• Cartoon and Animation Studies
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• s.33
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• pp.383-402
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• 2013

In this study, we apply the facial Facial Action Coding System for coding the muscular system anatomical approach facial expressions to be displayed in response to a change in sensitivity. To verify by applying the virtual character the Duchenne smile to the original. I extracted the Duchenne smile by inducing experiment of emotion (man 2, woman 2) and the movie theater department students trained for the experiment. Based on the expression that has been extracted, I collect the data of the facial muscles. Calculates the frequency of expression of the face and other parts of the body muscles around the mouth and lips, to be applied to the virtual character of the data. Orbicularis muscle to contract end of lips due to shrinkage of the Zygomatic Major is a upward movement, cheek goes up, the movement of the muscles, facial expressions appear the outer eyelid under the eye goes up with a look of smile. Muscle movement of large muscle and surrounding Zygomatic Major is observed together (AU9) muscles around the nose and (AU25, AU26, AU27) muscles around the mouth associated with openness. Duchen smile occurred in the form of Orbicularis Oculi and Zygomatic Major moves at the same time. Based on this, by separating the orbicularis muscle that is displayed in the form of laughter and sympathy to emotional feelings and viable large muscle by the will of the person, by applying to the character of the virtual, and expression of human I try to examine expression of the virtual character's ability to distinguish.

• Korean Journal of Child Studies
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• v.38 no.1
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• pp.251-262
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• 2017

Objective: This study analyzed mother-child interactions in a stressful situation each second by mother's emotional regulation level. Methods: The study was conducted with 16 mothers and their 5-year-old children playing a teaching task for 15 min. During the interactions, the participants were videotaped and examined. Furthermore, qualitative analysis was used for analyzing mother-child interactions in detail by creating a situation that maximizes the stress and frustration of the mother and child. Results: The results showed that maternal humor and affection were significantly related to child positive emotion and that maternal coaching closely correlated with the child pride, pleasure, and whining. Additionally, maternal intrusive behavior showed a positive correlation with child anger. Lastly, mothers with higher levels of emotional regulation more often expressed affection to their children. They were more actively involved in the tasks and used fewer positive or negative directive expressions. Therefore, children of this group expressed more positive emotions. Conclusion: These findings suggests that programs improving parental emotional reaction and emotion regulation should be developed.

• Journal of The Korean Association For Science Education
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• v.25 no.4
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• pp.503-513
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• 2005

The purpose of this study was to analyze the generating processes of scientific emotion, that appears during the generation of biological hypotheses. To perform the study, a tentative model was set up through pilot test, a think-aloud training procedure was planned and a standardized interview instrument was developed before getting protocols. In this study, 8 college students were selected to bring out protocol through the method of think-aloud, retrospective debriefing, focused interview and observing. As the result of analysis of the collected protocol through coding scheme, 4 types of process for scientific emotion-generating were sorted out. First type was a basic process which was a feeling process in prior to recognition. Second type was a retrospective process that explains the process of retrospect for emotional memory based on the past. Third type was a cognitive process and it explains emotion that occurs during thinking process to achieve cognitive goal. Fourth type was an attribution process and it explains that emotion is generated in the process of attribution for cognitive goal's achievement. These types of process of scientific emotion-generating can contribute the basis for developing cognitive model of EBL (Emotional Brain-based Learning) strategy.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2002.11a
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• pp.160-166
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• 2002

본 연구의 목적은 비디오/오디오 프로토콜 분석 방식을 이용해서 텍스타일 디자인 프로세스 중 모티브 개발 단계에서 디지털 나염(DTP : Digital Textile Printing) 전용 캐드(CAD)와 같은 디자인 저작도구를 설계할 때 어떤 요소에 중점을 두고 개발 할 것인지에 대한 향상된 지침을 마련하는데 있다. 텍스타일 디자인 프로세스에 대한 프로토콜 분석을 위해 선행 연구를 고찰하여 디자인 행동 범주의 틀을 하향식(top-down)방식으로 설정하고 실제 행동 프로토콜 (action protocol) 분석을 통해 상향식(bottom-up)방식으로 세부 디자인 행동을 도출하였다. 텍스타일 디자인은 선행연구의 건축디자인과는 다른 특징을 지니기 때문에 프로토콜 분석에서도 새로운 디자인 행동 범주(action category)가 필요하게 되었다. 이를 위하여 모델 휴먼 프로세서(Model Human Processor)이론을 근거로 디자인 행동을 모터 행동(motor action), 지각 행동(perceptual action), 인지 행동(cognitive action)의 세 가지 범주[4]로 나누었으며 텍스타일 디자인 프로세스에 적합한 코딩 스킴(coding scheme)을 개발하였다. 본 연구에서는 이 새로운 코딩 스킴을 토대로 디자인 저작도구에 대한 디자이너의 인지적 모형(Cognitive Model)을 개발하였다. 이렇게 개발된 디자이너의 인지적 모형은 디지털 나염을 기반으로 하는 모티브 개발 단계에서 스케치와 렌더링에 대한 디자인 저작 도구의 향상된 설계지침 뿐만 아니라 방향도 시사하였다.

