• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.3
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• pp.333-340
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• 2022

The COVID-19 has made everyone anxious and people need to keep their distance. It is necessary to conduct collective assessment and screening of college students' mental health in the opening season of every year. This study uses and trains a multi-layer perceptron neural network model for deep learning to identify facial emotions. After the training, real pictures and videos were input for face detection. After detecting the positions of faces in the samples, emotions were classified, and the predicted emotional results of the samples were sent back and displayed on the pictures. The results show that the accuracy is 93.2% in the test set and 95.57% in practice. The recognition rate of Anger is 95%, Disgust is 97%, Happiness is 96%, Fear is 96%, Sadness is 97%, Surprise is 95%, Neutral is 93%, such efficient emotion recognition can provide objective data support for capturing negative. Deep learning emotion recognition system can cooperate with traditional psychological activities to provide more dimensions of psychological indicators for health.

• Journal of Broadcast Engineering
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• v.27 no.5
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• pp.738-750
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• 2022

In this study, we reviewed and discussed whether auditory stimuli with short length can evoke emotion-related neurological responses. The findings implicate that if personalized sound tracks are provided to XR users based on machine learning or probability network models, user experiences in XR environment can be enhanced. We also investigated that the arousal-relaxed factor evoked by short auditory sound can make distinct patterns in functional connectivity characterized from background EEG signals. We found that coherence in the right hemisphere increases in sound-evoked arousal state, and vice versa in relaxed state. Our findings can be practically utilized in developing XR sound bio-feedback system which can provide preference sound to users for highly immersive XR experiences.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.3
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• pp.45-50
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• 2023

As the ownership of pets has steadily increased in recent years, the need for an effective pet management system has grown. In this study, we propose a pet management system with a deep learning-based emotion recognition SNS. The system detects emotions through pet facial expressions using a convolutional neural network (CNN) and shares them with a user community through SNS. Through SNS, pet owners can connect with other users, share their experiences, and receive support and advice for pet management. Additionally, the system provides comprehensive pet management, including tracking pet health and vaccination and reservation reminders. Furthermore, we added a function to manage and share pet walking records so that pet owners can share their walking experiences with other users. This study demonstrates the potential of utilizing AI technology to improve pet management systems and enhance the well-being of pets and their owners.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.7
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• pp.341-350
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• 2018

The purpose of this study was to develop science essay writing activities for developing elementary pre-service teacher's scientific thinking ability and scientific emotion and to analyze its effects. For the study, 60 first grade students attending teacher training institutes in the G region of Korea were selected. All 60 elementary pre-service teachers were students who selected a liberal arts lecture related to 'science inquiry'. As a result of the study, we confirmed that the preliminary teacher uses the scientific method of 'induction' in the article related to scientific thinking and the description related to the past time, agency, and purpose of the story is included in the essay related to scientific emotion. In addition, it was confirmed that elementary school teachers' writing ability was improved as the writing was repeated, and that the image of 'science' changed positively in many areas. This study suggests that a various and interesting scientific inquiry activities are needed to improve the science writing skills.

• Journal of Internet of Things and Convergence
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• v.9 no.6
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• pp.37-44
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• 2023

As a primary technology of Industry 4.0, human-robot collaboration (HRC) requires additional measures to ensure worker safety. Previous studies on avoiding collisions between collaborative robots and workers mainly detect collisions based on sensors and cameras attached to the robot. This method requires complex algorithms to continuously track robots, people, and objects and has the disadvantage of not being able to respond quickly to changes in the work environment. The present study was conducted to implement a web-based platform that manages collaborative robots by recognizing the emotions of workers - specifically their perception of danger - in the collaborative process. To this end, we developed a web-based application that collects and stores emotion-related brain waves via a wearable device; a deep-learning model that extracts and classifies the characteristics of neutral, positive, and negative emotions; and an Internet-of-things (IoT) interface program that controls motor operation according to classified emotions. We conducted a comparative analysis of our system's performance using a public open dataset and a dataset collected through actual measurement, achieving validation accuracies of 96.8% and 70.7%, respectively.

