• Journal of The Korean Society of Integrative Medicine
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• v.9 no.2
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• pp.153-164
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• 2021

Purpose : This study aims to assess the impact of the emotional labor on female dental clinic employees' intention to leave, and the moderating effect of internal marketing, reducing the intention to leave and providing basic data for an effective human resources management of dental clinics. Methods : The structured self-administered questionnaires were distributed to dental hygienists, dental assistants and other employees (including administrative staff and dental coordinators, but excluding dentists) working at a dental hospital and at dental clinics in the Busan and Gyeongnam area. This study used SPSS Windows version 18.0 program (Chicago, IL, USA) to perform frequency factor, reliability, correlation, and hierarchical regression analyses were performed using SPSS. Results : First, emotional labor had a positive effect on the intention to leave. Two components of the internal marketing, communication and employee welfare system, had a significant moderating effect on the relationship between employees' emotional labor and their intention to leave, while the education/training component of the internal marketing showed no moderating effect. Conclusion : Enhancement of communication and the employee welfare system will help dental care organizations reduce their employees' emotional labor and hence employees' turnover.

• Journal of information and communication convergence engineering
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• v.21 no.1
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• pp.68-74
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• 2023

This study examines the response of users' feelings from a gender perspective toward interactive video mobile learning (IVML). An IVML prototype was developed for the Android platform allowing users to install and make use of the app for m-learning purposes. This study aims to measure the level of feelings toward the IVML prototype and examine the differences in gender perspectives, identify the most responsive feelings between male, and female users as prominent feelings and measure the correlation between user-friendly feeling traits as an independent variable in accordance with gender attributes. The feelings response could then be extracted from the user experience, user interface, and human-computer interaction based on gender perspectives using the Kansei engineering approach as the measurement method. The statistical results demonstrated the different emotional reactions from a male and female perspective toward the IVML prototype may or may not have a correlation with the user-friendly trait, perhaps having a similar emotional response from one to another.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.6
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• pp.544-550
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• 2015

The opinion mining technique which analogize significant information from SNS message is increasingly important because opinions communicated through SNS are increasing. This paper propose SEIAS(SNS Emotional Information Analysis Strategy) based on opinion mining that analogize emotional information from SNS setting a different weight according to position of antonym and adverb. Firstly, the proposed SEIAS constructs a emotion dictionary for opinion mining analysis, Secondly, it collects SNS data on real time, compare it with emotion dictionary and calculates opinion value of SNS data. Specially, it increases the precision of opinion analysis result compared to the existing SO-PMI because it sets up the different value according to the position of antonym and adverb when it calculates the opinion value of data.

• International Journal of Advanced Culture Technology
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• v.12 no.1
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• pp.1-10
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• 2024

While technologies such as the 4th revolution and artificial intelligence (AI), which create new value through the convergence of intelligent information technology, are becoming hot topics, the beauty industry is rapidly developing and combining information and communication technology to produce beauty items based on smartphones among mobile technologies. As the area of expands, YouTube is forming a network through various means of information. In particular, beauty-related YouTube videos are a field of great interest and popularity among the public. By classifying the makeup characteristics according to the emotional images shown in domestic YouTube videos by emotional image and identifying the characteristics of makeup, the needs for watching YouTube makeup videos are identified. We aim to build trust in the delivery of information about makeup. The emotional images were divided into four types: 'modern', 'natural', 'gorgeous', and cute. Among the domestic makeup YouTubers, Pony, Isabe and Shinnim, Lamuque were selected. By organizing more diverse makeup-related content systematically and creatively, we expect to have a positive influence on k-makeup not only domestically but also overseas. We aim to provide basic data for follow-up research on makeup YouTuber videos in the field of cosmetology and contribute to marketing plans for the development of the beauty content industry and establishment of promotional strategies.

• The Research Journal of the Costume Culture
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• v.23 no.2
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• pp.254-269
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• 2015

The digital technology that has brought about the information revolution acts as the causes of multi-faceted socio-cultural phenomena. The spread of the digital environment and the popularity of the digital devices accelerate the phenomenon or the fusion of culture and technology, and such a phenomenon is no exception in the fashion design. Namely, the combination of fashion design and digital-based technology draws more and more attention; Not only the technology is simply applied to the fashion design, but also it is used as an emotional tool to enhance consumers' satisfaction, while some designs and marketing cases stimulating consumers' emotion are highlighted importantly. This study was aimed at surveying and analyzing the contemporary fashion using the digital technology and thereupon, assessing the characteristics of the emotional representations of technology as well as their aesthetic values. To this end, the theory of 'science of emotion and sensibility' was applied to divide the characteristics of emotional technological expressions in the contemporary fashion into immateriality, non-boundary, multi-media and interaction, while the aesthetic values of the emotional technology immanent in the contemporary fashion were categorized into communication & participation, conceptual configuration, physical expansion and variable movement. This study analyzed uses of technology for human emotion and sensibility shown in not only collections but also communication media and exhibition spaces and thereby, suggested the direction for our fashion industry to fulfill consumers' changing needs and advance further.