• International Journal of Advanced Culture Technology
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• v.7 no.4
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• pp.49-55
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• 2019

In the age of information, newly produced knowledge is mostly written in English. Therefore, there has been a strong demand for English language learning in the EFL context. However, most EFL learners possess a lack of interest and motivation in the text-based reading class. In this educational context, film is one of the most widely used materials in English reading classes considering that modern learners are predominantly familiar with various audiovisual materials. The purpose of this study is to investigate how Korean EFL learners experienced in the film-based reading class. Specifically, this study aims to analyze the EFL students' perceptions about the class and learning strategies that they used during the class. In order to comprehensively interpret the EFL learners' experiences in the classroom, a coding system consisting of five categories was developed: report, emotion, reflection, evaluation, future plans. The results of data analysis showed that the use of movies in English reading classes had positive effects on reading comprehension and inference of word meaning. The most frequently used learning strategies were affective strategies which helped them control their emotion, attitude, motivations and values, whereas memorization strategies were rarely used. In this respect, this study suggests that the use of movies in the EFL reading classroom encourage students' attention and help them obtain and activate schema which is useful in gaining a better understanding of text-based reading materials.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.5
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• pp.3188-3198
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• 2015

This study explores the health behaviors and related situations of Korean low-income breast cancer survivors using in-depth interview. The study derives 95 concepts, 23 sub-categories and 12 categories in open coding. Illness experiences were categorized by behavioral, psychological, and social domains, cognitive were categorized by causal and destiny thought, emotions were categorized by negative, positive emotion, reserve capacity were categorized by internal and external domains and health behaviors were categorized by behavioral, psychological, and social domains. Understanding illness experience, cognitive, emotion, reserve capacity and health behaviors for Korean low-income breast cancer survivors will be useful in developing social welfare interventions and for enhancing health promotion.

• Journal of Korea Multimedia Society
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• v.18 no.6
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• pp.763-771
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• 2015

The kinetic typography animates the static text and it will enable the delivery the opinion and emotion, but we should use professional software or do complex coding precess to create a motion into an existing static text. In this paper, we propose the primitive motion API which is the way to configure the kinetic typography easily by adding a motion into the static text. In the pursuit of this purpose, we analyzed the movement of the text, defined the underlying levels of the movement and designed the primitive motion API to express the kinetic typography promptly. Furthermore, we verified the performance of the primitive motion API by testing the usability. Using the primitive motion API to implement the kinetic typography explicitly might substitute for tedious coding process and usage of the existing professional software so it makes anyone be able to apply the kinetic typography in a variety of applications.

• Journal of KIISE:Computing Practices and Letters
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• v.7 no.5
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• pp.475-488
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• 2001

With the increase of the number of Internet users, various methodologies have been proposed for the effective design of web page. However, the prior methodologies have focused only on the functional aspect of web page while ignoring the emotional aspects of web pages. This paper focuses on the emotional design of home pages and aims to provide a methodology to design a web page suitable for goal emotions. In order to achieve the main purpose, we have conducted three related studies. First, we have identified basic emotional dimensions representing various feeling users have from web pages as a pool of emotional adjectives. Second, we have identified key design elements related to the emotion by observing the design process of expert designers. Third, we examined the causal relation between the perceived emotion and designed elements. The results indicate that some design elements are more effective to produce certain feeling than others. This paper ends with limitations and implications of the study results.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.4
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• pp.562-567
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• 2009

