• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.1
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• pp.1-5
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• 2009

This paper suggests to apply mirror-reflected method based 2D emotion recognition database to 3D application. Also, it makes facial expression of fuzzy modeling using probability of emotion. Suggested facial expression function applies fuzzy theory to 3 basic movement for facial expressions. This method applies 3D application to feature vector for emotion recognition from 2D application using mirror-reflected multi-image. Thus, we can have model based on fuzzy nonlinear facial expression of a 2D model for a real model. We use average values about probability of 6 basic expressions such as happy, sad, disgust, angry, surprise and fear. Furthermore, dynimic facial expressions are made via fuzzy modelling. This paper compares and analyzes feature vectors of real model with 3D human-like avatar.

• Nutrition Research and Practice
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• v.10 no.4
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• pp.456-463
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• 2016

BACKGROUND/OBJECTIVES: Setting healthful beverage expectations, making calcium-rich foods and beverages (CRF/B) available, and role modeling are parenting practices promoting calcium intake among early adolescents. This study aimed to evaluate emotion-based messages designed to motivate parents of early adolescents to perform these practices. SUBJECTS/METHODS: Emotion-based messages were developed for each parenting practice and tested in 35 parents from 5 states. Findings were used to modify messages and develop a survey administered via Amazon MechanicalTurk to a convenience sample of Asian (n = 166) and Hispanic (n = 184) parents of children 10-13 years. Main outcome measures were message comprehension, motivation, relevance, acceptability, and novelty. Engagement in the parenting practices was also assessed. RESULTS: Message comprehension was acceptable for the majority of parents. Most also agreed that messages were motivational (setting healthful beverage expectations (69.0%), making CRF/B available (67.4%), and role modeling (80.0%)), relevant and acceptable. About 30-50% indicated they had not seen the information before. Many parents indicated they were already engaging in the practices (> 70%). No racial/ethnic differences were observed for responses to messages or engaging in parenting practices. CONCLUSIONS: Results indicate that emotion-based messages designed to motivate parents to engage in parenting practices that promote calcium intake among early adolescents were motivating, relevant, and acceptable.

• Journal of Internet Computing and Services
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• v.24 no.2
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• pp.11-18
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• 2023

Recently, in the field of Speech Emotion Recognition (SER), many studies have been conducted to improve accuracy using voice features and modeling. In addition to modeling studies to improve the accuracy of existing voice emotion recognition, various studies using voice features are being conducted. This paper, voice files are separated by time interval in a time series method, focusing on the fact that voice emotions are related to time flow. After voice file separation, we propose a model for classifying emotions of speech data by extracting speech features Mel, Chroma, zero-crossing rate (ZCR), root mean square (RMS), and mel-frequency cepstrum coefficients (MFCC) and applying them to a recurrent neural network model used for sequential data processing. As proposed method, voice features were extracted from all files using 'librosa' library and applied to neural network models. The experimental method compared and analyzed the performance of models of recurrent neural network (RNN), long short-term memory (LSTM) and gated recurrent unit (GRU) using the Interactive emotional dyadic motion capture Interactive Emotional Dyadic Motion Capture (IEMOCAP) english dataset.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.1937-1943
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• 2005

The technology of emotion recognition is a crucial factor in day of ubiquitous that it provides various intelligent services for human. This paper intends to make the system which recognizes the human emotions based on 2-dimensional model with two bio signals, GSR and HRV. Since it is too difficult to make model the human's bio system analytically, as a statistical method, Hidden Markov Model(HMM) is used, which uses the transition probability among various states and measurable observation variance. As a result of experiments for each emotion, we can get average recognition rates of 64% for first HMM results and 55% for second HMM results

• Science of Emotion and Sensibility
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• v.2 no.1
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• pp.1-25
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• 1999

The differentiation of emotions by means of psychophysiological measures has been only moderately successful so far. A major reason for this dilemma may be the lack of appropriate neurophysiological modeling for the various autonomic nervous system based measures being used in emotion research. The aim of the present article is to provide such a neurophysiological background for electrodermal activity which has been frequently used as an indicator of emotional processes. First, the literature is reviewd with respect to the usability of electrodermal measures as an indicators of emotion. second, the neurophysilogical sources of electrodermal phenomena in general are described. Electrodermal activity has different origins in the central nervous system, a limbic-hypothalamic source that dominates during negative emotions as opposed to a premotor and basal ganglia source being predominantly active during positive emotions. Panksepp's model of four basic emotive systems is adopted for demonstrating subcortical structures and pathways possibly involved in the elicitation of both kinds of electrodermal activity in comparison with cardiovascular in dicators of emotional processes.

