• Journal of People, Plants, and Environment
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• v.23 no.3
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• pp.347-362
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• 2020

Background and objective: It is difficult to conclusively determine the exact cause of tree defects since multiple causes are involved such as climate change, plantation, tree quality and planting time, construction, planting base, drainage, sunshine conditions, maintenance, and microclimate. The data related to landscaping construction defects are scattered or fragmented by companies and years, but not managed systematically by the defect information management system. Most of the earlier studies associated with tree defects in apartment complexes suggested defect rates after examining tree defects in the completed construction site and proposed fragmentary and subjective conclusions about the causes of defects observed in trees with high defect rates. It is proposed to continue to conduct studies on the establishment and analysis of systematic databases to identify the exact causes of tree defects and measures to improve, and the need to accumulate systematic data in the construction process where many defects arises. This study was conducted to reduce the defects of trees planted in apartment complexes. Methods: Main factors related to tree defects were subdivided based on the results of literature review and a defect investigation at the completion site, and tree history management items were selected and subdivided during the construction stage. Results: The criteria for the preparation of subdivided items were obtained, and the tree history management checklist was written for the site under actual construction and a systematic database was established. Items that are categorized based to the causes of defects include the location of nurseries, date, tree quality, site conditions, planting techniques, microclimates, and maintenance. Conclusion: This study suggested tree history management items based on the tree defects that can be identified at the construction stage and applied them to the selected study site, which differentiates this study from earlier studies. It will be necessary to conduct a comprehensive and objective time series analysis on tree defects that occur over time by continuously monitoring and collecting data after construction.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.1
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• pp.9-16
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• 2023

The importance of team activities increases as the problem to be solved in the industrial field become more diverse and complex. Team performance is not simply the sum of team members' performances, but synergies are gained or reduced depending on the team's interactions. Analytical research on team activities using ICT has been conducted, but developing and utilizing these technologies is time-consuming and costly, making it difficult for field practitioners and researchers to utilize them. In this study, we design a system that collects interaction information during conversations at a low cost using Arduino and Raspberry Pi and verify that conversation interaction information is collected from multiple devices and correctly stored in the database. Through the low-cost information collection system proposed in this study, we intend to create an environment where follow-up research can be conducted in various fields of industrial information.

• Fashion & Textile Research Journal
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• v.24 no.1
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• pp.81-94
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• 2022

The purpose of this study is to analyze the trends of MZ generation's lifestyle-related research from 2010 to 2020. As a result of searching keywords such as MZ generation's and lifestyle using academic database search sites, a total of 218 cases were used as analysis data to conduct frequency and content analysis. First, research type was 74 dissertations(34.6%), 144 journals(65.4%). The study of MZ generation was relatively active in journals. Second, the current status of academic field was 85(39.7%) in the social field, followed by 66(30.8%) in the arts/physical education, 21(9.8%) in the complex studies, 16(7.5%) in education, 15(7.0%) in nature, 6(2.8%) in engineering, 4(1.9%) in humanities, 1(0.5%) in agriculture/marine. Third, the current status of MZ generation research topics is 54 social participations(25.3%), 35 fashion/beauty(16.3%), 31 social/organizational adaptations(14.5%), 25 cultural/leisure activities(11.7%), 24 design/development projects(11.2%), 21 economic/employment/job projects(9.8%), 11 educational/career/experiences(5.1%), 9 self-concepts(4.2%), 4 welfare services(1.9%). Fourth, the current status of MZ generation research methods was quantitative research(survey/experiment) 125(58.4%), qualitative research(depth interview/participant observation) 42(19.6%), theory/literature research 35(16.4%) and mixed research 12(5.6%). Fifth, the study on the lifestyle of the MZ generation was conducted in four cases, one in 2016, one in 2019, two in 2020. This study is meaningful in that it grasped the overall flow of data of information exchange that can share the research trends of the MZ generation and suggested the basic data on the direction of future research, the individual tendency, behavior, and lifestyle characteristics of the MZ generation.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.6_2
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• pp.1103-1110
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• 2022

