• Journal of the Korea Safety Management & Science
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• v.15 no.2
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• pp.121-128
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• 2013

The objectives of this study were to investigate the degrees of emotional labor, the effects to organizational effectiveness and the significant factors influencing organizational effectiveness in radiation therapy professional. The subjects of this study were the radiation therapists working at the hospital in Seoul and Gyungi. The self-reported questionnaires were administered to 205 radiation therapists and the data were analyzed with SPSS 19.0 package. The level of emotional labor of single or female subjects were revealed higher than married or male. The professionalism of job has significant correlation with emotional labor. Significant explanatory variables of the degrees of emotional labor included organization culture, distress and self-leadership. These three variables demonstrated the explanatory power of 13.9% of the emotional labor. Based on the findings, emotional labor of radiation therapist was correlated with occupational professionalism. These results suggest that the intervention program intervening emotional labor should be continued to develop in order to improve the effective self-leadership, organization culture and distress factor.

• Journal of the Korea Society of Computer and Information
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• v.25 no.4
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• pp.133-140
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• 2020

Emotional analysis is an application of opinion mining that analyzes opinions and tendencies of people appearing in unstructured text. Recently, emotional analysis of social media has attracted attention, but social media contains newly-created words and slang, so it is not easy to analyze with existing emotional analysis. In this study, I design a new emotional analysis system to solve these problems. The proposed system is possible to analyze various emotions as well as positive and negative in social media including newly-created words and slang. First, I collect newly-created words and slang related to emotions that appear in social media. Then, expand the existing emotional model and use it to quantify the degree of sentiment in emotional words. Also, a new sentiment dictionary is constructed by reflecting the degree of sentiment. Finally, I design an emotional analysis system that applies an sentiment dictionary that includes newly-created words and an extended emotional model.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.4
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• pp.83-88
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• 2013

Many studies adopting brain functions to the engineering systems have been made for recent years as the brain Science has developed. If we investigate the parts which take part in memorizing and emotional process, we can know that Hippocampus of memorizing center and Amygdala of Emotional center closely cooperate each other. Actually Knowledge effects on Emotion and Emotion effects on Knowledge. During the human decision making, emotional factor has much important effects on Decision making process. For implementing more delicate intelligent system, the knowledge base coupled to emotional factor should be designed. Accordingly in this paper starting from the idea of cooperating system between Hippocampus and Amygdala,, we design Knowledge Emotion Binding System and propose Emotional changing mechanism by Memory retrieval and knowledge reasoning process.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.2
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• pp.181-187
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• 2015

In this study, an LED emotional lighting algorithm optimized to the situation was implemented using fuzzy inference for users in exercise and resting situations in indoor environment. The fuzzy theory was used instead of the conventional simple color temperature control in order to control the colors and color temperatures of LED light sources in line with user environment under complex conditions. An LED emotional lighting system based on fuzzy theory was designed through a combination of colors according to the color and temperature of emotional language based on the user behavior. As a result, the color and color temperature can give a good effect on user's emotions for an emotional lighting that is effective for resting and exercise.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.12
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• pp.497-507
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• 2021

The objective of the current research study is to examine those elements/factors that can reduce silence so that organizations can become more efficient, innovative, and adaptable by sharing knowledge and work-related problems. The purpose behind conducting this research was to explore the effects of emotional intelligence on silent behavior. The study also focuses on other individual negative aspects that can increase counterproductive behavior like silence and examines the effects of emotional intelligence on silence through moral disengagement. Data was collected from 400 employees using stratified sampling to ensure adequate representation of males and females. Data was collected from nurses and young doctors using the adopted measurement scale through a self-administered questionnaire. Since the sample included nursing staff and they usually are not well versed in English, the instrument was translated into Urdu. Data were analyzed using SEM to assess the direct and indirect effects of EI on employee silence. The result indicates that emotional intelligence has a positive impact on employee silence and moral disengagement. In contradiction to theory, the findings suggest that people with high emotional intelligence tend to get morally disengaged. As a result, they will remain silent and withhold information regarding work-related issues and problems.