• The Journal of Korea Robotics Society
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• v.8 no.4
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• pp.266-272
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• 2013

Facial feature extraction and tracking are essential steps in human-robot-interaction (HRI) field such as face recognition, gaze estimation, and emotion recognition. Active shape model (ASM) is one of the successful generative models that extract the facial features. However, applying only ASM is not adequate for modeling a face in actual applications, because positions of facial features are unstably extracted due to limitation of the number of iterations in the ASM fitting algorithm. The unaccurate positions of facial features decrease the performance of the emotion recognition. In this paper, we propose real-time facial feature extraction and tracking framework using ASM and LK optical flow for emotion recognition. LK optical flow is desirable to estimate time-varying geometric parameters in sequential face images. In addition, we introduce a straightforward method to avoid tracking failure caused by partial occlusions that can be a serious problem for tracking based algorithm. Emotion recognition experiments with k-NN and SVM classifier shows over 95% classification accuracy for three emotions: "joy", "anger", and "disgust".

• Journal of the Korean Society of Safety
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• v.31 no.6
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• pp.113-120
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• 2016

People use social media platforms such as Twitter to leave traces of their personal thoughts and opinions. In other words, social media platforms retain the emotions of the people as it is, and accurately understanding the emotions of the people through social media will be used as a significant index for disaster management. In this research, emotion type modeling method and emotional quotient quantification method will be proposed to understand the emotions present in social media platforms. Emotion types are primarily analyzed based on 3 major emotions of affirmation, caution, and observation. Then, in order to understand the public's emotional progress according to the progress of disaster or accident and government response in detail, negative emotions are broken down into anxiety, seriousness, sadness, and complaint to enhance the analysis. Ultimately, positive emotions are further broken down into 3 more emotions, and Russell emotion model was used as a reference to develop a model of 8 primary emotions in order to acquire an overall understanding of the public's emotions. Then, the emotional quotient of each emotion was quantified. Based on the results, overall emotional status of the public is monitored, and in the event of a disaster, the public's emotional fluctuation rate could be quantitatively observed.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.129-134
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• 2009

Recently, percentage of people who use SMS service is increasing. However, it is difficult to express own complicated emotion with text and emoticon of exited SMS service. This paper focuses on that point and practical uses character animation to express emotion and nuance correctly, funny. Also this paper suggests emotion based gesture animation generation system that use character's facial expression and gesture to delivery emotion excitably and clearly than only speaking. Michel[1] investigated interview movies of a person whose gesturing style they wish to animate and suggested gesture generation graph for stylized gesture animation. In this paper, we make focus to analyze and abstracted emotional gestures of Disney animation characters and did 3D modeling of these emotional gestures expanding Michel[1]'s research. To express emotion of person, suggests a emotion gesture generation graph that reflects emotion flow graph express emotion flow for probability. We investigated user reaction for research the propriety of suggested system and alternation propriety.

• Journal of the Korea Convergence Society
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• v.12 no.11
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• pp.435-444
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• 2021

The purpose of this study is to suggest enhancing positive emotions by examining the relationship between savoring belief, rumination, and positive emotion for university and graduate students. For this purpose, a questionnaire measuring savoring beliefs, ruminations, and positive emotion was conducted for 235 university and graduate students in Seoul. As a result of the Structural modeling analysis, students' savoring beliefs had a positive effect on positive emotion and negative effect on rumination, and rumination had a negative effect on positive emotion. Rumination showed a partial mediating effect on the relationship between savoring beliefs and positive emotion. The results of this study provide important meaning that the savoring beliefs is a process of exploring the positive emotion because it does not deal with the mechanism of reinforcing positive emotions in detail. That is, it is meaningful in that it confirms the effect of an effective savoring strategy to increase the positive emotion and at the same time reveals the mechanism. Rather than simply focusing on the savoring beliefs, it can be expected that positive emotion will be improved by intervening with rumination.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2000.04a
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• pp.81-85
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• 2000

The present study investigated the processes of selecting and modeling of design variables based on HIEs for developing the evaluational model on the physical suitability of office chairs. Evaluational model can be used for development of the new products or improvement of the old products. For the best utilization of the evaluational model, the process of scrutinizing the variables and the complex interactions among the variables is indispensible. Also, for this, it is necessary to select only the right HIEs which influence the physical suitability of products greatly.The present study suggested analytical processes for making the evaluational model on the physical suitability (Comfortability, Suitability, Stability, Adjustability, Clearance) of office chairs.