• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.33 no.2
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• pp.156-170
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• 2023

Objectives: This study conducted practical training to improve the proper usage of personal protective equipment(PPE), which greatly impacts workplace safety and health management. Personal protective equipment education was conducted through active participation, without theoretical modules, and aimed to identify the effects of repeated practical education and determine ways to increase participant satisfaction. Methods: Study data were analyzed using the IBM SPSS Statistics ver.29 software. First, participants' general characteristics were analyzed with frequency analysis. Second, the normality and equality of variances (Leven's test) were tested for the dependent variables prior to statistical analyses to determine the use of parametric tests. In general, normality is assumed when the sample size is 30 or more per the central limit theorem (Park et al., 2014). As our sample size of health management workers was 43, normality can be assumed. However, to ensure rigor of the study, we examined skewness and kurtosis. The results confirmed that the data were normally distributed. Third, the effects of repeated PPE training were analyzed using paired t-tests. Fourth, differences in satisfaction with PPE training according to the safety and health job position and safety and health certification were analyzed with t-test and Welch's t-test. For parameters that did not meet the assumption of equal variances, the Welch's t-test was performed. Results: Repeated PPE training improved the educational outcomes, and the improvements were significant in the 1st and 2nd respiratory PPE and safety and hygiene PPE training evaluations (p<.001). In terms of safety and health job position, repeated training led to improvements in educational outcomes, with significant improvements observed among supervisors and specialized health management institution workers in the 1st and 2nd training evaluations (p<.005). In terms of safety certification, repeated training led to improvements in educational outcomes, with significant improvements observed among both certified and non-certified individuals (p<.005). Regarding satisfaction with PPE training according to safety and health job positions, specialized health management institution workers showed greater satisfaction than supervisors, with significant differences in the satisfaction for expertise of lecture, work relevance, and lecturer's attitude (p<.001). Regarding satisfaction with PPE training according to safety and health certification, satisfaction was higher among certified individuals, with significant differences in satisfaction for work relevance and lecture attitude (p<.05) Conclusions: PPE education should be recommended to be provided as practical training. Repeated training can enhance educational outcomes for individuals with inadequate knowledge and understanding of PPE prior to education. For individuals with high levels of pre-existing knowledge and understanding of PPE, the results show that various training experiences should be provided to enhance their satisfaction. Therefore, it suggests that the workplace should actively seek educational media and methods to acquire expertise and skills in wearing personal protective equipment and improve the ability to use

• The Journal of the Convergence on Culture Technology
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• v.9 no.4
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• pp.687-692
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• 2023

We analyze the accuracy of emotion analysis of natural language processing deep learning model and propose to use it for emotional content development. After looking at the outline of the GPT-3 model, about 6,000 pieces of dialogue data provided by Aihub were input to 9 emotion categories: 'joy', 'sadness', 'fear', 'anger', 'disgust', and 'surprise'. ', 'interest', 'boredom', and 'pain'. Performance evaluation was conducted using the evaluation indices of accuracy, precision, recall, and F1-score, which are evaluation methods for natural language processing models. As a result of the emotion analysis, the accuracy was over 91%, and in the case of precision, 'fear' and 'pain' showed low values. In the case of reproducibility, a low value was shown in negative emotions, and in the case of 'disgust' in particular, an error appeared due to the lack of data. In the case of previous studies, emotion analysis was mainly used only for polarity analysis divided into positive, negative, and neutral, and there was a limitation in that it was used only in the feedback stage due to its nature. We expand emotion analysis into 9 categories and suggest its use in the development of emotional content considering it from the planning stage. It is expected that more accurate results can be obtained if emotion analysis is performed by additionally collecting more diverse daily conversations through follow-up research.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.769-777
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• 2023

