• The Journal of Economics, Marketing and Management
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• v.7 no.1
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• pp.26-38
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• 2019

Purpose - This paper is to review recent literature, by conducting a thorough investigation of the limitations and implications for future research on work-life balance with the focus and linkages between work-life balance practices, machine learning and emotional intelligence, work-life conflict, the correlations between work-life enrichment and work-life balance practices, the relationships between employee job satisfaction and work-life balance, the links between work-life balance and the managerial support. Research design, data, and methodology - The paper will further detail linkages between work-life balance and organizational performance outcomes productivity and innovation. Previous literatures have paid attentions to the link of HR practices and organizational outcomes such as productivity, flexibility, and financial performance, but the understanding needs to be extended to involve innovation performance. Dealing with employees' emotions using different machine learning techniques is one of the phenomenal researches in today's world. Here, we examine how far the employees are conscious of their own self and found the ideas and views of an individual about themselves and others. Without proper knowledge about their personality it will be very difficult for an individual to manage their own emotions. This study also aims at finding out the individual abilities to manage their emotions in order to perform well. Conclusions - A theoretical conceptual framework has been built by integrating the existing literature to explain a number of factors which are closely associated with work-life balance. The conceptual model illustrates how the work-life balance interplays with performance and interrelates with the aforementioned factors.

• Journal of Korea Multimedia Society
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• v.23 no.6
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• pp.765-771
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• 2020

To enable AI(artificial intelligence) to realize visual emotions, it attempts to create music centered on color, an element that causes emotions in paintings. Traditional image-based music production studies have a limitation in playing notes that are unrelated to the picture because of the absence of musical elements. In this paper, we propose a new algorithm to set the group of music through the average color of the picture, and to produce music after adding diatonic code progression and deleting sound using median value. And the results obtained through the proposed algorithm were analyzed.

• Journal of Digital Convergence
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• v.20 no.1
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• pp.141-153
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• 2022

This study tried to understand the structural relationship of consumer characteristics on consumer emotions and satisfaction in online shopping. First, consumer characteristics derived various tendencies through previous studies. Next, consumer emotion was defined as positive and negative emotions in the six purchasing processes from information search to use, and satisfaction was defined as the overall satisfaction of the purchasing experience. To this end, this study measured consumer satisfaction and positive/negative emotions in the six consumption processes in their 20s and 40s with online clothing shopping experience within the last month. Finally, structural equation modeling(SEM) was conducted. As a result, the model fit was good, and impulse purchase tendency, conspicuous consumption tendency, innovation tendency, and trendy shopping tendency only affected negative emotions. On the other hand, it was confirmed that information search tendency, hedonic shopping tendency, and economic shopping tendency directly affect positive emotions and indirectly affect consumer satisfaction. Through this, implications for improving the consumer experience in online shopping were presented by identifying consumer characteristics and enhancing consumer emotions.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.5
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• pp.23-28
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• 2022

Today, the online market has grown rapidly due to the development of digital platforms and the pandemic situation. Therefore, unlike the existing offline market, the distinctiveness of the online market has prompted users to check online reviews. It has been established that reviews play a significant part in influencing the user's purchase intention through precedents of several studies. However, the current review writing method makes it difficult for other users to understand the writer's emotions by expressing them through elements like tone and words. If the writer also wanted to emphasize something, it was very cumbersome to thicken the parts or change the colors to reflect their emotions. Therefore, in this paper, we propose a technique to check the user's emotions through facial expression recognition using a camera, to automatically set colors for each emotion using research on existing emotions and colors, and give colors based on the user's intention.

• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.223-229
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• 2021

This study starts with the premise that many problematic situations in modern society can seriously damage personal feelings and that this phenomenon can create anxiety in individuals and society. In order to address such anxiety in individuals and society, we would like to propose measures to heal emotions. Accordingly, 270 research trends related to emotions studied from 2005 to 2020 will be analyzed to establish the direction of future research on emotion healing. As a result of analyzing the trends of healing papers, active healing studies have been conducted since 2010, but reading and writing healing through specific academic societies has been the main focus. Theoretical research accounted for a large portion, and emotional research was steadily conducted. Although healing methods are expanding to various topics, they have not been commercialized as specific methods. As a result, we hope that concrete research to heal individual emotions will be expanded and measures to implement a stable future society will be proposed.

