• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2012.05a
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• pp.73-74
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• 2012

• Korean Journal of Child Studies
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• v.35 no.2
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• pp.117-136
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• 2014

This study examined the effects of maternal grandmothers' positive parenting behavior, mothers' emotion regulation, and positive parenting behavior on children's emotion regulation. A total of 348 mothers of fourth and fifth graders responded to questionnaires, which included items related to their mothers' positive parenting behavior, their own emotion regulation and positive parenting behavior, and their children's emotion regulation. The data were analyzed by means of correlations and Structural Equation Modeling (SEM). First, maternal grandmothers' positive parenting behavior significantly affected mothers' emotion regulation, but mothers' emotion regulation did not directly affect their children's emotion regulation. Second, maternal grandmothers' positive parenting behavior had an effect on mothers' positive parenting behavior, which led to a high level of their children's emotion regulation. Lastly, maternal grandmothers' positive parenting behavior indirectly influenced children's emotion regulation through mothers' emotion regulation and positive parenting behavior. This study emphasizes the intergenerational transmission of positive parenting, as well as a crucial influence of mothers' positive parenting behavior on children's emotion regulation.

• Journal of Korea Society of Digital Industry and Information Management
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• v.4 no.1
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• pp.55-63
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• 2008

I Previous scrolling-shooter games cannot represent various emotions of characters as a personality and situations, so it can only represent simple and momentary emotions. This paper purpose to develop and applying an artificial emotion which gives emotional responses and actions to character as a personality and situations of a character. So we proposed an artificial emotion that receives emotional stimulus, analyzes what emotion will be generated, controls various emotions by a personality and time, and exports a current emotion. To visualize and to test an artificial emotion, We made a scrolling shooter game which has two characters who have a different personality each other. And we applied an artificial emotion to that game, modified it to be able to change status as emotions. To estimate a satisfaction of a artificial emotion for a scrolling-shooter game, we made up a question to two groups-one has people who likes a scrolling shooter game, the other has people who doesn't.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 1997.11a
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• pp.11-15
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• 1997

This study deals with the method for modeling relationship between human sensibility and design dldments of a product for applying human sensibility to product development, Inorder to extract sensibility characteeristics concerning a product, we figured out the relationship between xensibilith and design elements using corrdlation analysis and multiple regression analysis, and then modeled the realtionship between then through multiple objective linert programming. The results of this study can be effectively applied to develop a product based on human sensibility

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.10
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• pp.957-962
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• 2010

If we want to recognize the human's emotion via the facial image, first of all, we need to extract the emotional features from the facial image by using a feature extraction algorithm. And we need to classify the emotional status by using pattern classification method. The AAM (Active Appearance Model) is a well-known method that can represent a non-rigid object, such as face, facial expression. The Bayesian Network is a probability based classifier that can represent the probabilistic relationships between a set of facial features. In this paper, our approach to facial feature extraction lies in the proposed feature extraction method based on combining AAM with FACS (Facial Action Coding System) for automatically modeling and extracting the facial emotional features. To recognize the facial emotion, we use the DBNs (Dynamic Bayesian Networks) for modeling and understanding the temporal phases of facial expressions in image sequences. The result of emotion recognition can be used to rehabilitate based on biofeedback for emotional disabled.

• Science of Emotion and Sensibility
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• v.15 no.2
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• pp.283-296
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• 2012

The goal of this study is to determine the social emotion model as an emotion sharing relationship and information sharing relationship based on the user's relations at social networking services. 26 social emotions were extracted by verification of compliance among 92 different emotions collected from the literature survey. The survey on the 26 emotion words was verified to the similarity of social relation types to the Likert 7-points scale. The principal component analysis of the survey data determined 12 representative social emotions in the emotion sharing relation and 13 representative social emotions in the information sharing relation. Multidimensional scaling developed the two-dimensional social emotion model of emotion sharing relation and of information sharing relation based on online communication environment. Meanwhile, insignificant factors in the suggest social emotion models were removed by the structural equation modeling analysis, statistically. The test result of validity analysis demonstrated the fitness of social emotion models at emotion sharing relationships (CFI: .887, TLI: .885, RMSEA: .094), social emotion model of information sharing relationships (CFI: .917, TLI: .900, RMSEA : 0.050). In conclusion, this study presents two different social emotion models based on two different relation types. The findings of this study will provide not only a reference of evaluating social emotions in designing social networking services but also a direction of improving social emotions.

• Proceedings of the IEEK Conference
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• 2003.07d
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• pp.1243-1246
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• 2003

It is known that structure of Human's brain information system is controlled by cerebral cortex mainly. Cerebral cortex is divided by sensory area, motor area and associated area largely. Sensory area takes part in information from environment and motor area is actuation by decision as associated area determined. It is possible to copy brain information system by input-output pattern. but there is difficulty in modeling of memorizing new information. Such action is performed by Limbic Lobe and Papez circuit which is controlled by intrinsic emotion. So we need of definition of emotion's role in decision. In this paper, we define roles of emotion in intrinsic decision using Dynamic Cognitive Maps(DCMs). The emotion is evaluated by outside information then intrinsic decision performed as how much emotion variated. The dynamic cognitive maps take part in emotion evaluating process.

• Journal of Korean Academy of Nursing Administration
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• v.12 no.2
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• pp.213-224
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• 2006

Purpose: This study examined Korean nurses' job attitude (i.e., satisfaction and burnout) regarding the extent to which organization's emotion display rule influences on job attitudes through emotion-related variables (i.e., negative emotion suppress behavior and inauthenticity), thereby examining mediation effects of negative emotion suppress behavior and inauthenticity. Method: Using a survey to nurses working in various general hospitals in Korea, structural equation modeling was adopted. Result: Emotion display rule affected outcome variables but these effects were mostly observed via the two mediators, negative emotion suppress and inauthenticity, which largely supports the research model. Conclusion: Individuals who perceived stronger emotional display rule suppressed more their negative emotion, and also perceived more inauthenticity. In turn, negative emotion suppress behavior only affected job burnout positively. Inauthenticity showed a negative effect on job satisfaction while it had a positive effect on burnout. The study provided directions for future research and practical implications to help nurses' effective job performance.

• 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.

• Science of Emotion and Sensibility
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• v.20 no.1
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• pp.75-82
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• 2017

We propose a novel method for modeling emotional dimensions using expansion of Russell's (1980) emotional dimensions (Circumplex Model). The Circumplex Model represents emotional words in two axes (Arousal, Valence). However, other researchers have insisted that location of word in Russell's model which is expressed by single point could not represent exact position. Consequently, it is difficult to apply this model in engineering fields (such as Science of Emotion & Sensibility, Human-Computer-Interaction, Ergonomics, etc.). Therefore, we propose a new modeling method which expresses emotional word not as a single point but as a region. We conducted survey to obtain actual data and derived equations using ellipse formula to represent emotional region. Furthermore, we applied ANEW and IAPS which are commonly used in many studies to our emotional model using pattern recognition algorithm. Using our method, we could solve problems with Russell's model and our model is easily applicable to the field of engineering.