• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.1009-1029
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• 2023

Urban trees play a vital role in urban ecosystems,significantly reducing impervious surfaces and impacting carbon cycling within the city. Although previous research has demonstrated the efficacy of employing artificial intelligence in conjunction with airborne light detection and ranging (LiDAR) data to generate urban tree information, the availability and cost constraints associated with LiDAR data pose limitations. Consequently, this study employed freely accessible, high-resolution multispectral satellite imagery (i.e., Sentinel-2 data) to estimate fractional tree canopy cover (FTC) within the urban confines of Suwon, South Korea, employing machine learning techniques. This study leveraged a median composite image derived from a time series of Sentinel-2 images. In order to account for the diverse land cover found in urban areas, the model incorporated three types of input variables: average (mean) and standard deviation (std) values within a 30-meter grid from 10 m resolution of optical indices from Sentinel-2, and fractional coverage for distinct land cover classes within 30 m grids from the existing level 3 land cover map. Four schemes with different combinations of input variables were compared. Notably, when all three factors (i.e., mean, std, and fractional cover) were used to consider the variation of landcover in urban areas(Scheme 4, S4), the machine learning model exhibited improved performance compared to using only the mean of optical indices (Scheme 1). Of the various models proposed, the random forest (RF) model with S4 demonstrated the most remarkable performance, achieving R² of 0.8196, and mean absolute error (MAE) of 0.0749, and a root mean squared error (RMSE) of 0.1022. The std variable exhibited the highest impact on model outputs within the heterogeneous land covers based on the variable importance analysis. This trained RF model with S4 was then applied to the entire Suwon region, consistently delivering robust results with an R² of 0.8702, MAE of 0.0873, and RMSE of 0.1335. The FTC estimation method developed in this study is expected to offer advantages for application in various regions, providing fundamental data for a better understanding of carbon dynamics in urban ecosystems in the future.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.933-948
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• 2023

Atmospheric aerosols not only have adverse effects on human health but also exert direct and indirect impacts on the climate system. Consequently, it is imperative to comprehend the characteristics and spatiotemporal distribution of aerosols. Numerous research endeavors have been undertaken to monitor aerosols, predominantly through the retrieval of aerosol optical depth (AOD) via satellite-based observations. Nonetheless, this approach primarily relies on a look-up table-based inversion algorithm, characterized by computationally intensive operations and associated uncertainties. In this study, a novel high-resolution AOD direct retrieval algorithm, leveraging machine learning, was developed using top-of-atmosphere reflectance data derived from the Geostationary Ocean Color Imager-II (GOCI-II), in conjunction with their differences from the past 30-day minimum reflectance, and meteorological variables from numerical models. The Light Gradient Boosting Machine (LGBM) technique was harnessed, and the resultant estimates underwent rigorous validation encompassing random, temporal, and spatial N-fold cross-validation (CV) using ground-based observation data from Aerosol Robotic Network (AERONET) AOD. The three CV results consistently demonstrated robust performance, yielding R²=0.70-0.80, RMSE=0.08-0.09, and within the expected error (EE) of 75.2-85.1%. The Shapley Additive exPlanations(SHAP) analysis confirmed the substantial influence of reflectance-related variables on AOD estimation. A comprehensive examination of the spatiotemporal distribution of AOD in Seoul and Ulsan revealed that the developed LGBM model yielded results that are in close concordance with AERONET AOD over time, thereby confirming its suitability for AOD retrieval at high spatiotemporal resolution (i.e., hourly, 250 m). Furthermore, upon comparing data coverage, it was ascertained that the LGBM model enhanced data retrieval frequency by approximately 8.8% in comparison to the GOCI-II L2 AOD products, ameliorating issues associated with excessive masking over very illuminated surfaces that are often encountered in physics-based AOD retrieval processes.