• Journal of Advanced Technology Convergence
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• v.2 no.4
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• pp.21-30
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• 2023

This paper tried to determine whether emotional dysregulation would function as a mediating variable when social exclusion affects SNS addiction tendencies. For this purpose, a survey was conducted targeting students enrolled in a university located in the central region. Responses from 298 people were analyzed. The analysis results show that social exclusion completely mediates emotional dysregulation and influences SNS addiction tendencies. Meanwhile, we set the two sub-dimensions of social exclusion as independent variables to determine whether it influences SNS addiction tendency through emotion regulation. It was found that the experience of being ignored influenced the tendency to addict to SNS by partially mediating the experience of emotion regulation, while the experience of rejection was found to affect the tendency to addict to SNS by fully mediating the experience of emotion regulation. These analysis results show that when establishing social exclusion as an influential factor in SNS addiction tendency, it is meaningful not only to set it as an overall factor but also to approach it by dividing it into individual factors.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.105-112
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• 2024

In contemporary society, the expression of emotions and self-reflection are considered pivotal factors with a positive impact on stress management and mental well-being, thereby highlighting the significance of journaling. However, traditional journaling methods have posed challenges for many individuals due to constraints in terms of time and space. Recent rapid advancements in chatbot and emotion analysis technologies have garnered significant attention as essential tools to address these issues. This paper introduces an artificial intelligence chatbot that integrates the GPT-3 model and emotion analysis technology, detailing the development process of a system that automatically generates journals based on users' chat data. Through this system, users can engage in journaling more conveniently and efficiently, fostering a deeper understanding of their emotions and promoting positive emotional experiences.

• Science of Emotion and Sensibility
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• v.16 no.3
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• pp.363-372
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• 2013

When retrieving music with folksonomy tags, internal use of numeric tags (AV tags: tags consisting of Arousal and Valence values ) instead of word tags can partially solve the problem posed by synonyms. However, the two predecessor tasks should be done correctly; the first task is to map word tags to their numeric tags; the second is to get numeric tags of the music pieces to be retrieved. The first task is verified through our prior study and thus, in this paper, its significance is seen for the second task. To this end, we propose the music mapping table defining the relation between AV values and music and ANOVA tests are performed for analysis. The result shows that the arousal values and valence values of music have different distributions for 12 mood tags with or without synonymy and that their type I error values are P<0.001. Consequently, it is checked that the distribution of AV values is different according to music mood.

• Journal of Broadcast Engineering
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• v.25 no.6
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• pp.973-979
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• 2020

This study aims to objectively and quantitatively determine the social emotion of empathy by collecting pupillary response. 52 subjects (26 men and 26 women) voluntarily participated in the experiment. After the measurement of the reference of 30 seconds, the experiment was divided into the task of imitation and spontaneously self-expression. The two subjects were interacted through facial expressions, and the pupil images were recorded. The pupil data was processed through binarization and circular edge detection algorithm, and outlier detection and removal technique was used to reject eye-blinking. The pupil size according to the empathy was confirmed for statistical significance with test of normality and independent sample t-test. Statistical analysis results, the pupil size was significantly different between empathy (M ± SD = 0.050 ± 1.817)) and non-empathy (M ± SD = 1.659 ± 1.514) condition (t(92) = -4.629, p = 0.000). The rule of empathy according to the pupil size was defined through discriminant analysis, and the rule was verified (Estimation accuracy: 75%) new 12 subjects (6 men and 6 women, mean age ± SD = 22.84 ± 1.57 years). The method proposed in this study is non-contact camera technology and is expected to be utilized in various virtual reality with smart glasses.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.130-133
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• 2003

The robot has recently emerged as a factor in the daily lives of humans, taking the form of a mechanical pet or similar source of entertainment. A robot system that is designed to co-exist with humans, i.e., a coexistence-type robot system, is important to be "it exists in various environments with the person, and robot system by which the interaction of a physical, informational emotion with the person etc. was valued". When studying the impact of intimacy in the human/robot relationship, we have to examine the problems that can arise as a result of physical intimacy(coordination on safety in the hardware side and a soft side). Furthermore, We should also consider the informational aspects of intimacy (recognition technology, and information transport and sharing). This paper reports the interim results of the research of a system configuration that enhances the physical intimacy relationship in the symbiosis of the human and the robot.