The old machine tools that have been used for a long time cause both increase in defective rate and decrease in productivity compared to new machines due to wear and failure of their components. In order to improve productivity and quality of machined components through remanufacturing, it is necessary to analyze the wear and failure of major components of old machine tools. In this study, the process for reverse engineering is designed for the remanufacture of planner millers, which belong to a very large machine tool. Also, the suitability of the designed process is verified through the analysis of the selected remanufactured components. In the first step of the process, some major components of the aging planner miller are scanned using a 3D laser scanner. In the next step, reverse engineering is performed using the data obtained through 3D scanning. Finally, wear and failure analysis is performed by comparing the reverse engineering data with the scan data. As a result, this reverse design and wear analysis can complement the insufficient design database and reduce costs in the maintenance of remanufactured products.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.6
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• pp.693-700
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• 2017

The mines in our country are complex in geography and shape and because of its small scale, accurate surveying performance and 3D modeling are necessary for mine development and management and mining plans. However, due to the data acquisition and processing technology and economy, the existing methods are currently used. The structure, mining, and mining area of the mine are recorded and managed based on the 2D drawings. As a result, it is true that there is risk of accidents caused by problems of accuracy as well as waste of personnel and time. In recent years, research data on geology and geospatial information on mines have been integrated into a database in foreign countries, and they are used for mine management and mining planning. In this study, we tried to construct spatial information for mining management and mining plan using laser scanner. Through research, spatial information about the mine was effectively obtained and produced data modeled through data processing. The 3D model for mining mines is expected to be a valuable tool for establishing and operating a safe mining plan for mines.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.140-140
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• 2021

Urban flood management is a crucial and challenging task, particularly in developed cities. Therefore, accurate prediction of urban flooding under heavy precipitation is critically important to address such a challenge. In recent years, machine learning techniques have received considerable attention for their strong learning ability and suitability for modeling complex and nonlinear hydrological processes. Moreover, a survey of the published literature finds that hybrid computational intelligent methods using nature-inspired algorithms have been increasingly employed to predict or simulate the streamflow with high reliability. The present study is aimed to propose a novel approach, an ensemble tree, Bayesian Additive Regression Trees (BART) model incorporating a nature-inspired algorithm to predict hourly multi-step ahead streamflow. For this reason, a hybrid intelligent model was developed, namely GA-BART, containing BART model integrating with Genetic algorithm (GA). The Jungrang urban basin located in Seoul, South Korea, was selected as a case study for the purpose. A database was established based on 39 heavy rainfall events during 2003 and 2020 that collected from the rain gauges and monitoring stations system in the basin. For the goal of this study, the different step ahead models will be developed based in the methods, including 1-hour, 2-hour, 3-hour, 4-hour, 5-hour, and 6-hour step ahead streamflow predictions. In addition, the comparison of the hybrid BART model with a baseline model such as super vector regression models is examined in this study. It is expected that the hybrid BART model has a robust performance and can be an optional choice in streamflow forecasting for urban basins.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.119-127
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• 2022

Most of the construction works are conducted outdoors, so the construction workers are affected by weather conditions such as temperature, humidity, and wind velocity which can be evaluated the thermal comfort as environmental factors. In our previous researches, it was found that construction accidents are usually occurred in the discomfort ranges. The safety management, therefore, should be planned in consideration of the thermal comfort and measured by a specialized simulation tool. However, it is very complex, time-consuming, and difficult to model. To address this issue, this study is aimed to develop a framework of a prediction model for improving the prediction accuracy about outdoor thermal comfort considering environmental factors using machine learning algorithms with hyperparameter tuning. This study is done in four steps: i) Establishment of database, ii) Selection of variables to develop prediction model, iii) Development of prediction model; iv) Conducting of hyperparameter tuning. The tree type algorithm is used to develop the prediction model. The results of this study are as follows. First, considering three variables related to environmental factor, the prediction accuracy was 85.74%. Second, the prediction accuracy was 86.55% when considering four environmental factors. Third, after conducting hyperparameter tuning, the prediction accuracy was increased up to 87.28%. This study has several contributions. First, using this prediction model, the thermal comfort can be calculated easily and quickly. Second, using this prediction model, the safety management can be utilized to manage the construction accident considering weather conditions.