• Journal of Korean Public Health Nursing
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• v.5 no.2
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• pp.45-51
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• 1991

The purpose of this study is to investigate the stress and coping level as a result of dysmenorrhea which was experienced by girls. For the collection of data, the girls from the 1st to the 3rd grade in middle school in Seoul were selected through a random sampling technique. The survey was conducted from the 1st. to the 14th of June, 1991 by the use of questionnaires made after a pilot study. The final subjects for analysis were restricted to only those who had experienced me~arche, the number of which totaled 1,131. The stress, coping level, and other variables, were tested and analysed by descriptive statistics (eg, frequency, percentage, mean and standard deviation), t-test, ANOVA and Pearson's correlation coefficients. The obtained results are summarized as follows. 1. The chronological start for menarche was at a mean age of 13.1 The respondents who had experienced menarche numbered $70.9\%$ of the 1st grades and $96.2\%$ of the 2nd grades in middle school, otherwise the starting age for menarche was in the 4th grade in primary school. 2. Their menstrual cycle and period were longer than adult's one. The number of students studied who had experienced dysmenorrhea during their menstrual cycle were 860, and 650 of those revealed that their mothers or sisters had experienced similar problems. 3. The subjects who were late or head left early rather than being absent from school every menstruation cycle were more stressful. The results are thought to show that the girl's perception of dysmenorrhea seems to be more sensitive than adult's one. 4, A significant negative correlation was found between the perception of menstrual flow and strees level. It means that an increase in the stress of dysmenorrhea was associated with decreased menstrual bleeding. The degree of hypochondrical concern assessed by the girls was significantly correlated to stress and coping level. When the girls perceived high stress as a result of dysmenorrhea, they worried about their physical health more. The above results lead us to the suggestion that the starting point of early education with a school program is appropriate for the 4th grade in primary school. Especially if the girls in middle school should be required to give the information about correct knowledge and sufficient self -care management of menstruation monthly, if this could be implemented the loss in school days among the students due to dysmenorrhea would be minimized with more ease.

• The Journal of Industrial Distribution & Business
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• v.9 no.3
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• pp.81-87
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• 2018

Purpose - The perception of the quality of the consumer's distributor's brand(PBs) is generally perceived to be lower than that of the manufacturer's brand(NB), although it is a critical factor in determining the success of PBs. Accordingly, this study examines the characteristics of the convenience store PB products and their correlation with brand trust and purchase intent in the consumers who have had experience purchasing the convenience store PBs to expand the sales variables. Further, this research shows that the marketing strategy is to increase the share of PBs by providing an empirical analysis on the effect of the product attribute factors on the sales volume associated with brand trust, purchase intent, and others. Research design, data, and methodology - The survey period of this study was approximately three weeks from December 1, 2017 to December 21, 2017. The study samples that were taken from 100 random people extracted. The statistical analysis was carried out with multiple regression analysis using the SPSS statistical package. Results - The analysis shows that the brand credibility and purchasing intention were statistically significant differences between the private convenience store private brand products. Specifically, brand trust showed a statistically significant relationship the brand images and quality levels, but the perceived value was not affected statistically. Although the intent of the purchase showed a statistically significant relationship the quality level and the perceived value, the brand image was not statistically significant in its relationship. Conclusions - Overall, it has been established that the perception value does not statistically affect brand trust for convenience store PB products, and that the brand image has no statistically significant effect on the purchase intent. These results are analyzed to be due to the influence of brand in convenience stores themselves rather than brand trust and purchase intentions that affect sales performance, which is the property of private brand food and beverage products, the perceived value of their products. Accordingly, the study found that not only did the marketing performance of the convenience store PB products be improved statistically, but also the cause of the product attributes that were not statistically significant was identified.

• Wind and Structures
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• v.34 no.1
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• pp.127-136
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• 2022

