• Journal of Digital Convergence
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• 제19권3호
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• pp.319-329
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• 2021

This study aims to investigate Korean fashion-related research trends and knowledge structures on digital transformation through information-based approaches. Accordingly, we first identified the current status of the relevant research in Korean academic literature by year and journal; subsequently, we derived key research topics through network analysis, and then analyzed major research trends and knowledge structures by time. From 2010 to 2020, we collected 159 studies published on Korean academic platforms, cleansed data through Python 3.7, and measured centrality and network implementation through NodeXL 1.0.1. The results are as follows: first, related research has been actively conducted since 2016, mainly concentrated in clothing and art areas. Second, the online platform, AR/VR, appeared as the most frequently mentioned topic, and consumer psychological analysis, marketing strategy suggestion, and case analysis were used as the main research methods. Through clustering, major research contents for each sub-major of clothing were derived. Third, major subject by period was considered, which has, over time, changed from consumer-centered research to strategy suggestion, and design development research of platforms or services. This study contributes to enhancing insight into the fashion field on digital transformation, and can be used as a basic research to design research on related topics.

• The Journal of the Korea Contents Association
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• 제22권1호
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• pp.99-115
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• 2022

In this study, domestic academic journal papers on tax compliance, tax consciousness, and faithful tax payment (hereinafter referred to as "tax compliance") were comprehensively analyzed from an interdisciplinary perspective as a representative research topic in the field of tax science. To achieve the research purpose, topic modeling technique was applied as part of text mining. In the flow of data collection-keyword preprocessing-topic model analysis, potential research topics were presented from tax compliance related keywords registered by the researcher in a total of 347 papers. The results of this study can be summarized as follows. First, in the keyword analysis, keywords such as tax investigation, tax avoidance, and honest tax reporting system were included in the top 5 keywords based on simple term-frequency, and in the TF-IDF value considering the relative importance of keywords, they were also included in the top 5 keywords. On the other hand, the keyword, tax evasion, was included in the top keyword based on the TF-IDF value, whereas it was not highlighted in the simple term-frequency. Second, eight potential research topics were derived through topic modeling. The topics covered are (1) tax fairness and suppression of tax offenses, (2) the ideology of the tax law and the validity of tax policies, (3) the principle of substance over form and guarantee of tax receivables (4) tax compliance costs and tax administration services, (5) the tax returns self- assessment system and tax experts, (6) tax climate and strategic tax behavior, (7) multifaceted tax behavior and differential compliance intentions, (8) tax information system and tax resource management. The research comprehensively looked at the various perspectives on the tax compliance from an interdisciplinary perspective, thereby comprehensively grasping past research trends on tax compliance and suggesting the direction of future research.

• KSCE Journal of Civil and Environmental Engineering Research
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• 제42권1호
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• pp.35-44
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• 2022

The V_S30 map is used as a key variable for site amplification in the ShakeMap, which predicts ground motion at any site. However, no V_S30 map considering Korean geology and geomorphology has been developed yet. To develop a proxy-based V_S30 map, we used 1,101 V_S profiles obtained from a geophysical survey and collected proxy layers of geological and topographical information for the Korean Peninsula. Then, V_S30 prediction models were developed using linear regression analysis for each geological age considering the distribution of V_S30. As a result, models depending on geomorphology were suggested per each geologic group, including Quaternary, Fill, Ocean, Mesozoic group and Precambrian. Resolution of map is doubled from that of V_S30 map by U.S. Geological Survey (USGS). Standard deviation of residual in natural log of proxy-based V_S30 map is 0.233, whereas standard deviation of slope-based USGS V_S30 map is 0.387. Therefore, the proxy-based V_S30 map developed in this study is expected to have less uncertainty and to contribute to predicting more accurately the ground motion amplitude.

• Journal of the Korean Society of Marine Environment & Safety
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• 제27권2호
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• pp.266-274
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• 2021

Ship officers are subject to excessive job stress, which has negative physical and psychological impacts and may adversely affect the smooth supply and demand of human resources. In this study, a mobile web application was developed as a tool for systematic job stress measurement and management of officers and verified through quality evaluation. Requirement analysis was performed by ship officers and staff in charge of human resources of shipping companies, and the results were reflected in the application configuration step. The application was designed according to the waterfall model, which is a traditional software development method, and functions were implemented using JSP and Spring Framework. Performance evaluation on the user interface, confirmed that proper input and output results were implemented, and the respondent results and the database were configured in the administrator interface. The results of evaluation questionnaires for quality evaluation of the interface based on ISO/IEC 9126-2 metric were significant 4.60 for the user interface and 4.65 for the administrator interface in a 5-point scale. In the future, it is necessary to conduct follow-up research on the development of data analysis system through utilization of the collected big-data sets.

• Journal of the Korea Institute of Building Construction
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• 제21권3호
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• pp.231-239
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• 2021

Entering the era of the fourth industrial revolution, information and communication technologies such as CCTV, home network systems and equipment are being used in the construction industry. In particular, in order to increase the autonomy of information and communication technologies in apartments, the government has announced an administrative revision of information and communication-related laws, and companies are focusing on developing technologies such as smart home services. In addition, most domestic and foreign studies on the information and communication work were mainly conducted on technology and management. However there is a lack of research on physical defects affecting the quality of ICT. Therefore, this study collected the defect data registered in the project management system of three domestic construction companies and classified them according to the standards of the Enforcement Decree of the Apartment House Management Act. According to the analysis of the frequency of defects work type, 88.10% of defects occurred in home network equipment work. In addition, analysis of defects type in the four detailed works showed the highest number of operation error. The cause was analyzed and prevention measures and countermeasures were presented in parts of design, construction, and maintenance. The results of this study will improve the quality of apartment housing and be used as basic data for future research on practical defect minimization and prevention measures.