• Journal of Sensor Science and Technology
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• v.30 no.6
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• pp.429-435
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• 2021

In this study, the creation of emotional dialogue was investigated within the process of developing a robot's natural language understanding and emotional dialogue processing. Unlike an English-based dataset, which is the mainstay of natural language processing, the Korean-based dataset has several shortcomings. Therefore, in a situation where the Korean language base is insufficient, the Korean dataset should be dealt with in detail, and in particular, the unique characteristics of the language should be considered. Hence, the first step is to base this study on a specific Korean dataset consisting of conversations on emotional topics. Subsequently, a model was built that learns to extract the continuous dialogue features from a pre-trained language model to generate sentences while maintaining the context of the dialogue. To validate the model, a chatbot system was implemented and meaningful results were obtained by collecting the external subjects and conducting experiments. As a result, the proposed model was influenced by the dataset in which the conversation topic was consultation, to facilitate free and emotional communication with users as if they were consulting with a chatbot. The results were analyzed to identify and explain the advantages and disadvantages of the current model. Finally, as a necessary element to reach the aforementioned ultimate research goal, a discussion is presented on the areas for future studies.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.1
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• pp.51-58
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• 2022

Various studies have been conducted from the past to the present because stock price forecasts provide stability in the national economy and huge profits to investors. Recently, there have been many studies that suggest stock price prediction models using various input data such as macroeconomic indicators and emotional analysis. However, since each study was conducted individually, it is difficult to objectively compare each method, and studies on their impact on stock price prediction are still insufficient. In this paper, the effect of input data currently mainly used on the stock price is evaluated through the predicted value of the deep learning model and the error rate of the actual stock price. In addition, unlike most papers in emotional analysis, emotional analysis using the news body was conducted, and a method of supplementing the results of each emotional analysis is proposed through three emotional analysis models. Through experiments predicting Microsoft's revised closing price, the results of emotional analysis were found to be the most important factor in stock price prediction. Especially, when all of input data is used, error rate of ensembled sentiment analysis model is reduced by 58% compared to the baseline.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.613-617
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• 2021

According to the growth of the service industry, stresses from emotional labor workers have been emerging as a social problem, thereby so-called the Emotional Labor Protection Act was implemented in 2018. However, insufficient substantial protection systems for emotional workers emphasizes the necessity of a digital stress management system. Thus, in this paper, we suggest a stress detection system for customer service representatives based on deep learning facial expression recognition. This system consists of a real-time face detection module, an emotion classification FER module that deep-learned big data including Korean emotion images, and a monitoring module that only visualizes stress levels. We designed the system to aim to monitor stress and prevent mental illness in emotional workers.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.594-595
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• 2022

In the process leading to the continuous use of mobile payment system users, emotional and cognitive reactions are carried out. In this study, a questionnaire was conducted to determine the effect of external factors(social, system, service factors) of the mobile payment system on the continuous use of emotional responses(pleasure, emotional trust) and cognitive responses(cognitive trust). The structural model was tested using SPSS and PLS. As a result of the analysis, it was found that external factors affect emotional and cognitive responses, and cognitive responses affect continuous use.

• Journal of the Ergonomics Society of Korea
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• v.35 no.6
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• pp.535-550
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• 2016

Objective: To enhance user experience of the product by using "wow" materials and parts, a framework for participatory emotional design and evaluation was proposed and validated through a case study in this paper. Background: Customers in recent days value a product which provides new feeling and images they want to get while interacting with it beyond its function, quality, and usability. Since the product consists of various parts and materials, "wow" materials and parts which can affect the customer's feeling and emotions are the essential components for changing the user experience. Method: A framework for participatory and human sensibility ergonomic design was considered and applied on developing the aesthetically and emotionally affecting glass panels of changing colors. Design experts defined a target market for this multicolor glass panels and modified the existing designing goal. Constraints for this design modification were identified by market trend research and consulting with the company which owns the technology for checking out its feasibility. The company developed and provided prototype samples as well as their competing materials. Quantitative and qualitative evaluation of the emotional quality was conducted to validate whether the design goal was achieved successfully. Results: The target market for the developing materials was defined as finishing for the buildings. The designing goal was set as to feed new visual sensation of clean and colorful images. The emotional quality of two different types of multicolor glass panels and an ordinary unicolor panel were evaluated quantitatively with semantic differential method. Results showed that the emotion of the subjects for the multicolor glass panels can be abstracted into two dimensions; named 'colorfulness' and 'harmony'. It was found that the developed samples got higher scores in emotional quality for both dimensions compared to the ordinary one. Age was found to be a significant factor for evaluating the emotional quality of colorfulness. Conclusion and Applications: The proposed framework is a valid approach for enhancing the user experience of the product by participatory design of emotional materials and parts. This framework can be applied easily on the emotional design and evaluation of different materials and components.