• Korean Journal of Environment and Ecology
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• v.31 no.6
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• pp.606-614
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• 2017

This study analyzed the effect of forest therapy program on reduction of stress of teachers and their positive and negative emotions based on the survey of 221 teachers who participated in the overnight Happiness School Edu-healing Camp held for teachers by the National Center for Forest Healing. For data analysis, a paired sample t-test was conducted using the SPSS 24.0 program to examine the difference in the stress reaction index of teachers and their positive and negative emotions before and after their participation in the forest therapy program. The results indicated that teachers who participated in the program showed a significant decrease in the stress response index and the values of sub-domain such as physical symptoms, depression symptoms, and anger symptoms. Moreover, all teachers exhibited a significant decrease in stress. This result verifies that the forest therapy program is effective in reducing the stress of teachers and their negative emotions. These results are expected to be used to promote more active forest therapy programs for teachers exposed to a high level of stress.

• Journal of the Korea Convergence Society
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• v.10 no.12
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• pp.101-108
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• 2019

Family tourism has become the mainstream demand of the tourism market, and it is also an effective way to obtain happiness. This paper takes family tourists as the research object, takes the family tourism family affection interaction behavior and the experience value relationship as the link, Empirically tests the family tourism "interaction behavior-social support-experience value" conceptual model and the relationship hypothesis. The results showed that interaction of family affection had a positive and significant effect on the functional, cognitive and emotional experience value of family tourists. Family interaction in family tourism has a significant positive impact on social support. Social support has significant positive effects on functional, cognitive, emotional and overall experiential values. This conclusion expands the theoretical and empirical research on the relationship between interaction behavior and experience value, and provides a basis for understanding the interaction behavior and experience value of family love from the perspective of tourism experience essence.

• Korean Journal of Childcare and Education
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• v.7 no.3
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• pp.21-42
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• 2011

This study examined the effects of social capital, ego-resilience and sociodemographic variables on children's Happiness. The subjects were 426 5th and 6th grade students living in Seoul. Collected data was subjected to descriptive statistical analysis, t-test, and multiple regression analysis. Results were :(a) Happiness index was higher in the fifth grade and the higher the economic level. There were no significant differences in gender. (b) Ego-resilience was deeply related to Children's Happiness.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.6
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• pp.821-827
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• 2009

Human emotion can be reflected by their facial expressions. So, it is one of good ways to understand people's emotions by recognizing their facial expressions. General recognition system of facial expressions had selected interesting points, and then only extracted features without analyzing physical meanings. They takes a long time to find interesting points, and it is hard to estimate accurate positions of these feature points. And in order to implement a recognition system of facial expressions on real-time embedded system, it is needed to simplify the algorithm and reduce the using resources. In this paper, we propose a real-time recognition algorithm of facial expressions that project the grid points on an expression space based on Gabor wavelet feature. Facial expression is simply described by feature vectors on the expression space, and is classified by an neural network with its resources dramatically reduced. The proposed system deals 5 expressions: anger, happiness, neutral, sadness, and surprise. In experiment, average execution time is 10.251 ms and recognition rate is measured as 87~93%.

• Journal of Korea Society of Industrial Information Systems
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• v.12 no.3
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• pp.60-68
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• 2007

In this paper, we propose an automatic facial expressions recognition system to analyze facial expressions (happiness, disgust, surprise and neutral) using tree structures based on heuristic rules. The facial region is first obtained using skin-color model and connected-component analysis (CCs). Thereafter the origins of user's eyes are localized using neural network (NN)-based texture classifier, then the facial features using some heuristics are localized. After detection of facial features, the facial expression recognition are performed using decision tree. To assess the validity of the proposed system, we tested the proposed system using 180 facial image in the MMI, JAFFE, VAK DB. The results show that our system have the accuracy of 93%.

