• The Journal of the Convergence on Culture Technology
• /
• v.5 no.2
• /
• pp.299-303
• /
• 2019

This study is one of the preparatory tasks for this researcher to do Emotion Coding on AI. This time, we're doing an Emotion Coding for Sijo "Blue Mountain is My Meaning" by Hwang Jin-yi. Huang Jin-yi is doing Emotion Coding on Blue Mountain and Green Stream in this Sijo. These Emotions code, as seen in Emotion Codon, as in UUU. This phenomenon can be described in the form in which this researcher hypothesized. In other words, this Emotion Coding acts as a catalyst for the formation of an amino acid called phenylalanine. If we continue this research, it is thought that the function of literature, which is more healing, will be utilized in the future of mankind.

• Journal of the Ergonomics Society of Korea
• /
• v.31 no.2
• /
• pp.271-279
• /
• 2012

Objective: This study classified three different emotional states(boredom, pain, and surprise) using physiological signals. Background: Emotion recognition studies have tried to recognize human emotion by using physiological signals. It is important for emotion recognition to apply on human-computer interaction system for emotion detection. Method: 122 college students participated in this experiment. Three different emotional stimuli were presented to participants and physiological signals, i.e., EDA(Electrodermal Activity), SKT(Skin Temperature), PPG(Photoplethysmogram), and ECG (Electrocardiogram) were measured for 1 minute as baseline and for 1~1.5 minutes during emotional state. The obtained signals were analyzed for 30 seconds from the baseline and the emotional state and 27 features were extracted from these signals. Statistical analysis for emotion classification were done by DFA(discriminant function analysis) (SPSS 15.0) by using the difference values subtracting baseline values from the emotional state. Results: The result showed that physiological responses during emotional states were significantly differed as compared to during baseline. Also, an accuracy rate of emotion classification was 84.7%. Conclusion: Our study have identified that emotions were classified by various physiological signals. However, future study is needed to obtain additional signals from other modalities such as facial expression, face temperature, or voice to improve classification rate and to examine the stability and reliability of this result compare with accuracy of emotion classification using other algorithms. Application: This could help emotion recognition studies lead to better chance to recognize various human emotions by using physiological signals as well as is able to be applied on human-computer interaction system for emotion recognition. Also, it can be useful in developing an emotion theory, or profiling emotion-specific physiological responses as well as establishing the basis for emotion recognition system in human-computer interaction.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
• /
• 2011.05a
• /
• pp.23-24
• /
• 2011

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.5 no.1
• /
• pp.1-6
• /
• 2005

In this paper, we propose an emotion recognition method using the facial images and speech signals. Six basic emotions including happiness, sadness, anger, surprise, fear and dislike are investigated. Facia] expression recognition is performed by using the multi-resolution analysis based on the discrete wavelet. Here, we obtain the feature vectors through the ICA(Independent Component Analysis). On the other hand, the emotion recognition from the speech signal method has a structure of performing the recognition algorithm independently for each wavelet subband and the final recognition is obtained from the multi-decision making scheme. After merging the facial and speech emotion recognition results, we obtained better performance than previous ones.

• The Journal of the Acoustical Society of Korea
• /
• v.26 no.2E
• /
• pp.56-62
• /
• 2007

This paper presents the automatic music emotion classification on acoustic data. A three-level structure is developed. The low-level extracts the timbre and rhythm features. The middle-level estimates the indication functions that represent the emotion probability of a single analysis unit. The high-level predicts the emotion result based on the indication function values. Experiments are carried out on 695 homogeneous music pieces labeled with four emotions, including pleasant, calm, sad, and excited. Three machine learning methods, GMM, MLP, and SVM, are compared on the high-level. The best result of 90.16% is obtained by MLP method.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2002.11b
• /
• pp.762-766
• /
• 2002

This paper describes the emotion recognition algorithm using HMM(Hidden Markov Model) method. The relation between the mechanic system and the human has just been unilateral so far. This is the why people don't want to get familiar with multi-service robots of today. If the function of the emotion recognition is granted to the robot system, the concept of the mechanic part will be changed a lot. Pitch and Energy extracted from the human speech are good and important factors to classify the each emotion (neutral, happy, sad and angry etc.), which are called prosodic features. HMM is the powerful and effective theory among several methods to construct the statistical model with characteristic vector which is made up with the mixture of prosodic features

• Journal of the Korean Academy of Child and Adolescent Psychiatry
• /
• v.34 no.3
• /
• pp.159-168
• /
• 2023

