• The Journal of Korean Association of Computer Education
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• v.10 no.4
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• pp.125-133
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• 2007

Many researches have tried to introduce affective computing for Human-Computer Interaction (HCI). In the affective aspect, emotional memories significantly affect on people's cognitive processing activities. In this paper, to observe the effect of affective feedback for emotional state of learners in an e-learning environment, selected emotional feedback messages and delivery method are integrated into an e-learning system. Self reporting button for recognizing learner's emotional state are used for detecting learner's emotional states and the test results show that providing affective feedback to learner has positive effects in e-learning environment in terms of learner's academic achievements.

• Journal of the Korea Computer Graphics Society
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• v.24 no.4
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• pp.1-9
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• 2018

We propose an emotional training framework that can determine the initial symptom of schizophrenia by using emotional analysis method through facial expression change. We use Emotion API in Microsoft to obtain facial expressions and emotion values at the present time. We analyzed these values and recognized subtle facial expressions that change with time. The emotion states were classified according to the peak analysis-based variance method in order to measure the emotions appearing in facial expressions according to time. The proposed method analyzes the lack of emotional recognition and expressive ability by using characteristics that are different from the emotional state changes classified according to the six basic emotions proposed by Ekman. As a result, the analyzed values are integrated into the image color transfer framework so that users can easily recognize and train their own emotional changes.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.8
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• pp.1503-1510
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• 2016

In this study, we implemented the emotional light controlling system by using the wheel interface built in the smart-watch devices. Most previous light controlling systems have been adopted the direct switches or smart-phone applications for presenting individual emotion in lighting systems. However, in order to control color properties, these studies have some complicated user-interfaces in systems and limitation to present various color spectrums. Therefore, we need to user-friendly interfaces and functions for controlling properties of the lightning systems such as color, tone, color temperature, brightness, and saturation in detail with the wheel interface built in the smart-watch devices. The system proposed in the study is given to choose the user's selecting the emotional status information for providing the emotional lights. The selectable emotional status such as "stable", "surprise", "tired", "angry", etc. can be among 11 kinds of emotional states. In addition, the designed system processed the user's information such as user's emotional status information, local time, location information.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.11a
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• pp.179-184
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• 2005

Recently, studying on modeling the emotion of a robot has become issued among fields of a humanoid robot and an interaction of human and robot. Especially, modeling of the motivation, the emotion, the behavior, and so on, in the robot, is hard and need to make efforts to use our originality. In this paper, new modeling using mathematical formulations to represent the emotion and the behavior selection is proposed for the software robot with virtual sensor modules. Various Points which affect six emotional states such as happy or sad are formulated as simple exponential equations with various parameters. There are several experiments with seven external sensor inputs from virtual environment and human to evaluate this modeling.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.10
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• pp.1364-1369
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• 2018

Speech emotion recognition, which aims to classify speaker's emotional states through speech signals, is one of the essential tasks for making Human-machine interaction (HMI) more natural and realistic. Voice expressions are one of the main information channels in interpersonal communication. However, existing speech emotion recognition technology has not achieved satisfactory performances, probably because of the lack of effective emotion-related features. This paper provides a survey on various features used for speech emotional recognition and discusses which features or which combinations of the features are valuable and meaningful for the emotional recognition classification. The main aim of this paper is to discuss and compare various approaches used for feature extraction and to propose a basis for extracting useful features in order to improve SER performance.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.1
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• pp.37-42
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• 2006

Recently, studying on modeling the emotion of a robot has become issued among fields of a humanoid robot and an interaction of human and robot. Especially, modeling of the motivation, the emotion, the behavior. and so on, in the robot, is hard and need to make efforts to use ow originality. In this paper, new modeling using mathematical formulations to represent the emotion and the behavior selection is proposed for the software robot with virtual sensor modules. Various points which affect six emotional states such as happy or sad are formulated as simple exponential equations with various parameters. There are several experiments with seven external sensor inputs from virtual environment and human to evaluate this modeling.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.4
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• pp.304-309
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• 2000

For understanding the information processing in human brain, we analyze the EEG, a spontaneous electric activity on the scalp of the human. In this paper, we used the mutual information to analyze EEG. The mutual information is used to show the stochastic correlation between signals which are generated in the communication and information theory. The used EEG is evoked by each auditory stimulus in positive and negative emotional states. As a result, we found thet there is some difference at the mutual information in each emotional state.

• Korean Journal of Child Studies
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• v.29 no.1
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• pp.257-273
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• 2008

This study examined the development of children's theory of mind by types of false-belief tasks and various mental states. Seventy six 3-, 4-, 5- and 6-year olds were asked to infer others' minds or choose other's behaviors. Ten tasks, including two picture book tasks, were used to tap the children's understanding of various mental states. Results showed that children did well in their understanding of diverse perception and desire, but they did poorly in emotional inference based on false-belief, and second order false-belief. Children performed better in picture book tasks than in classical tasks for the understanding of false-belief and false-belief based emotion.

• Korean Journal of Child Studies
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• v.17 no.1
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• pp.137-152
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• 1996

The goal of this study was to investigate how daily experiences of schoolwork and leisure activities explained cultural differences in levels of adolescent depression. A combined sample of 58 high school seniors in Korea and 62 high school seniors in the United States reported time use patterns and affect states in daily activities and levels of depression. The time use pattern in daily independent study during class hours and in active leisure activities significantly explained cultural differences in levels of depression. Affect states in all schoolwork activities and passive leisure activities also significantly explained cultural differences in levels of depression. These findings suggest that Korean adolescents' experience of 'exam hell', particularly the lack of active leisure activities and more negative emotional experiences of daily activities are partly responsible for their higher depression relative to American counterparts.

• Proceedings of the ESK Conference
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• 1997.04a
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• pp.165-175
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• 1997

Brain potential is described by using Euler Lagrange equation derived from Lagrangian based on SMNI(Statistical Mechanics of Neocortical Interaction). It is assumed that excitatory neuron firing is amplitude-modulated dominantly by the sum of two modes of frequency ${\omega}and 2 {\omega}$ . Time series of this neuron firing is numerically calculated. $I_{L}$related to low frequency distribution of power spectrum, $I_{H}$high frequency, and S(standard deviation) are introduced for the effective extraction of the dynamic property in this simulated brain potential. $I_{L}$,$I_{H}$, and S are obtained from EEG of 4 persons in rest state and are compared with thoretical results. It is of importance in various fields related to human well-being such as comfort-pursued industrial design, psychology, medicine to characterize human emotional states by EEG analysis. The pleasant and unpleasant sensation among various emotional states would be demonstrated to be determined in terms of ${\epsilon}$ and ${\gamma}$ parameters estimated by the simulated $I_{L}$-$I_{H}$-S relations.