• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.469-474
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• 2021

Nowadays, a lot of software engineers struggle with the efficient back-end design of mobile application programs operated on the new mobile platform. It is simply because not only their lack of experiences in developing large scale system but also the unstructured nature of the mobile software, where there are no standard solutions. Furthermore, since big data is at the center of many challenges in system design of mobile software, so an efficient system design scheme is required for the development of such data-intensive applications. In this paper, we propose a systematic and efficient system design method that can figure out the substantial nature of the mobile software and solve the difficulties of the back-end software engineers.

• Fashion & Textile Research Journal
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• v.23 no.6
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• pp.790-798
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• 2021

With digital technology innovation, increased data access and mobile network use by consumers, products and services are changing toward pursuing differentiated values for personalization, and personalized markets are rapidly emerging in the fashion industry. This study aims to identify trends in digital customized automation technology by deriving types of digital customizing and analyzing cases by type, and to present directions for the development of digital customizing processes and the use of technology in the future. As a research method, a literature study for a theoretical background, a case study for classification and analysis of types was conducted. The results of the study are as follows. The types of digital customizing can be classified into three types: 'cooperative customization', 'selective composition and combination', 'transparent suggestion', and automation technologies shown in each type include 3D printing, 3D virtual clothing, robot mannequin, human automatic measurement program, AR-based fitting service, big data, and AI-based curation function. With the development of digital automation technology, the fashion industry environment is also changing from existing manufacturing-oriented to consumer-oriented, and the production process is rapidly changing with IT and artificial intelligence-based automation technology. The results of this study hope that digital customized automation technology will meet various needs of personalization and customization and present the future direction of digital fashion technology, where fashion brands will expand based on the spread of digital technology.

• Journal of East-West Nursing Research
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• v.28 no.1
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• pp.41-48
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• 2022

Purpose: The purpose of this study was to identify factors influencing prevention behaviors for particulate matter exposure in young adults. Methods: A convenience sample of 330 young adults was recruited from the community. Data were collected using a structured questionnaire and analyzed by descriptive statistics, t-test, ANOVA, Pearson's correlation coefficients, and stepwise multiple regression analysis with the SPSS/WIN 26.0 program. Results: The factors affecting prevention behaviors of particulate matter exposure were self-efficacy (β=.54 p<.001), subjective norm (β=.18, p<.001) and using the air purifier (β=.-17, p<.001). These variables had a 46% variance to explain prevention behaviors for particulate matter exposure. Conclusion: Findings showed that 'self-efficacy' and 'subjective norm' were important factors influencing prevention behaviors of particulate matter exposure in young adults. Thus, we need to consider the positive impact of prevention behaviors of particulate matter exposure and increase the chances of prevention behaviors of particulate matter exposure program for young adults.

• Fashion & Textile Research Journal
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• v.24 no.1
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• pp.66-80
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• 2022

Even before the Covid-19 outbreak, the second-hand fashion market has been growing as the fashion industry strives towards sustainability. It has also accelerated due to the economic contraction caused by the pandemic. In previous studies, the second-hand market has been steadily studied; however, the research is insufficient compared to the diversified market. Therefore, this study investigates changes in consumers' perception of the second-hand fashion market affected by Covid-19. This study collected text data with the keyword 'second-hand fashion' from various blogs. We analyzed 24,000 posts before and after the Covid-19 outbreak by applying the LDA algorithm for topic modeling and content analysis. Seven and nine different topics for the period before and after the pandemic respectively were derived. The results revealed that during the pandemic the consumers realized the practical value of sustainability in their daily lives than they did before the pandemic. Furthermore, they tried to minimize transaction anxiety by using diverse platforms with advanced technology. They also realized economic value by buying and selling sneakers in the popular sneakers resale market. The results could help understand the rapidly growing second-hand fashion market during Covid-19.

• Nuclear Engineering and Technology
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• v.54 no.2
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• pp.770-780
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• 2022

In 1993 the University of Extremadura initiated the design, construction and management of the Radiological Alert Network of Extremadura (RAREx). The goal was to acquire reliable near-real-time information on the environmental radiological status in the surroundings of the Almaraz Nuclear Power Plant by measuring, mainly, the ambient dose equivalent. However, the phased development of this network has been carried out from two points of view. Firstly, there has been an increase in the number of stations comprising the network. Secondly, there has been an increase in the number of monitored parameters. As a consequence of the growth of RAREx network, large data volumes are daily generated. To face this big data paradigm, software applications have been developed and implemented in order to maintain the indispensable real-time and efficient performance of the alert network. In this paper, the description of the current status of RAREx network after 30 years of design and performance is showed. Also, the performance of the graphing software for daily assessment of the registered parameters and the automatic on real time warning notification system, which aid with the decision making process and analysis of values of possible radiological and non-radiological alterations, is briefly described in this paper.