• Journal of Convergence for Information Technology
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• v.12 no.3
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• pp.75-84
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• 2022

The purpose of this study was to identify the degree of stress coping method, emotional intelligence, gratitude disposition, and communication competence of nursing college students to identify the factors that influence communication competence. Data were collected by using questionnaires from 159 students who were in 2nd year of the nursing college in G city, from Nov 9 to 11, 2021. Data were analyzed by t-test, ANOVA, Scheffe, Kruskal-Wallis test, Pearson's correlation, and multiple regression. Statistically, communication competence showed a significantly positive correlation with active stress coping method, emotional intelligence and gratitude disposition. Influencing factors on communication competence were emotional intelligence, gratitude disposition, and active stress coping method accounting for 68% of the total change. Based on this results, strategies to increase emotional intelligence, gratitude disposition, and active stress coping method are needed to improve communication skills of nursing students.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.3
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• pp.215-222
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• 2021

As the importance of human-computer interaction (Human Computer Interface) technology grows and research on HCI is progressing, it is inferred about the research emotion inference or the computer reaction according to the user's intention, not the computer reaction by the standard input of the user. Stress is an unavoidable result of modern human civilization, and it is a complex phenomenon, and depending on whether or not there is control, human activity ability can be seriously changed. In this paper, we propose an intelligent emotional recommendation system using music as a way to relieve stress after measuring heart rate variability (HRV) and acceleration photoplethymogram (APG) increased through stress as part of human-computer interaction. The differential evolution algorithm was used to extract reliable data by acquiring and recognizing the user's biometric information, that is, the stress index, and emotional inference was made through the semantic web based on the obtained stress index step by step. In addition, by searching and recommending a music list that matches the stress index and changes in emotion, an emotional recommendation system suitable for the user's biometric information was implemented as an application.

• The Journal of the Acoustical Society of Korea
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• v.21 no.2E
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• pp.98-104
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• 2002

The present study describes a combination method to recognize the human affective states such as anger, happiness, sadness, or surprise. For this, we extracted emotional features from voice signals and facial expressions, and then trained them to recognize emotional states using hidden Markov model (HMM) and neural network (NN). For voices, we used prosodic parameters such as pitch signals, energy, and their derivatives, which were then trained by HMM for recognition. For facial expressions, on the other hands, we used feature parameters extracted from thermal and visible images, and these feature parameters were then trained by NN for recognition. The recognition rates for the combined parameters obtained from voice and facial expressions showed better performance than any of two isolated sets of parameters. The simulation results were also compared with human questionnaire results.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.6
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• pp.711-717
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• 2018

The purpose of this study is to identify the relationship between psychological wellbeing of social welfare facility workers and their organizational commitment. The subjects of this study were 230 social welfare facility workers in OO city, Gyeongsangbuk-do, Korea. Analysis was conducted using the SPSS program, including frequency analysis, reliability analysis and correlation analysis, and regression analysis on the causal relationship between variables. The results of the study showed that the psychological wellbeing of social welfare facility workers had a meaningful effect on their emotional commitment, continuous commitment and normative commitment. These results confirmed that the higher the psychological wellbeing of social welfare facility workers, the higher the sub-factors of organizational commitment, such as emotional, continuous, normative commitment, resulting in positive effects on the achievement of goals and values that are pursued by the welfare facilities. This study aims to become foundational data for the improvement of working conditions to improve psychological wellbeing of social welfare facility workers to increase organizational commitment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.3
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• pp.1076-1094
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• 2022

Technology for emotion recognition is an essential part of human personality analysis. To define human personality characteristics, the existing method used the survey method. However, there are many cases where communication cannot make without considering emotions. Hence, emotional recognition technology is an essential element for communication but has also been adopted in many other fields. A person's emotions are revealed in various ways, typically including facial, speech, and biometric responses. Therefore, various methods can recognize emotions, e.g., images, voice signals, and physiological signals. Physiological signals are measured with biological sensors and analyzed to identify emotions. This study employed two sensor types. First, the existing method, the binary arousal-valence method, was subdivided into four levels to classify emotions in more detail. Then, based on the current techniques classified as High/Low, the model was further subdivided into multi-levels. Finally, signal characteristics were extracted using a 1-D Convolution Neural Network (CNN) and classified sixteen feelings. Although CNN was used to learn images in 2D, sensor data in 1D was used as the input in this paper. Finally, the proposed emotional recognition system was evaluated by measuring actual sensors.