• Journal of the Korea Safety Management & Science
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• v.17 no.3
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• pp.247-263
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• 2015

This study seeks to identify effects derived from emotional labor in the distribution industry, and draw ways to systematically manage the employees by exploring effects of the emotion work on performance. For the purpose, literature reviews and empirical experiments were conducted to find out effects of emotional labor and false face acting on emotion work and organizational performance and effects of social support and job autonomy on the relationship between emotion work and organizational performance. To verify the hypothesis, we conducted a hierarchical regression analysis and structural equation model analysis using SPSS 20 and AMOS19. The result of the verification in this study is as follows: First, effects of emotional labor on burnout was found to be statistically significant, second, as for the path-coefficient for "emotional labor ${\rightarrow}$ emotion work" and "emotional labor ${\rightarrow}$ job satisfaction" was not statistically significant, while the path-coefficient for "emotional labor ${\rightarrow}$ service level" was found to be statistically significant. Third, effects of emotion work on job satisfaction was found statistically significant, fourth, emotion work on the service level was found statistically significant, fifth, effects of false face acting on emotion work was found statistically significant, sixth, effects of false face acting on burnout was statistically significant, seventh, moderating were found statistically significant and lastly, moderating effects of the relationship between emotion work from job autonomy and organization performance was not verified in job satisfaction, while emotion work, job autonomy, and interaction variable in service level were statistically significant.

• Journal of the Korea Society of Computer and Information
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• v.28 no.12
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• pp.57-66
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• 2023

In this study, we propose a novel research framework for the recommendation system that can estimate the user's emotional state and reflect it in the recommendation process by applying deep learning techniques and emotion AI (artificial intelligence). To this end, we build an emotion classification model that classifies each of the seven emotions of angry, disgust, fear, happy, sad, surprise, and neutral, respectively, and propose a model that can reflect this result in the recommendation process. However, in the general emotion classification data, the difference in distribution ratio between each label is large, so it may be difficult to expect generalized classification results. In this study, since the number of emotion data such as disgust in emotion image data is often insufficient, correction is made through augmentation. Lastly, we propose a method to reflect the emotion prediction model based on data through image augmentation in the recommendation systems.

• Journal of Distribution Science
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• v.15 no.2
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• pp.101-109
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• 2017

Purpose - Previous studies related to emotional labor of salespeople have mainly focused on identifying the antecedents of emotional exhaustion and turnover intention and exploring the mitigating effects salespeople's motivation on emotional exhaustion and turnover intention. They also demonstrates that there are different roles for moderating in social support, which means mental/physical support related to the job in supervisors, colleagues and organizations. The purpose of this paper is to investigate how service employees' surface acting affect turnover intention through emotional exhaustion. Another important objective of this paper is to investigate whether perceived social support moderates 1) the relationship between surface acting and emotional exhaustion 2) the relationship between emotional exhaustion and turnover intention. Research design, data, and methodology - To test the hypotheses, we collected the data from Korean insurance company sales employees. A total of 235 responses were received, from which 220 usable responses were obtained after list-wise deletion. Working with a sample of 220 responses, structural equation modeling was employed to empirically test research hypotheses(

The relationship between surface acting and emotion exhaustion,

The relationship between emotion exhaustion and turnover intention,

The moderating effect of perceived social support(PSS) on the relationship between surface acting and emotion exhaustion, and

The moderating effect of perceived social support(PSS) on the relationship between emotion exhaustion and turnover intention. SPSS 22.0 and AMOS software were used in these data analysis. Results - The service employees' surface acting was positively related to the emotional exhaustion; in turn, the service employees' feelings on emotional exhaustion are positively related to turnover intention. In addition, Perceived Social Support significantly moderated the relationship between surface acting and emotional exhaustion. However, perceived social support has a non-significant moderating effect on the path from emotional exhaustion to turnover intention. On the basis of these results, the following conclusion can be drawn. First, distribution service companies will be needed the administrative efforts to offer counseling programs and space to provide their members with enough rest in experiencing psychological pain due to the salespeople's surface acting. Also, it is necessary for distribution service companies to identify and share the examples of successfully solving emotional exhaustion caused by salespeople's surface acting.

• Speech Sciences
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• v.12 no.4
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• pp.53-70
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• 2005

A Vowel of speech signals are multicomponent signals composed of AM-FM components whose instantaneous frequency and instantaneous amplitude are time-varying. The changes of emotion states cause the variation of the instantaneous frequencies and the instantaneous amplitudes of AM-FM components. Therefore, it is important to estimate exactly the instantaneous frequencies and the instantaneous amplitudes of AM-FM components for the extraction of key information representing emotion states and changes in speech signals. In tills paper, firstly a method decomposing speech signals into AM - FM components is addressed. Secondly, the fundamental frequency of vowel sound is estimated by the simple method based on the spectrogram. The estimate of the fundamental frequency is used for decomposing speech signals into AM-FM components. Thirdly, an estimation method is suggested for separation of the instantaneous frequencies and the instantaneous amplitudes of the decomposed AM - FM components, based on Hilbert transform and the demodulation property of the extended Fourier transform. The estimates of the instantaneous frequencies and the instantaneous amplitudes can be used for modification of the spectral distribution and smooth connection of two words in the speech synthesis systems based on a corpus.