Objectives: Non-suicidal self-injury (NSSI) has been theoretically, clinically, and empirically associated with emotional dysregulation. NSSI is a means of regulating emotional states, particularly negative emotions. However, empirical studies on this topic are scarce and the literature lacks qualitative research on individuals' perceptions and comprehension of the function of self-injury. Thus, this qualitative study aimed to provide novel insights into the relationship between NSSI and emotional dysregulation in young adults. Methods: Twelve participants (mean age=22.7 years, 9 females and 3 males) from different support groups and a healthcare center participated in semi-structured interviews on NSSI-related emotional processes. Three aspects were investigated: reasons for NSSI, function of NSSI, and emotions. Each interview was voice recorded and typically lasted between 20 and 40 minutes. All responses were analyzed using thematic analysis. Results: Four major themes were identified. The results showed that NSSI had both intrapersonal and interpersonal functions, within which emotional regulation played a significant role. NSSI was also used to regulate positive emotions. The results also showed a sequence of emotions among the participants, going from feeling overwhelmed to feeling relatively calm but guilty. Conclusion: NSSI has several functions for the same individual. Thus, it would be interesting to provide integrative therapy, such as emotion-focused therapy, which focus on improving intrapersonal and interpersonal emotion regulation skills and strategies.

• Korean Journal of Child Studies
• /
• v.37 no.6
• /
• pp.19-33
• /
• 2016

Objective: This study aimed to examine the prospective links among perspective taking, attachment security, and executive function and the mediating role of executive function on the relationship between attachment security and perspective taking. Methods: The participants included 147 preschoolers living in Gyeonggi. The data-analysis methods included descriptive statistics, independent t-tests, one-way ANOVAs, Pearson's correlation analysis, hierarchical multiple regression analysis, and the Sobel test. Results: First, preschoolers' perspective taking was significantly related to attachment security, and executive function. Furthermore, there was a significant association between attachment security and executive function. As expected, the correlations were positive in all cases. Second, the effects of attachment security on intention and emotion perspective takings were fully mediated by executive function when holding children's age and vocabulary constant. However, executive function did not predict thought perspective taking, whereas attachment security did. Conclusion: Given that parent-child attachment security might play an important role in child cognitive and socio-cognitive development, parents' endeavors to enhance the quality of the attachment relationship could be a fruitful path for preschoolers' developing executive capacities and perspective taking.

• Journal of Korean Academy of Nursing
• /
• v.35 no.2
• /
• pp.303-312
• /
• 2005

Purpose: This study was to develop an aromatherapy hand massage program, and to evaluate the effects of lavender aromatherapy on cognitive function, emotion, and aggressive behavior of elderly with dementia of the Alzheimer's type. Method: The Research design was a nonequivalent control group non-synchronized quasiexperimental study. Lavender aromatherapy was administrated to experimental group I for 2 weeks, jojoba oil massage was administrated to experimental group II for 2 weeks, and no treatment was administrated to the control group for 2 weeks. Data was analyzed using the $x^2-test$, ANOVA, repeated measures of ANCOVA and ANCOVA in the SPSS program package. Result: 1. Experimental group I did not show significant differences in cognitive function in relation to the experimental group II and control group. 2. Experimental group I showed significant differences in emotion and aggressive behavior in relation to the experimental group II and control group. Conclusion: A Lavender aromatherapy hand massage program is effective on emotions and aggressive behavior of elderly with dementia of the Alzheimer's type.

• Journal of Engineering Education Research
• /
• v.27 no.1
• /
• pp.50-62
• /
• 2024

This study examined how emotion regulation strategies specifically function in the interpersonal conflict coping strategies of engineering students. For this purpose, a interpersonal conflict coping strategies and emotion regulation strategies scale was used for 548 engineering students. Multiple regression analysis was conducted. Among the emotion regulation strategies, the "return to body" strategy was related to understanding, validation, focusing, and the "stop action" strategy. In particular, the "stop action" strategy was closely related only to the "return to body" strategy. Among interpersonal conflict coping strategies, the dominating strategy used both positive emotion regulation strategies, such as high refocus on planning, and negative emotion regulation strategies, such as other-blame. Additionally, among negative conflict coping strategies, it was confirmed that both aggression and negative emotional expression, which seem to have similar attributes, share a common feature of having high difficulty in emotional clarity. However, in the case of negative emotional expression, it is characterized by a lack of putting into perspective and high other-blame. On the other hand, the agression strategy seemed to have different characteristics, such as high self-blame and low return to body. By investigating the relationship between interpersonal conflict coping strategies and specific emotion regulation strategies, this study provides implications for education and intervention on which specific emotion regulation strategies need to be cultivated for engineering students to improve their interpersonal conflict resolution capabilities.