• Journal of Convergence for Information Technology
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• v.12 no.1
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• pp.76-82
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• 2022

Recently, natural and social disasters in Korea are increasing, and new disasters such as COVID 19 and sinkholes, and large-scale disasters that combine natural and social disasters are occurring frequently. In order to reduce damage caused by disasters and effectively respond to disasters, the importance of disaster safety education is emerging because it is necessary to understand the awareness of disaster situations and the functional response process. Ministry of Public Interior and Security is providing disaster safety education for emergency managers through 54 specialized disaster safety education institutions. There is also a lack of experience facilities. This has a problem in that it makes it difficult for disaster safety personnel to effectively respond to disasters due to lack of experience in actual disaster sites. Also, unlike other education fields, the connection between disaster safety education contents and new technologies such as AI is still lacking. In this study, focusing on natural disaster, the current status and problems of domestic disaster safety education institutions and their contents are investigated and analyzed, and based on this, this study suggested improvement plans for domestic disaster safety education contents such as establishment of a unified disaster safety standard curriculum, production and distribution of disaster safety education experience contents using virtual reality technology and infotainment technology, and development of mobile AI tutoring service.

• Journal of Convergence for Information Technology
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• v.12 no.4
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• pp.260-269
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• 2022

In this paper, We propose an anomaly detection model using deep neural network to automate the identification of outliers of the national air pollution measurement network data that is previously performed by experts. We generated training data by analyzing missing values and outliers of weather data provided by the Institute of Environmental Research and based on the BeatGAN model of the unsupervised learning method, we propose a new model by changing the kernel structure, adding the convolutional filter layer and the transposed convolutional filter layer to improve anomaly detection performance. In addition, by utilizing the generative features of the proposed model to implement and apply a retraining algorithm that generates new data and uses it for training, it was confirmed that the proposed model had the highest performance compared to the original BeatGAN models and other unsupervised learning model like Iforest and One Class SVM. Through this study, it was possible to suggest a method to improve the anomaly detection performance of proposed model while avoiding overfitting without additional cost in situations where training data are insufficient due to various factors such as sensor abnormalities and inspections in actual industrial sites.

• Journal of Convergence for Information Technology
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• v.12 no.4
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• pp.316-327
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• 2022

This study empirically analyzed the effects of beauty service training on customer orientation and job performance of beauty industry workers. First, as a result of the study, there were differences in service training, customer orientation, and job performance according to general characteristics, and service training showed significant differences in age, highest level of education, work experience, and number of employees, job performance in age, work experience, and number of employees, and job performance in age, academic background, work experience, and number of employees. Secondly, it was identified that service training makes a significant effect on customer orientation, the factor that makes the greatest effect on customer orientation among sub-factors of service training is educational content, and it can be seen that customer orientation increases when educational content, educational instructor, and educational environment are higher. Thirdly, it was identified that service training and customer orientation make a significant effect on job performance. hese research results show that the better the educational environment, instructor, and educational content of beauty industry workers, the higher the customer-oriented service, leading to the creation of loyal customers and can improve job performance as well.

• Journal of Radiation Protection and Research
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• v.47 no.1
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• pp.16-21
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• 2022

Background: Epidemiological observations such as mental retardation, physical deformities, etc., in children besides different types of cancer in the adult population of the Malwa region have been reported. The present study is designed to get insight into the role of naturally occurring radioactive material (NORM) in causing detrimental health effects observed in the general population of this region. Materials and Methods: Deep soil samples were collected from different locations in the Malwa region. Their activity concentrations were determined using low-level background gammaray spectrometry. High efficiency and high purity germanium detector capped in a lead-shielded chamber having a resolution of 1.8 keV at 1,173 keV and 2.0 keV at the 1,332 keV line of ⁶⁰Co was used in the present work. Data were evaluated with Genie-2000 software. Results and Discussion: Mean activity concentrations of ²³⁸U, ²³²Th, and ⁴⁰K in deep soil were found to be 101.3 Bq/kg, 65.8 Bq/kg, and 688.6 Bq/kg, respectively. The mean activity concentration of ²³⁸U was found to be three and half times higher than the global average prescribed by the United Nations Scientific Committee on the Effects of Atomic Radiation (UNSCEAR). It was further observed that the activity concentration of ²³²Th and ⁴⁰K has a magnitude that is nearly one and half times higher than the global average prescribed by UNSCEAR. In addition, the radioisotope ¹³⁷Cs which is likely to have its origin in radiation fallout was also observed. It is postulated that the NORM present in high quantity in deep soil somehow get mobilized into the water aquifers used by the general population and thereby causing harmful health problems. Conclusion: It can be stated that the present work has been able to demonstrate the use of low background gamma-ray spectrometry to understand the role of NORM in causing health-related effects in a general population of the Malwa region of Punjab, India.

• Journal of Convergence for Information Technology
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• v.12 no.4
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• pp.103-110
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• 2022

Online transactions are more familiar in various fields due to the development of the ICT and the increase in trading platforms. In particular, the amount of transactions is increasing due to the increase in used transaction platforms and users, and reliability is very important due to the nature of used transactions. Among them, the used car market is very active because automobiles are operated over a long period of time. However, used car transactions are a representative market to which information asymmetry is applied. In this paper presents a DID-based transaction model that guarantees reliability to solve problems with false advertisements and false sales in used car transactions. In the used car transaction model, sellers only register data issued by the issuing agency to prevent false sales at the time of initial sales registration. It is authenticated with DID Auth in the issuance process, it is safe from attacks such as sniping and middleman attacks. In the presented transaction model, integrity is verified with VP's Proof item to increase reliability and solve information asymmetry. Also, through direct transactions between buyers and sellers, there is no third-party intervention, which has the effect of reducing fees.