• Journal of Convergence for Information Technology
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• v.11 no.2
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• pp.16-24
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• 2021

This paper introduces a smart aging service that helps the elderly lead a happy old age by actively utilizing IoT and AI technologies for the elderly who are increasing rapidly as they enter the aging society. In particular, we propose a future-oriented, age-friendly well-being support system that breaks away from the existing welfare concept to solve the aging problem but leads to a paradigm shift toward building a vibrant aging society by protecting from emergency and satisfying emotions. By introducing IoT and AI, it judges the life situation and emotional state from the living information of the elderly can respond to emergencies and suggest meetings as a change of mood and give an emotional comfort. Since the proposed system uses artificial intelligence techniques to determine the degree of depression when inputting information such as pulse-rate, dangerous word usage, and external communication, I think it showed the feasibility of the new concept of wellbeing support system that is totally different from conventional wellbeing concept of health-care.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.1
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• pp.11-20
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• 2023

Traditionally, surveys or interview studies have been used to measure satisfaction factors for public services. This method focuses on the simple frequency of civil complaints and does not consider the aggravation of emotions implied in civil complaints. As a result, it is difficult to judge the urgency of civil complaints and the severity of grievances experienced by civil petitioners. This study aims to calculate the negative emotional value of collective complaints by using the happiness score for each word on the Hedonometer. The Anti-Corruption and Civil Rights Commission applied a Hedonometer to the top civil complaint topics and related keyword data by region in 2021 to calculate negative sentiment values by subject of civil complaints, and visualize the distribution by region. Using the negative emotional values derived from the results of this study, the severity of emotions contained in civil complaints can be considered. It is also expected to be helpful in determining the urgency of civil complaints and the severity of grievances experienced by civil petitioners.

• Korean Journal of School Psychology
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• v.18 no.1
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• pp.49-70
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• 2021

The purpose of the study was to examine Korean high school students' experience and perceptions of friendship and to inductively conceptualize friendship. The concept mapping method which is used to quantitatively analyze qualitative data was used to identify and visualize participants' experiences and perceptions of friendship. Through a brainstorming process, 93 statements were generated by boys and 100 statements were generated by girls, each set of which were sorted and categorized to generate concept maps. The final concept maps from both group equally had two dimensions: 'Practical-Conceptual' and 'Behavioral-Emotional'. The number of categories was equal to four, but there were some differences in the specifics of the statements in the category. Boys tended to conceptualize friendship as a source of happiness; a type of informal relationship through which they could share their everyday lives; and provide mutual care and engage in emotional bonding. In addition to those conceptualizations, girls also tended to conceptualize friendship as an affective alliance through which they displayed devotion to each other. Boys regarded the sympathy and bonding found in and the happiness produced by friendship as more important elements, whereas girls regarded the care and support found in and the informal nature of friendship as more important

• Journal of KIISE:Software and Applications
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• v.27 no.8
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• pp.827-833
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• 2000

Facial expression is an effective tool to express human emotion. In this paper, a facial expression analysis method based on the base faces and their blending ratio is proposed. The seven base faces were chosen as axes describing and analyzing arbitrary facial expression. We set up seven facial expressions such as, surprise, fear, anger, disgust, happiness, sadness, and expressionless as base faces. Facial expression was built by fitting generic 3D facial model to facial image. Two comparable methods, Genetic Algorithms and Simulated Annealing were used to search the blending ratio of base faces. The usefulness of the proposed method for facial expression analysis was proved by the facial expression synthesis results.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.11
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• pp.206-216
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• 2013

The emotion plays a critical role in human's daily life including learning, action, decision and communication. In this paper, emotion discrimination classifier is designed to reduce system complexity through reduced selection of dominant features from biosignals. The photoplethysmography(PPG), skin temperature, skin conductance, fontal and parietal electroencephalography(EEG) signals were measured during 4 types of movie watching associated with the induction of neutral, sad, fear joy emotions. The genetic algorithm with support vector machine(SVM) based fitness function was designed to determine dominant features among 24 parameters extracted from measured biosignals. It shows maximum classification accuracy of 96.4%, which is 17% higher than that of SVM alone. The minimum error features selected are the mean and NN50 of heart rate variability from PPG signal, the mean of PPG induced pulse transit time, the mean of skin resistance, and ${\delta}$ and ${\beta}$ frequency band powers of parietal EEG. The combination of parietal EEG, PPG, and skin resistance is recommendable in high accuracy instrumentation, while the combinational use of PPG and skin conductance(79% accuracy) is affordable in simplified instrumentation.