• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1538-1544
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• 2021

This study aims to analyze through empirical experiments for the effects of a 360 degree's VR travel contents on stress in the era of COVID-19, as stress has emerged as social problems due to restrictions on freedom of movement. For the empirical experiment, the hypothesis (Happiness level or Depression level or Arousal level will affect the level of stress after watching VR travel contents) was established. As a result, the depression level was adopted while the others were rejected. In order to relieve stress, it is necessary to be careful not to feel depressed, and it was found that even if we can't travel freely, we can reduce stress somewhat with VR travel contents in the untact era. In other words, the emotional state after watching VR travel contents has changed positively. It is hoped that the results of this study will be of some help to the tourism industry and VR production industry, which have been contracted.

• 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 the Korea Institute of Information and Communication Engineering
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• v.26 no.2
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• pp.306-312
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• 2022

During the unprecedented COVID-19 outbreak, the public's information needs created an environment where they overwhelmingly consume information on the chronic disease. Given that news media affect the public's emotional well-being, the pandemic situation highlights the importance of paying particular attention to how news stories frame their coverage. In this study, COVID-19 news speech emotion from mainstream broadcasters in South Korea and the United States (US) were analyzed using convolutional neural networks. Results showed that neutrality was detected across broadcasters. However, emotions such as sadness and anger were also detected. This was evident in Korean broadcasters, whereas those emotions were not detected in the US broadcasters. This is the first quantitative vocal emotion analysis of COVID-19 news speech. Overall, our findings provide new insight into news emotion analysis and have broad implications for better understanding of the COVID-19 pandemic.

• Journal of the Korea Convergence Society
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• v.13 no.5
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• pp.463-471
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• 2022

Purposes of this study were to identify the factors associated with behavioral Intention to social distancing (BItSD) in a loss versus gain advertising context. This study is a secondary analysis of data surveyed after randomly allocating one of the loss and gain message framing advertisements for the prevention of coronavirus disease-2019 (COVID-19) infection to 379 adults aged 19 and over living in Korea in early March 2021. Attitude toward advertisement (𝛽=.03, p<.001), involvement in COVID-19 (𝛽=.14, p=.006) and emotional stigma (𝛽=-0.17, p<.001) were associated with BItSD, and the explanatory power of these variables was 19% (Adjusted R²=.19). Therefore, when health care professionals communicate with the public, they should develop the strategies to increase public people's involvement in the information and to induce positive advertising attitudes, and provide the effective messages to prevent stigma by accurate information.

• Journal of the Korea Society of Computer and Information
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• v.28 no.3
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• pp.35-43
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• 2023

Emotion recognition while driving is an essential task to prevent accidents. Furthermore, in the era of autonomous driving, automobiles are the subject of mobility, requiring more emotional communication with drivers, and the emotion recognition market is gradually spreading. Accordingly, in this research plan, the driver's emotions are classified into seven categories using psychological and behavioral data, which are relatively easy to collect. The latent vectors extracted through the auto-encoder model were also used as features in this classification model, confirming that this affected performance improvement. Furthermore, it also confirmed that the performance was improved when using the framework presented in this paper compared to when the existing EEG data were included. Finally, 81% of the driver's emotion classification accuracy and 80% of F1-Score were achieved only through psychological, personal information, and behavioral data.

• The Korean Journal of Coaching Psychology
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• v.6 no.1
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• pp.1-32
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• 2022

The purpose of this study is to verify the effectiveness of developing and applying a strength-based art coaching program to improve psychological and social maturity for slow learners attending elementary school. To this end, 32 slow elementary school learners living in the Seoul area were selected to form 16 experimental groups and 16 control groups. A total of 10 session of strength-based art coaching programs were conducted once a week for 60 minutes for 16 experimental groups. The main contents of the program consisted of recognizing positive psychological strengths and utilizing strengths in daily life, recognizing and empathizing with my emotions and other people's feelings, and learning and expressing specific ways of expressing my thoughts. To verify the effectiveness of the program, psychological and social maturity tests (emotional stability, social competence, communication skills, school life adaptation, interpersonal friendliness) were conducted in advance, post, 4 weeks later, and 2 weeks later. The implications of the study through the results of this study, limitations of the study, and suggestions for future research were discussed.