Globalization has brought about rapid economic, technological, and cultural changes. In order for countries around the world to communicate, recognize and understand globalization, creativity or planning ability can be used to code. In this paper, we would like to present and prove a data analysis that can solve world problems. In the global market, the value of goods or services increases with connectivity. This connection is becoming one of the factors that increase the value of culture. Changes taking this into account promoted cultural spread and innovative growth, and increased productivity and competitiveness in each region of the world. This paper compares the income of the middle class in the United States on the impact of globalization and anti-globalization on cultural spread and innovative growth. Globalization has created an environment in which various elements of K-culture can interact and spread. Through the Internet, social media, and international travel, globalization has had a positive impact on Korea's innovative growth. In areas such as economic activity, technological innovation, and creative industries, globalization has facilitated new tech and approaches, Through this, it changed the existing economic model and contributed to exports K-culture with a new middle class model. However, globalization in the cultural industry can result in the loss of regional characteristics & individuality, which can lead to the middle class cultural unification and alienation(chasm). As a result of the empirical analysis of K-exports for the middle income in the United States, cultural diffusion and innovation must be developed even in anti-globalization. With these industrial changes the soft power value of the Korean Wave proves that it can create value for use for the middle class of major exporting countries.

• Korean Journal of Culture and Social Issue
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• v.9 no.2
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• pp.19-39
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• 2003

The purpose of this study was to investigate the degree of link with internet media and a internet addiction disposition of adolescents. The subjects were 500 students attending to middle and high schools consisted of male and female. The instruments were "the questionnaire on the present conditions of internet use" consisted of 14 items(Cronbach's α=.71) and "the internet addiction rating scale" consisted of 20 items(Cronbach's α=.73). These questionnaire were revised by this researcher. For data analysis, chisqure and ANOVA were used. The main results were as follows. First, a boy students and the vocational high school and the middle school each have more negative response than a girl students and the humanistic high schools in the present conditions of internet use and the judgement on a harmful object of internet space. Second, a boy students have higher than a girl students in an internet addiction disposition. Third, an internet addiction related with the times link with internet, the type of internet game, and the content of internet space(a lustful and violent objects). The various methods for the prevent with the internet addiction of adolescents discussed with based on the previous studies.

• The Journal of the Convergence on Culture Technology
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• v.10 no.2
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• pp.127-131
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• 2024

SW education was conducted for slow youth learners. 6 learners participatd in 8 sessions of an introductory course using several plays and 3 learners who more interested in introductory course participated in deeper course using normal method. After education, we survey and interview from learners, instructors and heads of welfare organizations. Learners showed interest and participated in the fact that they were participating in SW education, which was widely talked about. Learners were found to be more satisfied with introductory course education using play such as board games, and although they initially appeared to participate in unfamiliar learning content with low efficacy, it was observed that their efficacy increased with repetition. Additionally, it was observed that young people with an IQ of 80 or higher had a higher level of interest or interest in SW education than those with an IQ of 80 or lower. we discussed that there were not many opportunities to directly use the SW education content for youth who are slow learners in work or real life. We suggest this should be a focus education on the use of digital media - online meeting apps, office SW etc.- to improve digital literacy for life and work and that research on this should continue.

• Korean Journal of Radiology
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• v.21 no.9
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• pp.1077-1086
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• 2020

Objective: To evaluate the effect of perfluorobutane microbubbles (Sonazoid^®, GE Healthcare) on steam popping during radiofrequency (RF) ablation for treating hepatocellular carcinoma (HCC), and to assess whether popping affects treatment outcomes. Materials and Methods: The institutional review board approved this retrospective study, which included 90 consecutive patients with single HCC, who received percutaneous RF ablation as the first-line treatment. The patients were divided into two groups, based on the presence or absence of the popping phenomenon, which was defined as an audible sound with a simultaneous sudden explosion within the ablation zone as detected via ultrasonography during the procedure. The factors contributing to the popping phenomenon were identified using multivariable logistic regression analysis. Local tumor progression (LTP) and disease-free survival (DFS) were assessed using the Kaplan-Meier method with the log-rank test for performing comparisons between the two groups. Results: The overall incidence of the popping phenomenon was 25.8% (24/93). Sonazoid^® was used in 1 patient (4.2%) in the popping group (n = 24), while it was used in 15 patients (21.7%) in the non-popping group (n = 69). Multivariable analysis revealed that the use of Sonazoid^® was the only significant factor for absence of the popping phenomenon (odds ratio = 0.10, p = 0.048). There were no significant differences in cumulative LTP and DFS between the two groups (p = 0.479 and p = 0.424, respectively). Conclusion: The use of Sonazoid^® has a suppressive effect on the popping phenomenon during RF ablation in patients with HCC. However, the presence of the popping phenomenon may not affect clinical outcomes.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.143-152
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• 2024