• Journal of KIBIM
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• v.12 no.2
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• pp.1-11
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• 2022

Road traffic accidents (RTAs) are the leading cause of accidental death among children. RTA reduction is becoming an increasingly important social issue among children. Municipalities aim to resolve this issue by introducing "Smart Pedestrian Crosswalks" that help prevent traffic accidents near children's facilities. Nonetheless such facilities tend to be installed in relatively limited number of areas, such as the school zone. In order for budget allocation to be efficient and policy effects maximized, optimal location selection based on machine learning is needed. In this paper, we employ machine learning models to select the optimal locations for smart pedestrian crosswalks to reduce the RTAs of children. This study develops an optimal location index using variable importance measures. By using k-means clustering method, the authors classified the crosswalks into three types after the optimal location selection. This study has broadened the scope of research in relation to smart crosswalks and traffic safety. Also, the study serves as a unique contribution by integrating policy design decisions based on public and open data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.6
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• pp.1913-1934
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• 2022

The emergence of technologies like Big data analytics, Industrial Internet of Things, Internet of Things, and applicability of these technologies in various domains leads to increased demand in the underlying execution environment. The demand may be for compute, storage, and network resources. These demands cannot be effectively catered by the conventional cloud environment, which requires an integrated environment. The task of finding an appropriate service provider is tedious for a service consumer as the number of service providers drastically increases and the services provided are heterogeneous in the specification. A service broker is essential to find the service provider for varying service consumer requests. Also, the service broker should be smart enough to make the service providers best fit for consumer requests, ensuring that both service consumer and provider are mutually beneficial. A service broker in an integrated environment named Global Manager is proposed in the paper, which can find an appropriate service provider for every varying service consumer request. The proposed Global Manager is capable of identification of parameters for service negotiation with the service providers thereby making the providers the best fit to the maximum possible extent for every consumer request. The paper describes the architecture of the proposed Global Manager, workflow through the proposed algorithms followed by the pilot implementation with sample datasets retrieved from literature and synthetic data. The experimental results are presented with a few of the future work to be carried out to make the Manager more sustainable and serviceable.

• Journal of Soil and Groundwater Environment
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• v.27 no.2
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• pp.36-40
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• 2022

To respond to rapidly changing water circumstances such as climate change, drought, etc., the korean government (MOE) established four advanced strategies for integrated groundwater management. The first strategy is watershed-based management of groundwater. The second strategy is total quantity management of groundwater including improvement of groundwater preservation area policy and procedure of investigation for groundwater influence area, additional construction of groundwater dam, installation of large-scale public wells, extention of spilled groundwater use. The third strategy is prevention of groundwater contamination including expansion of monitoring wells, introducing declaration of groundwater contamination. The last strategy is advancement of groundwater information management including integrated management of data, setting up a big-data based open platform. The above-mentioned four strategies will be reflected in the 4th National Groundwater Management Plan to secure implementation power, and it is expected to laid the foundation for advanced and rational groundwater management system.

• International Journal of Knowledge Content Development & Technology
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• v.12 no.3
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• pp.79-99
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• 2022

South Korea is at an important juncture in its history to decide whether to continue its investment to become a first-mover of artificial intelligence (A.I.) platform technology or stay as a fast follower. This paper compares South Korea's A.I. platform capacity to that of the United States, China and the European Union by reviewing publicly opened documents and reports on AI platform strategies and policies using the three elements of the national innovation capacity: common innovation infrastructure, cluster-specific conditions, and quality of linkages. This paper found three major areas the South Korean government can focus on in the A.I. platform industry. First, South Korea needs to increase its investment in the A.I. field and expand its public-private collaboration activities. Second, unlike the U.S. and the U.K., South Korea lacks data protection policies. Third, South Korea needs to build a high-performance system and environment to experiment with artificial intelligence technology and big data.

• The Journal of Information Systems
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• v.31 no.4
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• pp.47-73
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• 2022

Purpose The purpose of this study is to select the electronic architecture concept of the powertrain domain of the electronic platform to be applied to electric vehicles after 2025. Previously, the automotive electrical and electronic architecture was determined only by trend analysis, but the purpose was to determine the scenario based on the data and select it with clear evaluation indicators. Design/methodology/approach This study identified the function to be applied to the powertrain domain of next-generation electric vehicle, estimated the controller, defined the function feature list, organized the scenario candidates with the controller list and function feature list, and selected the final architecture scenario. Findings According to the research results, the powertrain domain of electric vehicles was selected as the architectural concept to apply the DCU (Domain Control Unit) and VCU (Vehicle Control Unit) integrated architecture to next-generation electric vehicles. Although it is disadvantageous or equivalent in terms of cost, it was found to be excellent in most indicators such as stability, security, and hardware demand.