• Journal of the Korea Convergence Society
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• v.10 no.5
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• pp.313-321
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• 2019

The purpose of this study was to examine music-color association response(MCAR) of people with visual impairment through music-emotion scale and music-color scale. The study was conducted on 60 participants(30 congenital/ 30 adventitious) who are using services of two welfare centers at S and B cities. For this, four basic emotions (happiness, sadness, anger, and fear) mediated by music were selected, and MCAR to emotion-inducing music were analyzed through self-report method. As a result, first, there were found contrasts in MCAR between happiness and sadness according to type of emotion, however, similar in anger and fear. Second, in MCAR among three variables of the music-emotion scale(valence, arousal and intensity), valence was congruent with MCAR according to type of emotion, arousal marked high scores in negative emotions, and scores of intensity in happiness and sadness were higher than those in anger and fear. Third, there were no significant differences between two groups of people with congenital and adventitious visual impairments. It is meaningful that this study showed the MCAR can be mediated by music through investigating those of people with visual impairment.

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

• Journal of the Korea Convergence Society
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• v.11 no.8
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• pp.297-307
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• 2020

This study aimed to clarify the meanings of developmental rehabilitation service providers' experiences of participation in a group art therapy. The 5 participants in this study were composed of cognitive, language and art therapists working at children developmental rehabilitation center in G city. The group art therapy was provided to participants from October to December, 2018. And the data were collected using in-depth interviews from January to February, 2019. Collected data was analyzed using the phenomenological method by Colaizzi(1978). As a result, four categories were derived: "Purification of emotions", "New discovery", "Encouragement and comfort", and "Close relationship". In conclusion, therapists participating in a group art therapy experienced purification of emotions and newly discovered about themselves and colleagues. And through encouraging and comforting in the group, they became closer. These results may serve as basic data on using art therapy for giving psychological support to therapists who provide developmental rehabilitation service.

• The Journal of the Convergence on Culture Technology
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• v.8 no.2
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• pp.209-215
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• 2022

In this study, detailed factors of public sentiment toward the 'post-corona new normal' were examined through social media big data sentiment analysis. Thus, it is to provide basic data to preemptively cope with the post-COVID-19 era. For data collection and analysis, the emotional analysis program of 'Textom', a big data analysis program, was used. The data collection period is one year from October 5, 2020 to October 5, 2021, and the collection channels are set as blogs, cafes, Twitter, and Facebook on Daum and Naver. The original data edited and refined a total of 3,770 collected texts from this channel were used for this study. The conclusion is as follows. First, there is a high level of interest and liking for the 'post-corona new normal'. In other words, it can be seen that optimism such as daily recovery, technological growth, and expectations for a new future took the lead at 77.62%. Second, negative emotions such as sadness and rejection are 22.38% of the total, but the intensity of emotions is 23.91%, which is higher than the ratio, suggesting that these negative emotions are intense. This study has a contribution to the detailed factor analysis of the public's positive and negative emotions through big data analysis on the 'post-corona new normal'.

• Journal of the Korea Convergence Society
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• v.10 no.3
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• pp.167-176
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• 2019

The conversational agent, which is at the forefront of the 4th industry, aims to personalize the user-centered focus in the future and holds an important position to have a hub that can be connected to various IoT devices. It is a challenge for interactive agents to recognize the user's emotions and provide the correct interaction to personalization. The study first I looked at emotional definitions and scientific and engineering approaches. Then I recognized through social perspectives what social function and what factors emotions have and how they can be used to understand emotions. Based on this, I explored how users can be discovered emotional social factors in communication. This research has shown that social factors can be found in the user's speech, which can be linked to the social meaning of emotions. Finally, I propose a model to discover social factors in user communication. I hope that this will help designer and researcher to study user-centered design and interaction in designing interactive agents.