Due to COVID-19, domestic Duty-free shops have been severely impacted, and with the expansion of the untact market, the proportion of mobile shopping has increased. So far, mobile duty-free shop AR shopping is not active, and related research is scarce. Therefore, we aims to enhance Duty-free Shopping APPs with AR technology by researching the needs of foreign users. First, in the mobile duty-free shop app, the AR shopping interface must be in a prominent position to be open and easy to use. Second, there should be an explanation or help for location and function so that all users can easily recognize the AR shopping interface. Third, when wearing duty-free items in the AR shopping interface or adding them to the storage and shopping cart of interest, the interface must be simple and flexible, making it convenient to use and operate. Fourth, technical improvements must be made to prevent errors. We expect that the research will help develop AR shopping technology and domestic duty-free shop AR shopping technology and revitalize online and offline duty-free shops.

• Journal of Chest Surgery
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• v.41 no.5
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• pp.563-567
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• 2008

Background: The histomorphological properties of the left anterior desecending artery (LAD), the left internal thoracic arteries (LITA), the radial arteries (RA) and the intercostal arteries (ICA) were studied for their use as a conduit for coronary artery bypass grafting (CABG), and we compared them with each other. Material and Method: All the vessels were harvested from nineteen cadavers (17 males and 2 females). The mid-portion of the LAD, the mid-portion of the LITA, the distal RA and the mid-portion of the 5th ICA were obtained. All of them were stained with hematoxylin-eosin and with Van Gieson's elastin stain. The morphological characteristics were examined and the thicknesses of the intima and media (I/M ratio: the intima to media ratio) were compared using one-way ANOVA tests. Result: The mean age of the cadavers was $61.5{\pm}9.6$ years. The LITA and ICA were elastic arteries, and the LAD and RA were muscular arteries. The I/M ratio showed statistically significant differences: $0.07{\pm}0.03$ in the LITA, $0.16{\pm}0.11$ in the ICA, $0.45{\pm}0.29$ in the RA and $0.93{\pm}0.52$ in the LAD, respectively. Conclusion: This study showed that the degrees of intimal hyperplasia of the CA and the various conduits for CABG were different significantly. The ICA was found to have relatively favorable characteristics as a coronary by pass conduit, but its suitability for clinical use is a challenging issue.

• Journal of Nutrition and Health
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• v.46 no.3
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• pp.250-260
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• 2013