As a key mechanism of the human emotion interaction, Facial Expression is a powerful tools in HRI(Human Robot Interface) such as Human Computer Interface. By using a facial expression, we can bring out various reaction correspond to emotional state of user in HCI(Human Computer Interaction). Also it can infer that suitable services to supply user from service agents such as intelligent robot. In this article, We addresses the issue of expressive face modeling using an advanced active appearance model for facial emotion recognition. We consider the six universal emotional categories that are defined by Ekman. In human face, emotions are most widely represented with eyes and mouth expression. If we want to recognize the human's emotion from this facial image, we need to extract feature points such as Action Unit(AU) of Ekman. Active Appearance Model (AAM) is one of the commonly used methods for facial feature extraction and it can be applied to construct AU. Regarding the traditional AAM depends on the setting of the initial parameters of the model and this paper introduces a facial emotion recognizing method based on which is combined Advanced AAM with Bayesian Network. Firstly, we obtain the reconstructive parameters of the new gray-scale image by sample-based learning and use them to reconstruct the shape and texture of the new image and calculate the initial parameters of the AAM by the reconstructed facial model. Then reduce the distance error between the model and the target contour by adjusting the parameters of the model. Finally get the model which is matched with the facial feature outline after several iterations and use them to recognize the facial emotion by using Bayesian Network.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.69-92
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• 2015

The explosion of social media data has led to apply text-mining techniques to analyze big social media data in a more rigorous manner. Even if social media text analysis algorithms were improved, previous approaches to social media text analysis have some limitations. In the field of sentiment analysis of social media written in Korean, there are two typical approaches. One is the linguistic approach using machine learning, which is the most common approach. Some studies have been conducted by adding grammatical factors to feature sets for training classification model. The other approach adopts the semantic analysis method to sentiment analysis, but this approach is mainly applied to English texts. To overcome these limitations, this study applies the Word2Vec algorithm which is an extension of the neural network algorithms to deal with more extensive semantic features that were underestimated in existing sentiment analysis. The result from adopting the Word2Vec algorithm is compared to the result from co-occurrence analysis to identify the difference between two approaches. The results show that the distribution related word extracted by Word2Vec algorithm in that the words represent some emotion about the keyword used are three times more than extracted by co-occurrence analysis. The reason of the difference between two results comes from Word2Vec's semantic features vectorization. Therefore, it is possible to say that Word2Vec algorithm is able to catch the hidden related words which have not been found in traditional analysis. In addition, Part Of Speech (POS) tagging for Korean is used to detect adjective as "emotional word" in Korean. In addition, the emotion words extracted from the text are converted into word vector by the Word2Vec algorithm to find related words. Among these related words, noun words are selected because each word of them would have causal relationship with "emotional word" in the sentence. The process of extracting these trigger factor of emotional word is named "Emotion Trigger" in this study. As a case study, the datasets used in the study are collected by searching using three keywords: professor, prosecutor, and doctor in that these keywords contain rich public emotion and opinion. Advanced data collecting was conducted to select secondary keywords for data gathering. The secondary keywords for each keyword used to gather the data to be used in actual analysis are followed: Professor (sexual assault, misappropriation of research money, recruitment irregularities, polifessor), Doctor (Shin hae-chul sky hospital, drinking and plastic surgery, rebate) Prosecutor (lewd behavior, sponsor). The size of the text data is about to 100,000(Professor: 25720, Doctor: 35110, Prosecutor: 43225) and the data are gathered from news, blog, and twitter to reflect various level of public emotion into text data analysis. As a visualization method, Gephi (http://gephi.github.io) was used and every program used in text processing and analysis are java coding. The contributions of this study are as follows: First, different approaches for sentiment analysis are integrated to overcome the limitations of existing approaches. Secondly, finding Emotion Trigger can detect the hidden connections to public emotion which existing method cannot detect. Finally, the approach used in this study could be generalized regardless of types of text data. The limitation of this study is that it is hard to say the word extracted by Emotion Trigger processing has significantly causal relationship with emotional word in a sentence. The future study will be conducted to clarify the causal relationship between emotional words and the words extracted by Emotion Trigger by comparing with the relationships manually tagged. Furthermore, the text data used in Emotion Trigger are twitter, so the data have a number of distinct features which we did not deal with in this study. These features will be considered in further study.