• Journal of Korea Multimedia Society
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• v.17 no.12
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• pp.1383-1392
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• 2014

In this paper, we proposed a method to automatically determine the optimal radius through multi-scale LBP operation generalizing the size of radius variation and boosting learning in facial emotion recognition. When we looked at the distribution of features vectors, the most common was $LBP_{8.1}$ of 31% and sum of $LBP_{8.1}$ and $LBP_{8.2}$ was 57.5%, $LBP_{8.3}$, $LBP_{8.4}$, and $LBP_{8.5}$ were respectively 18.5%, 12.0%, and 12.0%. It was found that the patterns of relatively greater radius express characteristics of face well. In case of normal and anger, $LBP_{8.1}$ and $LBP_{8.2}$ were mainly distributed. The distribution of $LBP_{8.3}$ is greater than or equal to the that of $LBP_{8.1}$ in laugh and surprise. It was found that the radius greater than 1 or 2 was useful for a specific emotion recognition. The facial expression recognition rate of proposed multi-scale LBP method was 97.5%. This showed the superiority of proposed method and it was confirmed through various experiments.

• Proceedings of the IEEK Conference
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• summer
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• pp.92-96
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• 2004

The researches of the emotions are currently great interest in speech processing as well as in human-machine interaction domain. In the recent years, more and more of researches relating to emotion synthesis or emotion recognition are developed for the different purposes. Each approach uses its methods and its various parameters measured on the speech signal. In this paper, we proposed using a short-time parameter: MFCC coefficients (Mel­Frequency Cepstrum Coefficients) and a simple but efficient classifying method: Vector Quantification (VQ) for speaker-dependent emotion recognition. Many other features: energy, pitch, zero crossing, phonetic rate, LPC... and their derivatives are also tested and combined with MFCC coefficients in order to find the best combination. The other models: GMM and HMM (Discrete and Continuous Hidden Markov Model) are studied as well in the hope that the usage of continuous distribution and the temporal behaviour of this set of features will improve the quality of emotion recognition. The maximum accuracy recognizing five different emotions exceeds $88\%$ by using only MFCC coefficients with VQ model. This is a simple but efficient approach, the result is even much better than those obtained with the same database in human evaluation by listening and judging without returning permission nor comparison between sentences [8]; And this result is positively comparable with the other approaches.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2001.11a
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• pp.216-221
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• 2001

바닥급기 공조시스템은 재실자에게 신선외기를 효과적으로 공급하고 온열환경을 효과적으로 제공하기 위한 새로운 수단으로 시도되고 있다. 그러나 급기구가 인체에 너무 가까이 위치할 경우, 부분적인 열구배에 의한 불쾌감을 유발할 수 있다. 따라서 본 연구에서는 바닥급기 공조시스템이 설치된 공간내의 온도 및 기류분포 등의 온열환경을 측정하였고 적외선 카메라를 이용하여 급기구에 의한 인체 표면 온도를 측정하여 열적 쾌적성에 미치는 영향에 관하여 고찰하였다.

• Science of Emotion and Sensibility
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• v.5 no.3
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• pp.53-59
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• 2002

The surface fibers on the fabric is one of decisive factors which affects human sensory evaluation as well as heat and moisture transfer characteristics. In this study the length and distribution of surface fibers that are extruded from the fabric surface of the wool/wool blend fabrics (14 wool fabrics and 10 wool blend fabrics) and its contribution to subjective sensory evaluation were investigated. In order to quantify the length and distribution of surface fibers, image analysis and wavelet transform technique were introduced. Instant warm-cool feeling of touch, Q$\_$max/, and contact area were also measured and related to the quantified surface fibers. To figure out the effect of surface characteristics on sensory evaluation, human sensory responses to three adjectives which represent surface characteristics and warm-cool feeling of touch were obtained and analyzed. The relationship between the quantified surface fibers assessed by wavelet energy and both warm-cool reeling of touch, Qmax, and human sensory response were discussed.

• Journal of Korea Multimedia Society
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• v.10 no.12
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• pp.1714-1725
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• 2007

This paper describes a top-down behavior planning framework in a simulation game from personality to real life action selection. The combined behavior creating system is formed by five levels of specification, which are personality definition, motivation extraction, emotion generation, decision making and action execution. Along with the data flowing process in our designed framework, NPC selects actions autonomously to adapt to the dynamic environment information resulting from active agents and human players. Furthermore, we illuminate applying Gaussian probabilistic distribution to realize character's behavior changeability like human performance. To elucidate the mechanism of the framework, we situated it in a restaurant simulation game.

• Journal of Convergence for Information Technology
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• v.11 no.11
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• pp.115-124
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• 2021

This research empirically tested the mediating role of customer emotion on the relationship between customer tumbler experience and social legitimacy. For this purpose, data were collected by surveying consumers who use tumblers. Structural equation model analysis was used for hypothesis testing, and the method proosed by Hoyle and Smith was used to additionally test the mediating effect of customer experience and social legitimacy. The empirical analysis results are as follows. First, customer experience has a positive effect on customer emotion and social legitimacy. Second, customer emotion has a positive effect on social legitimacy. This study proposes a exploratory relationship among customer tumbler experience, customer emotion, and social legitimacy and empirically shows that customer experience and customer emotion are identified as antecedents to social legitimacy.