• Journal of Korea Game Society
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• v.10 no.4
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• pp.15-22
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• 2010

The purpose of this research is to analyze players' emotion pattern for conducting a quest in Role Playing Game(RPG). We have rebuilt up the action and content of gameplay related to category to set up five action classes of game players based on the literature review about the human behavior classification. Moreover, Mabinogi game includes the composition of various quests by story-centered expanse. We classified the quest structure of the tutorial mode, initial state, of its game into the cognitive action. We build the model of the correlation between cognitive behavior patterns of gameplay and emotions derived from targeting ten novices. The result of this research reveals that gameplayers' stimulus levels are identified to emotion pattern. It is enable to grope to concrete the design of the quest and the level in a specified state. Moreover, players' emotion variation is indicated to the type of expression of fun elements. We expect to use a device to induce the curiousness and the challenge for conducting the higher goal of game in the whole.

• Fashion & Textile Research Journal
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• v.20 no.5
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• pp.509-519
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• 2018

This study is to examine the effects of salespeople' attributes (i.e., empathy, availability, professional appearance) on consumer cognition, emotion, and behavior. A conceptual model was developed based on stimulus-organism-response (S-O-R) theory and cognition-emotion theory. A total of 542 questionnaires were collected online and some incompletely written questionnaires were excluded. Because of the high possibility of memory distortion, only the questionnaires (n=220) written by those who visited fashion stores within one week were used for the final analysis. The results of PLS analyses demonstrated that 1) salespeople's empathy directly affected consumers' shopping emotion; 2) salespeople's availability and professional appearance indirectly affected consumer's shopping emotion through store image; 3) consumers' shopping emotion positively affected purchase intention. Theoretical and practical implications of the results are discussed in conclusion. As a result of this research, the main characteristics of the salespeople were identified in order to allow the consumers visiting the fashion store to buy the fashion products naturally and the basic directions of sales manuals for the salespeople in the fashion store were presented. It is also hoped that academic researchers will be able to use the characteristics of salespeople as the main data to understand how they affect consumers' cognitive and emotional responses and how they are connected to purchase behavior.

• Journal of Korean Institute of Industrial Engineers
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• v.43 no.3
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• pp.176-183
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• 2017

In recent years, studies about multitasking becomes more important. During multitasking, operators can feel frustration when they are interrupted during the task and frustration can affect operator's emotional state and performance. However there is no research on measuring the frustration quantitatively in multitasking environment. In this paper, we suggested quantitative measurement of frustration during multitasking. In order to measure the frustration, we made a mathematical representation with emotional decay model and the initial intensity of frustration based on cognitive closure theory. The amount of initial intensity could be represented as the ratio of actual remaining time to expected remaining time. By the experiment, we measured the frustration during the experiment and compared this values with values of frustration dimension of NASA-TLX. Finally we got the linear regression model with a good accuracy ($R^2=0.986$). This study contributes to measuring the emotion quantitatively by the relation of expected and actual remaining time in multitasking environment.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2000.04a
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• pp.126-132
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• 2000

This paper presents a facial expression recognition based on Gabor wavelets that uses a fuzzy C-means(FCM) clustering algorithm and neural network. Features of facial expressions are extracted to two steps. In the first step, Gabor wavelet representation can provide edges extraction of major face components using the average value of the image's 2-D Gabor wavelet coefficient histogram. In the next step, we extract sparse features of facial expressions from the extracted edge information using FCM clustering algorithm. The result of facial expression recognition is compared with dimensional values of internal stated derived from semantic ratings of words related to emotion. The dimensional model can recognize not only six facial expressions related to Ekman's basic emotions, but also expressions of various internal states.

• Science of Emotion and Sensibility
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• v.24 no.4
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• pp.53-68
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• 2021

The continuous development of in-vehicle information systems in recent years has dramatically enriched drivers' driving experience while occupying their cognitive resources to varying degrees, causing driving distraction. Under this complex information system, managing the complexity and priority of information and further improvement in driving safety has become a key issue that needs to be urgently solved by the in-vehicle information system. The new interactive methods incorporating the augmented reality (AR) and head-up display (HUD) technologies into in-vehicle information systems are currently receiving widespread attention. This superimposes various onboard information into an actual driving scene, thereby meeting the needs of complex tasks and improving driving safety. Based on the qualitative research methods of surveys and telephone interviews, this study collects the information needs of the target user groups (i.e., beginners and skilled drivers) and constructs a three-mode information database to provide the basis for a customized AR-HUD interface design.

