation architecture and detailed design of reactive process in the architecture based on insight about human emotion system. Reactive emotion generation is to increase task performance and believability of the service robot. Experiment result shows that it seems possible for the reactive process to function for those purposes, and reciprocal interaction between different layers is important for proper functioning of robot's emotion generation system.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.1
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• pp.33-39
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• 2010

The interaction of emotion is an important factor in Human-Robot Interaction(HRI). This requires a contextual appraisal of emotion extracting the emotional information according to the events happened from past to present. In this paper an emotion appraisal system based on the cognitive context is presented. Firstly, a conventional emotion appraisal model is simplified to model a contextual emotion appraisal which defines the types of emotion appraisal, the target of the emotion induced from analyzing emotional verbs, and the transition of emotions in the context. We employ a language based cognitive system and its sentential memory and object descriptor to define the type and target of emotion and to evaluate the emotion varying with the process of time with the a priori emotional evaluation of targets. In a experimentation, we simulate the proposed emotion appraisal system with a scenario and show the feasibility of the system to HRI.

• Journal of Fashion Business
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• v.7 no.1
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• pp.14-26
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• 2003

This research aimed 1) to analyze the relationship between consumer's emotional needs and elements of textile design in the 1st survey 2) to investigate textile design process presently conducted in the industry in the 2nd survey, and 3) to suggest a desirable direction to improve the textile design process based on a comparison of the results obtained from the two surveys. A description system and an emotion model on textile design were redeveloped as research devices in this study. In the 1st survey, total 600 respondents were sampled and asked to report their emotional response on 50 representative types of textile design, on a emotion measurement scale. The data set obtained from the 1st survey were statistically analyzed. In the 2nd survey, a depth interview was applied to qualitatively analyze the textile design process presently conducted in the industry. The results from the two surveys were compared.

• Journal of the Korea Society of Computer and Information
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• v.28 no.12
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• pp.57-66
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• 2023

In this study, we propose a novel research framework for the recommendation system that can estimate the user's emotional state and reflect it in the recommendation process by applying deep learning techniques and emotion AI (artificial intelligence). To this end, we build an emotion classification model that classifies each of the seven emotions of angry, disgust, fear, happy, sad, surprise, and neutral, respectively, and propose a model that can reflect this result in the recommendation process. However, in the general emotion classification data, the difference in distribution ratio between each label is large, so it may be difficult to expect generalized classification results. In this study, since the number of emotion data such as disgust in emotion image data is often insufficient, correction is made through augmentation. Lastly, we propose a method to reflect the emotion prediction model based on data through image augmentation in the recommendation systems.

• Science of Emotion and Sensibility
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• v.6 no.2
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• pp.1-7
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• 2003

The objectives of this study is to develop an adaptable digital wall model whose color can be changed dynamically according to the identified emotional state of a user. This study addresses how to capture a specific user's emotion through the web and use it for modifying VR model mainly for color adaptation. This adaptation process of a VR model consists of three phases: 1) identification of the user's emotional state projected onto the list of emotional keywords 2) translation of those captured emotional keywords into a pertinent set of color coordinations, and finally, 3) automated color adaptation process for the given model. This process derives an on-line viewer's emotional state, which can be utilized to find a new color scheme reflecting the identified emotion.

• Journal of The Korean Association For Science Education
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• v.25 no.4
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• pp.503-513
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• 2005

The purpose of this study was to analyze the generating processes of scientific emotion, that appears during the generation of biological hypotheses. To perform the study, a tentative model was set up through pilot test, a think-aloud training procedure was planned and a standardized interview instrument was developed before getting protocols. In this study, 8 college students were selected to bring out protocol through the method of think-aloud, retrospective debriefing, focused interview and observing. As the result of analysis of the collected protocol through coding scheme, 4 types of process for scientific emotion-generating were sorted out. First type was a basic process which was a feeling process in prior to recognition. Second type was a retrospective process that explains the process of retrospect for emotional memory based on the past. Third type was a cognitive process and it explains emotion that occurs during thinking process to achieve cognitive goal. Fourth type was an attribution process and it explains that emotion is generated in the process of attribution for cognitive goal's achievement. These types of process of scientific emotion-generating can contribute the basis for developing cognitive model of EBL (Emotional Brain-based Learning) strategy.