• Journal of Korean Society of Rural Planning
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• v.28 no.3
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• pp.13-23
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• 2022

The purpose of this study was to identify the effects experienced by cancer survivors through the forest therapy, and to provide evidence for applying the forest therapy program. Nineteen cancer survivors who participated in the forest therapy program hosted by K University were targeted, and qualitative data were collected through three focus group interviews. All interviews were recorded and transcribed and analyzed by subject-specific content analysis method. According to the research results, the attributes of forest therapy experienced by cancer survivors were 'Escape from bondage', 'Time to empty and fill the mind', 'Healing from positive forest stimulation', 'Self met in a space of rest', 'Initiative for life'. Five themes and fifteen sub-themes of 'recovery' were derived. These research results revealed a healing experience of feeling comfortable and physically relaxed through communication with the forest, discovering the self, and regaining initiative in life. It can be seen that the forest therapy is helpful in overcoming the physical, emotional, and psycho-social discomforts of cancer survivors.

• Journal of The Korean Society of Integrative Medicine
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• v.10 no.3
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• pp.209-219
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• 2022

Purpose : The purpose of this study was two-fold: to investigate the effects of uncertainty and depression on the quality of life (QoL) of elderly people with chronic diseases and to provide basic data on the physical, emotional, and psychological factors affecting their QoL in the field of physical therapy. Methods : A questionnaire covering uncertainty, depression, and QoL was distributed among 320 elderly people. Pearson's correlation analysis was performed to examine the correlation between uncertainty (ambiguity, complexity, inconsistency, and unpredictability), depression, and QoL (physical, psychological, social, and living environment domains) of the respondents; furthermore, multiple regression analysis was performed to identify the factors affecting the QoL of the respondents with a chronic disease. Results : The sub-factors of uncertainty and QoL-"complexity and social domain" (r=-.295, p<.001), "complexity and living environment domain" (r=-.302, p<.001), and "inconsistency and living environment domain" (r=-.360, p<.001)-showed a negative (-) correlation, as did depression and the sub-factors of QoL-"depression and physical domain" (r=-.782, p<.001), "depression and psychological domain" (r=-.876, p<.001), "depression and social domain" (r=-.668, p<.001), and "depression and living environment domain" (r=-.731, p<.001). The factors affecting QoL were complexity (𝛽=-.122, p<.001), inconsistency (𝛽=-.102, p=.002), unpredictability (𝛽=.112, p<.001), and depression (𝛽=-.850, p<.001). The relative influence of the independent variables was in the order of depression, complexity, unpredictability, and inconsistency, and the explanatory power was 77.1 % (F=215.853, p<.001). Conclusion : It is important to help the elderly with chronic diseases reduce the negative impact on their quality of life by helping them gain support from their families and medical professionals and by increasing their understanding through communication so that they can transition from negative emotions to positive emotions of opportunity.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.11
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• pp.1571-1576
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• 2022

This study aims to analyze the interest of modern people in non-face-to-face medical counseling in the medical industrys. Big data was collected on two social platforms, 지식인, a platform that allows experts to receive medical counseling, and YouTube. In addition to the top five keywords of telephone counseling, "internal medicine", "general medicine", "department of neurology", "department of mental health", and "pediatrics", a data set was built from each platform with a total of eight search terms: "specialist", "medical counseling", and "health information". Afterwards, pre-processing processes such as morpheme classification, disease extraction, and normalization were performed based on the crawled data. Data was visualized with word clouds, broken line graphs, quarterly graphs, and bar graphs by disease frequency based on word frequency. An emotional classification model was constructed only for YouTube data, and the performance of GRU and BERT-based models was compared.

• Journal of the Korean association of regional geographers
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• v.23 no.3
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• pp.514-528
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• 2017

This study aims at exploring the transnational care for family members back home among the Nepalese marriage immigrant women in Korea on the bases of some transnational care practices like remittances, virtual intimacy through information and communication technologies, visit to Nepal, and invitation of family members to Korea. This study argues that in order to understand migrant women's care practices properly, Nepalese marriage immigrant women should be considered as 'being in-between' the societies and cultures of Nepal and Korea. This study identifies the characteristics of transnational care practices of Nepalese women are closely related to the role expectation for the eldest daughter as well as whether or not migrant women have children, jobs, and original family member in Korea. Furthermore, this study highlights that migrant women's transnational care practices should be considered as 'reciprocal exchange of cares' between marriage women and their family members rather than one-way benefits going to the latter.