• Korean Journal of Culture and Social Issue
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• v.27 no.4
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• pp.475-503
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• 2021

The purpose of this study is to clarify the constructs of emotion suppression and help understanding on the multidimensional nature of emotion suppression by classifying constructs for suppression according to the KMW model. Also, this study examined the gender differences of emotion suppression. For this purpose, 657 adult male and female subjects were evaluated for attitude toward emotions, and difficulty in emotional regulation, as well as depression, state anger and daily stress scale. As a result of the exploratory factor analysis on the scales related to the emotion suppression factors, the emotion suppression factors corresponding to each stage of the KMW model were found to be 'distraction against emotional information, 'difficulty in understanding and interpretation of emotions', 'emotion control beliefs', 'vulnerability on emotional expression beliefs'. Next, the study participants were classified by performing a cluster analysis based on each emotion suppression factor. As a result, four clusters were extracted and named 'emotional control belief cluster', 'emotional expression cluster', 'emotional attention failure cluster', and 'general emotional suppression cluster'. As a result of examining the average difference of male depression, depression, state anger, and daily stress for each group, significant differences were found in all dependent variables. As a result of examining whether there is a difference in the frequency of emotional suppression clusters according to gender, the frequency of emotional suppression clusters was high in men, and the ratio of emotional expression clusters was high in women. Finally, it was analyzed whether there was a gender difference in the effect of the emotional suppression cluster on psychosocial adaptation, and the implications were discussed based on the results of this study.

• 한국HCI학회:학술대회논문집
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• 2008.02b
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• pp.411-416
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• 2008

The development of games has brought about the birth of game characters that are visually very realistic. At present, one sees much enthusiasm for giving the characters emotions through such devices as avatars and emoticons. However, in a freely changing environment of games, the devices merely allow for the expression of the value derived from a first input rather than creating expressions of emotion that actively respond to their surroundings. As such, there are as of yet no displays of deep emotions among game characters. In light of this, the present article proposes the 'CROSS(Character Reaction on Specific Situation) Model AE Engine' for game characters in order to develop characters that will actively express action and emotion within the environment of the changing face of games. This is accomplished by classifying the emotional components applicable to game characters based on the OCC model, which is one of the most well known cognitive psychological models. Then, the situation of game playing analysis of the commercialized RPG game is systematized by ontology.

• Journal of Digital Convergence
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• v.16 no.3
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• pp.513-525
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• 2018

The purpose of this study is to explore the experience of participants in the adventurous leisure activities and to examine the structural relations of the cognitive experience, the emotional experience and adherence intention. Robust quantitative measures were developed from rich qualitative data. The five dimensions selected from two preliminary tests were being away, technical enhancement, fascination with nature, challenge, and interpersonal trust. The cognitive dimensions have a significant effect on the emotional arousal - pleasure dimension. Our study also shows a positive causal relationship between emotional experience and adherence intention. Implications of this study include 1) a developed questionnaire for measuring the cognitive experience dimension of adventure leisure and establishing a foundation for future research, and 2) an identified psychological model among cognitive, emotion, and intention. We offer opportunities to better understand the psychological factors that motivate participation in adventure leisure.

• Journal of Korean Academic Society of Home Health Care Nursing
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• v.27 no.1
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• pp.29-41
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• 2020

Purpose: This study aimed to investigate the influence of post-traumatic stress on professional quality of life as mediated by cognitive emotion regulation among nurses working in small and medium hospitals who have experienced violence and to develop and test a structural equation model of that professional quality of life. Methods: Participants were 215 nurses who had experienced violence working in medium and small hospitals. They were surveyed using a structured questionnaire. Results: The final model was shown to have good fit with χ² (2.83), GFI (.90), TLI (.90), and CIF (.90). Therefore, the model was selected as the final model, supporting 7 of the 11 hypotheses. Post-traumatic stress, adaptive emotional regulation, and maladaptive emotional regulation had significant impacts on empathy satisfaction (professional quality of life subscale) and empathy fatigue (subscale of professional life quality) among nurses who had experienced violence, and the explanatory power of these variables was 28.7% and 38.6%, respectively. Conclusion: In the development of nursing intervention programs to improve the professional quality of life of nurses who have experienced violence, factors such as post-traumatic stress and cognitive emotion regulation (adaptive and maladaptive) should be considered as they were identified in this study as influencing the professional quality of life of such nurses in medium and small hospitals.

• Science of Emotion and Sensibility
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• v.21 no.3
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• pp.83-102
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• 2018

The process model of emotion regulation suggests that cognitive reappraisal and expressive suppression engage at different time points in the regulation process. Although multiple brain regions and networks have been identified for each strategy, no articles have explored changes in network characteristics or network connectivity over time. The present study examined (a) the whole-brain network and six other resting-state networks, (b) their modularity and global efficiency, which is an index of the efficiency of information exchange across the network, (c) the degree and betweenness centrality for 160 brain regions to identify the hub nodes with the most control over the entire network, and (d) the intra-network and inter-network functional connectivity (FC). Such investigations were performed using a traditional large-scale FC analysis and a relatively recent sliding window correlation analysis. The results showed that the right inferior orbitofrontal cortex was the hub region of the whole-brain network for both strategies. The present findings of temporally altering functional activity of the networks revealed that the default mode network (DMN) activated at the early stage of reappraisal, followed by the task-positive networks (cingulo-opercular network and fronto-parietal network), emotion-processing networks (the cerebellar network and DMN), and sensorimotor network (SMN) that activated at the early stage of suppression, followed by the greater recruitment of task-positive networks and their functional connection with the emotional response-related networks (SMN and occipital network). This is the first study that provides neuroimaging evidence supporting the process model of emotion regulation by revealing the temporally varying network efficiency and intra- and inter-network functional connections of reappraisal and suppression.