• Science of Emotion and Sensibility
• /
• v.20 no.2
• /
• pp.161-170
• /
• 2017

Emotion affects many parts of human life such as learning ability, behavior and judgment. It is important to understand human nature. Emotion can only be inferred from facial expressions or gestures, what it actually is. In particular, emotion is difficult to classify not only because individuals feel differently about emotion but also because visually induced emotion does not sustain during whole testing period. To solve the problem, we acquired bio-signals and extracted features from those signals, which offer objective information about emotion stimulus. The emotion pattern classifier was composed of unsupervised learning algorithm with hidden nodes and feature vectors. Restricted Boltzmann machine (RBM) based on probability estimation was used in the unsupervised learning and maps emotion features to transformed dimensions. The emotion was characterized by non-linear classifiers with hidden nodes of a multi layer neural network, named deep belief network (DBN). The accuracy of DBN (about 94 %) was better than that of back-propagation neural network (about 40 %). The DBN showed good performance as the emotion pattern classifier.

• Journal of the Korean Society of Costume
• /
• v.57 no.9
• /
• pp.149-160
• /
• 2007

The purpose of this study was to investigate effects of service qualities and consumption emotion on consumer satisfaction of internet fashion shopping malls. Data were obtained from 304 internet fashion shopping mall consumers who have bought fashion products or visited an internet fashion shopping mall. Questionnaires related to service quality, consumption emotion, consumer satisfaction. For analysis of data, exploratory factor analysis, confirmatory factor analysis, path analysis were applied. The results were as follows: 1. The service quality dimensions of internet fashion shopping malls were reliability, merchandise variability, web-design, communication and safety. The consumption emotion dimensions were classified as positive emotion and negative emotion. 2. The service quality of internet fashion shopping malls and the consumption emotion had an effect on consumer satisfaction of internet fashion shopping malls. The dimensions of communication, merchandise variability of the service quality in internet fashion shopping malls had an effect on positive emotion. Safety, reliability of the service quality had an effect on negative emotion. Both positive emotion and negative emotion of the consumption emotion dimensions had an effect on consumer satisfaction of internet fashion shopping malls.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.11 no.2
• /
• pp.124-128
• /
• 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
• /
• v.25 no.2
• /
• pp.215-220
• /
• 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.

• The Pure and Applied Mathematics
• /
• v.24 no.4
• /
• pp.227-241
• /
• 2017

The study investigates the stock market using emotion index calculated from SMD based on investors' emotion. In the VAR anlaysis, we find that the correlation between the KOSPI200 return and emotion score sum is highest in 2- or 3- day lag. This study concludes that explanatory power of the SMD emotion index is limited in explaining the Korean stock market yet.

• Science of Emotion and Sensibility
• /
• v.11 no.4
• /
• pp.613-628
• /
• 2008

Mind reading is an essential part of normal social functioning and empathy plays a key role in social understanding. This study investigated how individual differences can have an effect on reading emotions in facial expressions, focusing on empathizing and systemizing. Two experiments were conducted. In study 1, participants performed emotion recognition test using facial expressions to investigate how emotion recognition can be different as empathy-systemizing type, facial areas, and emotion type. Study 2 examined how emotion recognition can be different as empathy-systemizing type, facial areas, and emotion type. An emotion discrimination test was used instead, with every other condition the same as in studies 1. Results from study 2 showed mostly same results as study 1: there were significant differences among facial areas and emotion type and also have an interaction effect between facial areas and emotion type. On the other hand, there was an interaction effect between empathy-systemizing type and emotion type in study 2. That is, how much people empathize and systemize can make difference in emotional discrimination. These results suggested that the empathy-systemizing type was more appropriate to explain emotion discrimination than emotion recognition.

• Journal of Institute of Control, Robotics and Systems
• /
• v.13 no.4
• /
• pp.371-376
• /
• 2007

This paper presents an emotion recognition and its expression system of an intelligent robot like a home robot or a service robot. Emotion recognition method in the robot is used by a facial image. We use a motion and a position of many facial features. apply a tracking algorithm to recognize a moving user in the mobile robot and eliminate a skin color of a hand and a background without a facial region by using the facial region detecting algorithm in objecting user image. After normalizer operations are the image enlarge or reduction by distance of the detecting facial region and the image revolution transformation by an angel of a face, the mobile robot can object the facial image of a fixing size. And materialize a multi feature selection algorithm to enable robot to recognize an emotion of user. In this paper, used a multi layer perceptron of Artificial Neural Network(ANN) as a pattern recognition art, and a Back Propagation(BP) algorithm as a learning algorithm. Emotion of user that robot recognized is expressed as a graphic LCD. At this time, change two coordinates as the number of times of emotion expressed in ANN, and change a parameter of facial elements(eyes, eyebrows, mouth) as the change of two coordinates. By materializing the system, expressed the complex emotion of human as the avatar of LCD.

• Journal of Korean Medical classics
• /
• v.36 no.2
• /
• pp.1-22
• /
• 2023

Objectives : In order to understand and apply Lee Jema's emotion control method, the basic concepts of his nature-temperament theory was examined. Lee's thoughts on emotion control, and the basic principles of his method were deduced from this process. Methods : The meaning and set-up of basic concepts in his nature-temperament theory as written in text such as the Donguisusebowon, Gyeokchigo, and Donguisusebowon Sasang Chobongwon were examined, and compared with similar concepts of Confucianism. Results & Conclusions : Out of concepts set by Lee, the Ae(哀)-No(怒)-Hui(喜)-Rak(樂) nature-temperament is the condition for emotion control. Junghwa(中和) is the aim of emotion control according to different stages of emotional expression, and Jiin(知人) is the precondition for emotion control. Lee's basic principles of emotion control could be summarized as following. First, it must be done with the aim for 'Goodness[善]' to be manifested. Second, it must be based on clear understanding of 'Insa(人事)'. Lastly, Hoyeonjigi(浩然之氣) and Hoyeonjiri(浩然之理) must be consistently cultivated for stable emotion control.

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

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