In this work a multi-fidelity non-intrusive polynomial chaos (MF-NIPC) has been applied to a structural wind engineering problem in architectural design for the first time. In architectural design it is important to design structures that are safe in a range of wind directions and speeds. For this reason, the computational models used to design buildings and bridges must account for the uncertainties associated with the interaction between the structure and wind. In order to use the numerical simulations for the design, the numerical models must be validated by experi-mental data, and uncertainties contained in the experiments should also be taken into account. Uncertainty Quantifi-cation has been increasingly used for CFD simulations to consider such uncertainties. Typically, CFD simulations are computationally expensive, motivating the increased interest in multi-fidelity methods due to their ability to lev-erage limited data sets of high-fidelity data with evaluations of more computationally inexpensive models. Previous-ly, the multi-fidelity framework has been applied to CFD simulations for the purposes of optimization, rather than for the statistical assessment of candidate design. In this paper MF-NIPC method is applied to flow around a rectan-gular 5:1 cylinder, which has been thoroughly investigated for architectural design. The purpose of UQ is validation of numerical simulation results with experimental data, therefore the radius of curvature of the rectangular cylinder corners and the angle of attack are considered to be random variables, which are known to contain uncertainties when wind tunnel tests are carried out. Computational Fluid Dynamics (CFD) simulations are solved by a solver that employs the Finite Element Method (FEM) for two turbulence modeling approaches of the incompressible Navier-Stokes equations: Unsteady Reynolds Averaged Navier Stokes (URANS) and the Large Eddy simulation (LES). The results of the uncertainty analysis with CFD are compared to experimental data in terms of time-averaged pressure coefficients and bulk parameters. In addition, the accuracy and efficiency of the multi-fidelity framework is demonstrated through a comparison with the results of the high-fidelity model.

• Journal of agricultural medicine and community health
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• v.29 no.1
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• pp.1-14
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• 2004

Objectives: We investigated the factors related to health examination behaviors, sociodemographic aspects and lifestyles of elderly persons with different social backgrounds, and compared sexual and regional differences in urban and rural elderlies. Methods: The total study subjects(464 individuals) from urban(236) and rural areas(228), recruited by a stratified cluster random sampling were interviewed and examined about their sociodemographic profiles, daily lifestyles, subjective health status, conditions concerning use of medical resources, hearing acuity, visual acuity and ADL(activity of daily living), and whether they receive health examination or not. For statistical analysis, Chi-square test was used for sexual and regional comparisons among the groups who have been given a health examination and the one who have not. Results: In urban areas, the rate of having underwent health examination was 54.5% in men and 46.9% in women, and in rural areas, it was 59.8% in men and 42.7% in women, showing its higher rate in men than in women in both areas. For regional differences between the group who have taken a health examination and the one who have not, there was a significant difference in terms of age, family pattern, current job, monthly household income, owning a house, drinking status, eating habit, subjective health status, whether they have taken outpatient medical service for the recent 3 months or not, anxiety for the health, and IADL conditions according to whether the community is rural or urban. In multiple regressions, the influential factors on the health examination behaviors were selected such as having their own house, their family doctor, amnesia, urinary incontinence and chronic disease in urban districts. But in rural districts, the variables were selected such as having or not of their family doctor, urinary incontinence, anxiety for the health, educational level, their own house and chronic disease. Conclusions: It is suggested that the approach to the health examination of an older patient requires substantial consideration of highly variable individual sociodemographic characteristics involving regional attributes as well as their daily life styles, subjective health status, status of performing health examination, physical health status and ADL conditions.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.4
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• pp.161-173
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• 2020

As ICT convergence technology has spread and applied to various industrial fields and society in general, interest in rural entrepreneurship using smart farm as a means for solving many pending problems in agriculture is increasing. In this context, this study is to look at the influential factors in terms of perceived usefulness associated with the rural entrepreneurial intention using smart farm and suggest a proposal for spreading smart farms. The subjects were 296 general adults over 20 years old who were selected by simple random sampling method. The research method was exploratory factor analysis and multiple regression analysis using IBM SPSS 22.0. The perceived usefulness of smart farm, which are availability, reliability and economic efficiency were selected as independent variables to analyze the influential factors on rural entrepreneurial intention using smart farm and the moderating effect of personal innovation was observed. As a result, reliability and economic efficiency have a positive(+) influence on rural entrepreneurial intention using smart farm. And personal innovation moderates the relationship between the availability, reliability of smart farm and rural entrepreneurial intention using smart farm. The results of this study have significance in that we devised and empirically revealed factors affecting rural entrepreneurship intentions from the perspective of perceived usefulness of smart farms, away from studies of general entrepreneurship intention factors such as internal personal characteristics and external environmental factors. The implications of the study are expected to be utilized at the seeking direction of policy for potential entrepreneur using smart farm, the training and consulting in actual field of smart farm.