• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.146-149
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• 2003

This paper proposes the concept of “Artificial Emotion”(AE). The goal of AE is simulation, extension and expansion of natural emotion, especially human emotion. The object of AE is machine emotion and emotion machine. The contents of AE are emotion recognition, emotion measurement, emotion understanding emotion representation emotion generation, emotion processing, emotion control and emotion communication. The methodology, technology, scientific significance and application value of artificial emotion are discussed

• Journal of Integrative Natural Science
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• v.13 no.3
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• pp.97-104
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• 2020

This study suggests the emotion space modeling and emotion inference methods suitable for personalized services based on psychological and emotional models. For personalized emotion space modeling taking into account the subjective disposition based on the empirical assessment of the personal emotions felt by the personalization process of emotion space was used as a decision support tool, the Analytic Hierarchy Process. This confirmed that the special learning to perform personalized emotion space modeling without considering the subjective tendencies. In particular to check the possible reasoning based on fuzzy emotion space modeling and sensitivity for the quantification and vague human emotion to it based on the inherent human sensitivity.

• 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 Elementary Science Education
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• v.36 no.2
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• pp.155-162
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• 2017

The purpose of this study was to analyze science academic emotion and scientific imagination of students between a science gifted class and a general class in elementary school. Samples of this study were composed of 212 fifth and sixth graders in Gyeonggi province. The results of this study were as follows. First, positive scientific academic emotion of students in a science gifted class was higher than that of general class. Second, boredom and laziness of negative scientific academic emotion were higher scores in general students, whereas, angry area was higher scores of students in a science gifted class. Third, scientific imagination of students in a science gifted class was higher than that of general class. Fourth, both groups had a positive correlation between scientific imagination and positive science academic emotion. Especially, interest area of positive scientific academic emotion in both of the two groups influenced scientific imagination.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.2
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• pp.124-128
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• 2011

Music emotion recognition is currently one of the most attractive research areas in music information retrieval. In order to use emotion as clues when searching for a particular music, several music based emotion recognizing systems are fundamentally utilized. In order to maximize user satisfaction, the recognition accuracy is very important. In this paper, we develop a new music emotion recognition system, which employs a multilabel feature selector and multilabel classifier. The performance of the proposed system is demonstrated using novel musical emotion data.

• Journal of Korea Multimedia Society
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• v.25 no.2
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• pp.215-220
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• 2022

Emotion recognition is one of the most important and challenging areas of computer vision. Nowadays, many studies on emotion recognition were conducted and the performance of models is also improving. but, more research is needed on emotion recognition and sentiment analysis of video viewers. In this paper, we propose an emotion analysis system the includes a sentiment analysis model and an interest prediction model. We analyzed the emotional patterns of people watching popular and unpopular videos and predicted the level of interest using the emotion analysis system. Experimental results showed that certain emotions were strongly related to the popularity of videos and the interest prediction model had high accuracy in predicting the level of interest.

• Korean journal of food and cookery science
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• v.25 no.2
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• pp.206-218
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• 2009

The study assessed the relationship between brand evidence (e.g., brand name, price/value for money, servicescape, core service, employee service and self-image congruence) and positive/negative emotion and brand satisfaction, and between positive/negative emotion and brand satisfaction in the family restaurant setting. Also, the relationship of positive/negative emotion and brand satisfaction with customer loyalty were assessed. Customers who used five brands of family restaurant in Daegu and Pusan during October of 2008 were surveyed by questionnaires. Brand evidence was positively related to positive emotion and brand satisfaction, and was negatively related to negative emotion. Positive emotion was positively related to brand satisfaction and negative emotion was negatively related to brand satisfaction. Brand satisfaction was positively relatively to customer loyalty. The results indicate that management of family restaurants should focus on brand evidence as a means of increasing profits and sales volume.

• Science of Emotion and Sensibility
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• v.8 no.2
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• pp.161-167
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• 2005

The study is to examine how facial EMG responses change when children experience a positive emotion(happiness) and a negative emotion(fear). It is to prove that the positive emotion(happiness) could be distinguishable from the negative emotion(fear) by the EMG responses. Audiovisual film clips were used for evoking the positive emotion(happiness) and the negative emotion(fear). 47 children (11-13 years old, 23 boys and 24 girls) participated in the study Facial EMG (right corrugator and orbicularis oris) was measured while children were experiencing the positive or negative emotion. Emotional assessment scale was used for measuring children's psychological responses. It showed more than $85\%$ appropriateness and 3.15, 4.04 effectiveness (5 scale) for happiness and fear, respectively. Facial EMG responses were significantly different between a resting state and a emotional state both in happiness and in fear (p<001). Result suggests that each emotion was distinguishable by corrugator and orbicularis oris responses. Specifically, corrugator was more activated in the positive emotion(happiness) than in the negative emotion(fear), whereas orbicularis oris was more activated in the negative emotion(fear) than in the positive emotion(fear).

• Journal of the Semiconductor & Display Technology
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• v.18 no.1
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• pp.97-101
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• 2019

Understanding and classification of the human's emotion play an important tasks in interacting with human and machine communication systems. This paper proposes a novel emotion recognition method by extracting facial keypoints, which is able to understand and classify the human emotion, using active Appearance Model and the proposed classification model of the facial features. The existing appearance model scheme takes an expression of variations, which is calculated by the proposed classification model according to the change of human facial expression. The proposed method classifies four basic emotions (normal, happy, sad and angry). To evaluate the performance of the proposed method, we assess the ratio of success with common datasets, and we achieve the best 93% accuracy, average 82.2% in facial emotion recognition. The results show that the proposed method effectively performed well over the emotion recognition, compared to the existing schemes.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2000.04a
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• pp.306-311
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• 2000

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 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.