• 인지과학
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• 제21권2호
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• pp.387-408
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• 2010

이 연구는 자극의 정서성에 따른 부호화 기전의 차이와 맥락의 정서성이 중립 단어의 부호화 기전에 미치는 영향을 알아보기 위해 수행되었으며, 특히 정서자극의 우수한 기억 수행이 주의자원 배분에 기인한 것인지 밝히는 것을 목적으로 하였다. 이 연구는 연구 목적을 달성하기 위해 정서자극과 비정서적 단어를 연속으로 제시하여 자극과 맥락의 정서성이 기억 수행과 ERP 평균 진폭에 미치는 영향을 분석하였다. 정서자극으로는 IAPS(International Affective Picture System) 자극을 사용하였으며, 긍정, 중립, 부정자극을 제시하였다. 행동 분석결과, 정서자극이 중립자극보다 우수한 기억 수행을 보인 반면, 정서맥락 내 단어는 중립맥락 내 단어에 비해 저조한 기억 수행을 보였다. 또한 ERP의 LPC(Late Positive Complex) 진폭분석 결과, 정서자극이 중립자극에 비해 높은 진폭을 보인 반면, 정서맥락 내 단어는 중립맥락 내 단어에 비해 낮은 진폭을 나타냈다. 이 결과는 정서자극에 대한 주의 선점이 정서맥락 내 단어의 기억 수행을 방해한다는 자원할당 모형의 설명에 부합하는 것으로서, 정서자극에 대한 주의자원 배분 설명을 지지하는 것이다.

• 대한가정학회지
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• 제36권11호
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• pp.61-72
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• 1998

The purpose of this study was to investigate parental emotion regulation and children's understanding of emotional display rules. 31 boys and 29 girls of the first and fourth grades and their parents were selected for the subject. Sixty children were interviewed on eight interpersonal conflict situations and parent completed the PACES(Saarni, 1985) separately. The main results of this study were as follows. 1) Children's understanding of emotional display rules increased with age. 2) Children's primary justification for using emotional display rules was self-protective one. Girls used more often prosocial justification than boys. 3) Parental emotion regulation was significantly different between the two contexts: a child might cause another person substantial emotional distress and a child didn't cause another person substantial emotional distress. 4) Parental regulation was differed by children's age in the context that the child might cause another person substantial emotional distress. 5) Father's regulation was differed by children's sex in the context that the child might cause another person substantial emotional distress. 6) Maternal regulation was positively correlated to the level of emotional display rules in the context that the child might cause another person substantial emotional distress.

• 한국컴퓨터정보학회논문지
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• 제20권10호
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• pp.69-76
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• 2015

User's selection of music is largely influenced by private tastes as well as emotional states, and it is the unconsciousness projection of user's emotion. Therefore, we think user's emotional states to be music itself. In this paper, we try to grasp user's emotional states from music selected by users at a specific context, and we analyze the correlation between its context and user's emotional state. To get emotional states out of music, the proposed method extracts emotional words as the representative of music from lyrics of user-selected music through morphological analysis, and learns weights of linear classifier for each emotional features of extracted words. Regularities learned by classifier are utilized to calculate predictive weights of virtual music using weights of music chosen by other users in context similar to active user's context. Finally, we propose a method to recommend some pieces of music relative to user's contexts and emotional states. Experimental results shows that the proposed method is more accurate than the traditional collaborative filtering method.

• 대한음성학회:학술대회논문집
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• 대한음성학회 2006년도 춘계 학술대회 발표논문집
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• pp.123-125
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• 2006

One of the biggest problems unsolved in emotional speech acquisition is how to make or find a situation which is close to natual or desired state from humans. We proposed a method to collect emotional speech data by scriptual context. Several contexts from the scripts of drama were chosen by the experts in the area. Context were divided into 6 classes according to the contents. Two actors, one male and one female, read the text after recognizing the emotional situations in the script.

• 한국융합학회논문지
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• 제9권3호
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• pp.79-90
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• 2018

본 연구의 목적은 긍정 얼굴 자극에 대한 주의의 과정에서 정서 맥락적 배경의 유무에 따라 사회불안성향자들과 정상인 간 차이가 나타나는지 살펴보고자 하는 것이다. 이를 위해 무맥락적 배경에서 긍정 얼굴 자극에 대한 주의 과정을 확인하였고, 다음으로 정서 맥락적 배경이 존재하는 상황에서 동일한 주의 과정을 탐색하였다. D시의 800명의 대학생에게 SADS와 CES-D를 실시하고, 사회불안집단(SA, n=24)과 정상 대조군(NC, n=24)을 선별하였다. 주의 개입과 주의 이탈 두 요소를 측정하기 위해 최초 응시 방향, 최초 응시 시간을 안구 운동 추적을 통해 측정하였다. 그 결과, 사회불안집단의 경우 배경이 없는 상태에서 통제집단에 비해 긍정 얼굴 자극으로부터 더 빠른 주의 이탈이 관찰되었다. 그러나 긍정 얼굴 자극이 긍정 배경 자극 안에 제시되면 사회불안집단과 통제집단 간의 차이가 관찰되지 않았다. 이 결과는 긍정 배경이 사회불안장애성향자의 정서 처리에 영향을 미친다는 것을 시사한다.