• The Korean Journal of Franchise Management
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• v.12 no.1
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• pp.45-55
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• 2021

Purpose: How to build the positive emotion of customer is very important, because it affects the positive attitude. Brand evidence has a significant impact on consumer behavior in terms of reinforcing consumers' perception of food service companies and differentiating them from competing brands. Thus, this study examines the effect of brand evidence on emotion (positive emotion and negative emotion), and attitude in restaurant industry. Research design, data, and methodology: This study examines the structural relationship among brand evidence, emotion, and attitude. Brand evidence divide into three sub-dimensions such as physical evidence, core service, and employee service. In order to test the purposes of this study, research model and hypotheses were developed. The questionnaire items were modified and used according to the content of this study based on previous studies. All constructs were measured by multiple items tested and developed in the previous research. The data were collected from 439 restaurant users from Seoul area were analyzed using SPSS 22.0 and SmartPLS 3.0 program. A total of 460 questionnaires were distributed and a survey was conducted for 4 weeks, and a total of 439 were used for analysis, excluding non-response data and 21 unusable response data among the collected questionnaires. Frequency analysis was conducted to identify the general characteristics of the survey subjects. To measure the reliability and validity of the measurement tools, confirmatory factor analysis was conducted. Structural model analysis was conducted to verify the research model. Result: The findings demonstrate that physical evidence, core service, employee service had positive effects on positive emotion. And core service and employee service had negative effects on negative emotion while physical evidence did not have. Also, positive emotion had positive effect on attitude and negative emotion had negative effect on attitude. Conclusions: The findings of this study provide guidelines on how to enhance competitiveness in restaurant industry through understanding brand evidence's effects on raising perceived consumer's emotion and attitude. Therefore, food service companies should establish a marketing strategy that can stimulate positive emotions through brand evidence, which is all factors related to service brands that influence consumers' evaluation of service products and purchase decision-making process.

• Journal of the Korean Society of Clothing and Textiles
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• v.34 no.12
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• pp.1992-2005
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• 2010

Emotion directly affects consumer buying behavior. This study examines Chinese consumers' emotion elicitation process toward a U.S. apparel brand in the Chinese market. Employing a cognitive appraisal theory, this study proposed and tested a conceptual model incorporating three factors of consumer global orientation as antecedents of consumer emotion and purchase intention as a consequence of emotion. Among the ten proposed hypotheses, eight were supported. Of the three antecedents of consumer emotion, exposure to global mass media and cultural openness positively increased Chinese consumers' appraisals of a U.S. apparel brand. Unlike these two antecedents, the effects of exposure to mass migration on consumer appraisals were found to be non significant. The relationships between appraisal dimensions and positive emotion were all supported. Finally, this study confirmed that positive emotions increased Chinese consumers' purchase intentions of a U.S. apparel brand. Theoretical and managerial implications were discussed based on the findings.

• The Journal of Korea Robotics Society
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• v.5 no.3
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• pp.224-230
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• 2010

As robots are no longer just working labors in the industrial fields, but stepping into the human's daily lives, interaction and communication between human and robot is becoming essential. For this social interaction with humans, emotion generation of a robot has become necessary, which is a result of very complicated process. Concept of mood has been considered in psychology society as a factor that effects on emotion generation, which is similar to emotion but not the same. In this paper, mood factors for robot considering not only the conditions of the robot itself but also the circumstances of the robot are listed, chosen and finally considered as elements defining a 2-dimensional mood space. Moreover, architecture that combines the proposed mood model and a emotion generation module is given at the end.

• Journal of the Korea Society of Computer and Information
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• v.18 no.5
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• pp.43-52
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• 2013

In recent years, a large amount of music content is distributed in the Internet environment. In order to retrieve the music content effectively that user want, various studies have been carried out. Especially, it is also actively developing music recommendation system combining emotion model with MIR(Music Information Retrieval) studies. However, in these studies, there are several drawbacks. First, structure of emotion model that was used is simple. Second, because the emotion model has not designed for Korean language, there is limit to process the semantic of emotional words expressed with Korean. In this paper, through extending the existing emotion model, we propose a new emotion model KOREM(KORean Emotional Model) based on Korean. And also, we design and implement ontology using emotion model proposed. Through them, sorting, storage and retrieval of music content described with various emotional expression are available.