• Journal of Convergence for Information Technology
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• v.12 no.5
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• pp.183-193
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• 2022

The purpose of this study is to analyze the effect of black consumer behavior perception on the anger expression and turnover intention of beauty workers. For data collection, the final 392 copies were used by distributing questionnaires to 400 people for three months from November 1, 2021 to January 31, 2022, centering on beauty service workers in Seoul, Gyeonggi, and Incheon. For data analysis, SPSS 25.0 program was used. Frequency analysis was performed to identify demographic characteristics, and factor analysis and reliability analysis were performed to understand the validity of the measurement tool. Correlation analysis, A regression analysis was performed. As a result of the analysis, the transient and deterrence of black consumers had a positive (+) effect on anger expression, anger suppression, and turnover intention, and anger expression and anger control had a positive (+) effect on turnover intention. Therefore, it is necessary to raise excessive problems of black consumers or eradicate forced services, and it is believed that proper customer response methods and programs for stress relief should be provided by members.

• Journal of Convergence for Information Technology
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• v.11 no.8
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• pp.42-52
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• 2021

This study was conducted to identify the influence of the discrimination experienced in daily life and social isolation on depression among older adults living in the community. This study was a secondary analysis of the data of 2017 Living Profiles of Older Adults Survey. The participants was a representative sample among the older adults 65 years and older. Data from 10,041 older adults were analyzed for this study. Hierarchical logistic regression analyses were used. When the discrimination experiences was added in model 1, the likelihood of being depressed was 1.95(1.60-2.36) times higher for those who experienced discrimination comparing with those who didn't experienced discrimination. When the social isolation was added in model 2, the likelihood of being depressed was 1.89(1.55-2.30) times higher in those who experienced discrimination. In addition, as the number of close friends, neighbors, and acquaintances decreased by one, the likelihood of being depressed increased by 1.14 times. Those who were isolated from family, friends, neighbors and acquaintances were 3.90 times more likely to be depressed. Therefore, social efforts are needed to reduce the experience of discrimination. Maintaining a social network or creating a new network will contribute to lowering the level of depression in older adults who have experienced discrimination.

• Journal of Convergence for Information Technology
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• v.11 no.8
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• pp.36-41
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• 2021

Although the technology for prediction or analysis using artificial intelligence is constantly developing, a black-box problem does not interpret the decision-making process. Therefore, the decision process of the AI model can not be interpreted from the user's point of view, which leads to unreliable results. We investigated the problems of artificial intelligence and explainable artificial intelligence using Blockchain to solve them. Data from the decision-making process of artificial intelligence models, which can be explained with Blockchain, are stored in Blockchain with time stamps, among other things. Blockchain provides anti-counterfeiting of the stored data, and due to the nature of Blockchain, it allows free access to data such as decision processes stored in blocks. The difficulty of creating explainable artificial intelligence models is a large part of the complexity of existing models. Therefore, using the point cloud to increase the efficiency of 3D data processing and the processing procedures will shorten the decision-making process to facilitate an explainable artificial intelligence model. To solve the oracle problem, which may lead to data falsification or corruption when storing data in the Blockchain, a blockchain artificial intelligence problem was solved by proposing a blockchain-based explainable artificial intelligence model that passes through an intermediary in the storage process.

• Journal of Convergence for Information Technology
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• v.12 no.2
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• pp.116-126
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• 2022

Many studies using trademark information have suggested that trademark information is good data to monitor business trends. This study intends to analyze the trend change before and after COVID-19 using trademark information. Changes before and after COVID-19 were analyzed by using goods & service classification, similar group code, and designated goods information as trademark information. Among the trademark information, it was statistically significant that the change in trends before and after COVID-19 using designated goods names. To verify the results, the changes in keywords using designated goods names before and after COVID-19 were compared with the frequency of keywords in Google Trends. Among the top 8 keywords extracted from designated goods names, the frequency of Google trend searches for 'online, antibacterial, prevention of epidemics, meal kit, virtual' is on the rise, and 'mask, droplet' is not on the rise, but it increased rapidly at the time of COVID-19, and even after COVID-19, it showed a higher level than before. The frequency of 'unmanned' does not differ much before and after COVID-19, but it has been maintained at a consistently high level, and related businesses have been active since before COVID-19, and it can be interpreted as a keyword with high public interest. This study has academic achievements in that it specifically identified information that could be used in business trends by using three types of trademark information.

• Journal of Convergence for Information Technology
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• v.12 no.3
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• pp.132-140
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• 2022

This study was conducted to identify the optimal lotion manufacturing conditions with decursin and decursinol angelate of Angelica gigas Nakai extraction. Lotion was confirmed that it had viscosity (5,208±112 cPs), assay (99.71±1.01%), and pH (5.62) for 3 months. The optimization of manufacturing conditions of mixing 4 for lotion formulation were made by 22+3 full factorial design. Mixing temperature (40-80℃) and mixing time (10-30 min) were used as independent variables with three responses(assay, pH, and weight variation) as critical quality attributes (CQAs). The model for assay and weight variation identified a proper fit having a determination coefficient of the regression equation (about 0.9) and a p-value less than 0.05. Estimated conditions for the optimal manufacturing process of lotion were 61.93℃ in mixing temperature and 15.85 min in mixing time. Predicted values at the mixing temperature (60℃) and mixing time (20 min) were 100.69% of assay, 5.57 of pH, and 98.07% of weight variation. In the verification of the actual measurement the obtained values showed 100.29±0.98% of assay, 5.57±0.02 of pH, and 98.27±0.89% of weight variation, respectively, in good agreement with predicted values.