• 아동학회지
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• 제24권6호
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• pp.15-31
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• 2003

This study examined the effects of emotion inducing contexts on types of infants smiling. Facial expressions of forty-five 11-to 15-month-old infants were videotaped in an experimental lab with positive and negative emotional contests. Infants' smiling was identified as the Duchenne smile or non-Duchenne smile based on FACS(Facial Action Coding System, Ekman & Friesen, 1978). Duration of smiling types was analyzed. Overall, infants showed more smiling in the positive than in the negative emotional context. Occurrence of Duchenne smiling was more likely in the positive than in the negative context and in the peek-a-boo than in the melody toy condition within the same positive context. Non-Duchenne smiling did not differ by context.

• Safety and Health at Work
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• 제11권3호
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• pp.353-360
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• 2020

Background: Urban bus drivers work under conditions that are among the most demanding, stressful, and unhealthy with higher rates of mortality and morbidity as well as absenteeism and turnover. Methods: Drawing on the job demand-resource model, this study investigates the impacts of job characteristics on emotional exhaustion and the effects of emotional exhaustion on job outcomes (including job satisfaction, life satisfaction, organizational commitment, and turnover intention) in the context of bus drivers. Results: Using self-reported survey data collected from a sample of 320 Taiwanese urban bus drivers, results reveal that role overload and work-family conflict (as job demand factors) positively relate to emotional exhaustion, and organizational support (as a job resource factor) is negatively associated with emotional exhaustion. Emotional exhaustion has negative effects on both job satisfaction and organizational commitment. Job satisfaction positively leads to life satisfaction, whereas organizational commitment negatively relates to turnover intention. Conclusion: This study concludes that role overload and work-family conflict as two stressors related to job demands and organizational support as the job resource factor to affect emotional exhaustion which further influence well-being in bus driver context. The moderating effects of both extraversion and neuroticism on the relationship between job demands and emotional exhaustion are evident.

• 제어로봇시스템학회논문지
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• 제16권1호
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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.

• 한국의류학회지
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• 제41권2호
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• pp.266-280
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• 2017

This study predicted consumer approach/avoidance behavior through consumer emotional experiences and examined the moderating effect of perceived surprises in the context of digital signage in store environments. A self-administered questionnaire consisted of consumer emotional experience (e.g., pleasure, arousal, and dominance), approach-avoidance behavior and perceived surprise by digital signage. A total of 278 usable responses were obtained from consumers who experienced digital signage at fashion retail stores. The findings support the Mehrabian-Russell model in the context of digital signage. Approach behavior was predicted by pleasure and arousal emotional experience, while avoidance behavior was predicted by dominance. The moderating effect of perceived surprise was also indicated in the effect of emotional experience on approach or avoidance behavior. In the high level of perceived surprise, pleasure and arousal had significant effects on approach behavior, whereas dominance had significant effect on avoidance behavior. This study discussed theoretical and managerial implications for creating emotional experiences and developing strategic store management by utilizing new digital technology within the fashion retail environments.

• International Journal of Contents
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• 제18권3호
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• pp.11-20
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• 2022

Human Emotion Recognition is an exciting topic that has been attracting many researchers for a lengthy time. In recent years, there has been an increasing interest in exploiting contextual information on emotion recognition. Some previous explorations in psychology show that emotional perception is impacted by facial expressions, as well as contextual information from the scene, such as human activities, interactions, and body poses. Those explorations initialize a trend in computer vision in exploring the critical role of contexts, by considering them as modalities to infer predicted emotion along with facial expressions. However, the contextual information has not been fully exploited. The scene emotion created by the surrounding environment, can shape how people perceive emotion. Besides, additive fusion in multimodal training fashion is not practical, because the contributions of each modality are not equal to the final prediction. The purpose of this paper was to contribute to this growing area of research, by exploring the effectiveness of the emotional scene gist in the input image, to infer the emotional state of the primary target. The emotional scene gist includes emotion, emotional feelings, and actions or events that directly trigger emotional reactions in the input image. We also present an attention-based fusion network, to combine multimodal features based on their impacts on the target emotional state. We demonstrate the effectiveness of the method, through a significant improvement on the EMOTIC dataset.