• The Journal of the Korea institute of electronic communication sciences
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• 제16권4호
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• pp.771-782
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• 2021

Regular or irregular situations such as traffic accidents, damage to road facilities, maintenance or repair work, and vehicle breakdowns occur frequently on highways. It is required to provide traffic services to drivers by promptly recognizing these regular or irregular situations, various techniques have been developed for rapidly collecting data and detecting abnormal traffic conditions to solve the problem. We propose a method that can be used for verification and demonstration of unexpected situation algorithms by establishing a system and developing algorithms for detecting unexpected situations on highways. For the detection of emergencies on expressways, a system was established by defining the expressway contingency and algorithm development, and a test bed was operated to suggest a method that can be used for verification and demonstration of contingency algorithms. In this study, a system was established by defining the unexpected situation and developing an algorithm to detect the unexpected situation on the highway, and a method that can be used verifying and demonstrating unexpected situations. It is expected to secure golden time for the injured by reducing the effectiveness of secondary accidents. Also predictable accidents can be reduced in case of unexpected situations and the detection time of unpredictable accidents.

• Journal of Digital Convergence
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• 제20권2호
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• pp.325-338
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• 2022

This study was conducted to explore the acceptance behavior of undergraduate students toward telemedicine, which is temporarily allowed in the COVID-19. We applied social cognitive theory and technology acceptance model in order to reflect the convergence characteristics between medical service and digital technology of telemedicine. Based on these theoretical backgrounds, we investigated perception toward telemedicine and determinants of intention to accept telemedicine. To examine the research model and hypothesis, an online survey was conducted for college students who have not used telemedicine from September 8 to 10, 2021. A total of 184 data were collected, and multiple regression analysis was conducted using the SPSS 28.0 program. The results showed that health technology self-efficacy, usefulness and convenience benefits, social norm, and trust in telemedicine providers had positive effects on intention to accept telemedicine. This study is meaningful in that it selected undergraduate students, who are digital natives, as new targets for telemedicine, and presented the basic direction of strategies to target them.

• Journal of Internet Computing and Services
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• 제23권2호
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• pp.29-35
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• 2022

UV rays have beneficial or harmful effects on the human body depending on the degree of exposure. An accurate UV information is required for proper exposure to UV rays per individual. The UV rays' information is provided by the Korea Meteorological Administration as one component of daily weather information in Korea. However, it does not provide an accurate UVI at the user's location based on the region's Ultraviolet index. Some operate measuring instrument to obtain an accurate UVI, but it would be costly and inconvenient. Studies which assumed the UVI through environmental factors such as solar radiation and amount of cloud have been introduced, but those studies also could not provide service to individual. Therefore, this paper proposes a deep learning model to calculate UVI using solar object information and sunlight characteristics to provide an accurate UVI at individual location. After selecting the factors, which were considered as highly correlated with UVI such as location and size and illuminance of sun and which were obtained through the analysis of sky images and solar characteristics data, a data set for DNN model was constructed. A DNN model that calculates the UVI was finally realized by entering the solar object information and sunlight characteristics extracted through Mask R-CNN. In consideration of the domestic UVI recommendation standards, it was possible to accurately calculate UVI within the range of MAE 0.26 compared to the standard equipment in the performance evaluation for days with UVI above and below 8.

• Smart Media Journal
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• 제12권7호
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• pp.43-51
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• 2023

As online transactions increase, the image of clothing has a great influence on consumer purchasing decisions. The importance of image information for clothing materials has been emphasized, and it is important for the fashion industry to analyze clothing images and grasp the materials used. Textile materials used for clothing are difficult to identify with the naked eye, and much time and cost are consumed in sorting. This study aims to classify the materials of textiles from clothing images based on deep learning algorithms. Classifying materials can help reduce clothing production costs, increase the efficiency of the manufacturing process, and contribute to the service of recommending products of specific materials to consumers. We used machine vision-based deep learning algorithms ResNet and Vision Transformer to classify clothing images. A total of 760,949 images were collected and preprocessed to detect abnormal images. Finally, a total of 167,299 clothing images, 19 textile labels and 20 fabric labels were used. We used ResNet and Vision Transformer to classify clothing materials and compared the performance of the algorithms with the Top-k Accuracy Score metric. As a result of comparing the performance, the Vision Transformer algorithm outperforms ResNet.

• Journal of the Korea Society of Computer and Information
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• 제28권8호
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• pp.187-194
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• 2023

Recently, a lot of discussions are underway in the field of introducing new technologies about the rapidly growing metaverse. However, the degree of acceptance of metaverse users at the beginning of the introduction is different from expectations, so research should be conducted for the continuous use of current real users and service success. In this study, we would like to investigate the relationship between four experience factors according to Metaverse's experiential economy theory, and perceived value and intention to continue use. A survey was conducted on metaverse real-life veterans, and 177 questionnaires were finally analyzed. The collected data were empirically analyzed using SPSS 25.0 and AMOS 21.0. As a result; First, it was found that all the experience factors of the metaverse had a positive effect on the perceived value. Second, all of the experience factors of metaverse were found to have a positive effect on the intention to continue use. Third, perceived value was found to have a positive effect on the intention to continue use. Based on the analysis results, the implications and limitations of this study were presented. Based on the analysis results, metaverse should provide and develop various experience factors differentiated from reality to users. In addition, providing an experience environment and value that metaverse users can perceive will increase users' intention to continue using it.