• Health Policy and Management
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• v.33 no.3
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• pp.295-310
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• 2023

Background: The long-term care (LTC) group has higher rates of chronic disease and disability registration compared to the general older people population. There is a need to provide integrated medical services and care for LTC group. Consequently, this study aimed to identify medical usage patterns based on the ratings of LTC and the characteristics of benefits usage in the LTC group. Methods: This study employed the National Health Insurance Service Database to analyze the effects of demographic and LTC-related characteristics on medical usage from 2015 to 2019 using a repeated measures analysis. A longitudinal logit model was applied to binary data, while a linear mixed model was utilized for continuous data. Results: In the case of LTC ratings, a positive correlation was observed with overall medical usage. In terms of LTC benefit usage characteristics, a higher overall level of medical usage was found in the group using home care benefits. Detailed analysis by medical institution classification revealed a maintained correlation between care ratings and the volume of medical usage. However, medical usage by classification varied based on the characteristics of LTC benefit usage. Conclusion: This study identified a complex interaction between LTC characteristics and medical usage. Predicting the requisite medical services based on the LTC rating presented a challenge. Consequently, it becomes essential for the LTC group to continuously monitor medical and care needs, even after admission into the LTC system. To facilitate this, it is crucial to devise an LTC rating system that accurately reflects medical needs and to broaden the implementation of integrated medical-care policies.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.104-110
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• 2023

In the user-centered design paradigm, information systems are created entirely tailored to the users who will use them. When the functions of a complex system meet a simple user interface, users can use the system conveniently. While web personalization services are emerging as a major trend in portal services, portal companies are competing for a second service, such as introducing 'integrated communication platforms'. Until now, the role of the portal has been content and search, but this time, the goal is to create and provide the personalized services that users want through a single platform. Personalization service is a login-based cloud computing service. It has the characteristic of being able to enjoy the same experience at any time in any space with internet access. Personalized web services like this have the advantage of attracting highly loyal users, making them a new service trend that portal companies are paying attention to. Researchers spend a lot of time collecting research-related information by accessing multiple information sources. There is a need to automatically build interest information profiles for each researcher based on personal presentation materials (papers, research projects, patents). There is a need to provide an advanced customized information service that regularly provides the latest information matched with various information sources. Continuous modification and supplementation of each researcher's information profile of interest is the most important factor in increasing suitability when searching for information. As researchers' interest in unstructured information such as technology markets and research trends is gradually increasing from standardized academic information such as patents, it is necessary to expand information sources such as cutting-edge technology markets and research trends. Through this, it is possible to shorten the time required to search and obtain the latest information for research purposes. The interest information profile for each researcher that has already been established can be used in the future to determine the degree of relationship between researchers and to build a database. If this customized information service continues to be provided, it will be useful for research activities.

• Journal of Plant Biotechnology
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• v.50
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• pp.127-136
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• 2023

Water scarcity decreases the rate of photosynthesis and, consequently, the yield of banana plants (Musa spp). In this study, transcriptome analysis was performed to identify photosynthesis-related genes in banana plants and determine their expression profiles under water stress conditions. Banana plantlets were in vitro cultured on Murashige and Skoog agar medium with and without 10% polyethylene glycol and marked as BP10 and BK. Chlorophyll contents in the plant shoots were determined spectrophotometrically. Two cDNA libraries generated from BK and BP10 plantlets, respectively, were used as the reference for transcriptome data. Gene ontology (GO) enrichment analysis was performed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID) and visualized using the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway prediction. Morphological observations indicated that water deficiency caused chlorosis and reduced the shoot chlorophyll content of banana plantlets. GO enrichment identified 52 photosynthesis-related genes that were affected by water stress. KEGG visualization revealed the pathways related to the 52 photosynthesisr-elated genes and their allocations in four GO terms. Four, 12, 15, and 21 genes were related to chlorophyll biosynthesis, the Calvin cycle, the photosynthetic electron transfer chain, and the light-harvesting complex, respectively. Differentially expressed gene (DEG) analysis using DESeq revealed that 45 genes were down-regulated, whereas seven genes were up-regulated. Four of the down-regulated genes were responsible for chlorophyll biosynthesis and appeared to cause the decrease in the banana leaf chlorophyll content. Among the annotated DEGs, MaPNDO, MaPSAL, and MaFEDA were selected and validated using quantitative real-time PCR.