The purposes of this study were 1) to investigate eating behaviors and patterns in breast cancer patients using a newly developed food frequency questionnaire and 2) to examine perception and use of nutritional information about breast cancer treatment among cancer patients treated with radiation therapy. Sixty breast cancer patients (case group) undergoing radiation therapy in Ajou University Hospital, Suwon, South Korea and 79 healthy women (control group) participated in this study. Mean age of subjects in the control group was $46.00{\pm}7.88$ years and BMI was $23.12{\pm}2.85kg/m^2$, and that of the case group was $50.06{\pm}11.64$ years and $22.32{\pm}3.24kg/m^2$. The results of eating behaviors showed several significant differences between control and case groups. Breast cancer patients ate meals on a more regular basis, on time, and more frequently compared to control subjects. In addition, they preferred more salty or spicy and bland food compared to healthy women. According to answers from the food frequency questionnaire, breast cancer patients consumed significantly lower amounts of boiled white rice, meats and processed food, fish and shellfish, coffee, milk, and cheese, whereas they consumed a significantly large amount of boiled multigrain rice, vegetable, seaweeds, soybean and processed food, and yoghurt compared to healthy women. This study also observed the way in which cancer patients and healthy control subjects obtain information about breast cancer treatment and its reliabilities. Results showed that healthy women did not hesitate to obtain information from mass media, while breast cancer patients would obtain nutritional information from specialists rather than mass media. Results of this survey confirmed that breast cancer patients avoided intake of red meat protein, even though they already recognized the importance of dietary protein intake for recuperation and treatment of the disease. These results could be used for future diet and nutrition guidelines for breast cancer patients.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.1-19
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• 2018

Since stock movements forecasting is an important issue both academically and practically, studies related to stock price prediction have been actively conducted. The stock price forecasting research is classified into structured data and unstructured data, and it is divided into technical analysis, fundamental analysis and media effect analysis in detail. In the big data era, research on stock price prediction combining big data is actively underway. Based on a large number of data, stock prediction research mainly focuses on machine learning techniques. Especially, research methods that combine the effects of media are attracting attention recently, among which researches that analyze online news and utilize online news to forecast stock prices are becoming main. Previous studies predicting stock prices through online news are mostly sentiment analysis of news, making different corpus for each company, and making a dictionary that predicts stock prices by recording responses according to the past stock price. Therefore, existing studies have examined the impact of online news on individual companies. For example, stock movements of Samsung Electronics are predicted with only online news of Samsung Electronics. In addition, a method of considering influences among highly relevant companies has also been studied recently. For example, stock movements of Samsung Electronics are predicted with news of Samsung Electronics and a highly related company like LG Electronics.These previous studies examine the effects of news of industrial sector with homogeneity on the individual company. In the previous studies, homogeneous industries are classified according to the Global Industrial Classification Standard. In other words, the existing studies were analyzed under the assumption that industries divided into Global Industrial Classification Standard have homogeneity. However, existing studies have limitations in that they do not take into account influential companies with high relevance or reflect the existence of heterogeneity within the same Global Industrial Classification Standard sectors. As a result of our examining the various sectors, it can be seen that there are sectors that show the industrial sectors are not a homogeneous group. To overcome these limitations of existing studies that do not reflect heterogeneity, our study suggests a methodology that reflects the heterogeneous effects of the industrial sector that affect the stock price by applying k-means clustering. Multiple Kernel Learning is mainly used to integrate data with various characteristics. Multiple Kernel Learning has several kernels, each of which receives and predicts different data. To incorporate effects of target firm and its relevant firms simultaneously, we used Multiple Kernel Learning. Each kernel was assigned to predict stock prices with variables of financial news of the industrial group divided by the target firm, K-means cluster analysis. In order to prove that the suggested methodology is appropriate, experiments were conducted through three years of online news and stock prices. The results of this study are as follows. (1) We confirmed that the information of the industrial sectors related to target company also contains meaningful information to predict stock movements of target company and confirmed that machine learning algorithm has better predictive power when considering the news of the relevant companies and target company's news together. (2) It is important to predict stock movements with varying number of clusters according to the level of homogeneity in the industrial sector. In other words, when stock prices are homogeneous in industrial sectors, it is important to use relational effect at the level of industry group without analyzing clusters or to use it in small number of clusters. When the stock price is heterogeneous in industry group, it is important to cluster them into groups. This study has a contribution that we testified firms classified as Global Industrial Classification Standard have heterogeneity and suggested it is necessary to define the relevance through machine learning and statistical analysis methodology rather than simply defining it in the Global Industrial Classification Standard. It has also contribution that we proved the efficiency of the prediction model reflecting heterogeneity.