• The Journal of Korean Society for School & Community Health Education
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• v.20 no.2
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• pp.109-124
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• 2019

Purpose: The purpose of this study was to compare the happiness level of one-person households according to gender in Korea and identify factors influencing householders' happiness. Methods: This was a descriptive correlational study design using the 2017 Community Health Survey data. The participants were 8,724 male and 16,810 female individuals in one-person households. Complex samples descriptive statistics, cross analysis, general linear model, and multi-order regression were conducted to identify the health status, health behavior, and factors influencing happiness. Results: The mean score of happiness was higher in female than male individuals. The main factors of happiness of male householders were suicide thought experience, subjective health level, and experience of having necessary medical services. The main factors of happiness of female householders were suicide thought experience, household income, depression experience. Conclusion: It is necessary to develop and implement nursing interventions and policies according to priorities for the happiness of one-person householders.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.56-56
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• 2023

남양호는 농업용수 공급을 위해 건설된 하구 담수호로 과도한 영양물질 축적으로 인해 매년 여름 녹조류가 번성한다. 따라서 본 연구에서는 조류발생 특성을 분석하고자 식물성 플랑크톤 및 관련 분해 산물에 의해 고유 광학특성을 가지고 있는 Chlorophyll-a(Chl-a)의 추정을 통한 녹조 발생을 파악하고자 Sentinel-2 Multi Spectral Image(MSI)의 원격 반사율 광학 스펙트럼을 사용하였다. Chl-a 추정알고리즘 개발을 위하여 Sentinel-2 A, B의 교차 방문주기인 5일 간격에 맞추어 현장수질자료(2022년: 27회 2023년: 27회)를 측정하였다. Chl-a 농도는 EXO-YSI를이용하여 측정하였으며 해당기간동안 9.4 ~ 127.1 mg/L의 범위를 보였으며, Sentine-2 자료는 A, B자료에서 B1(443 nm) ~ B8A(865 nm)파장의 값을 기상조건(구름, 안개, 강수)을 고려하여 현장수질측정 위치에서 반사도를 추출하였다. 입력자료는 대기 및 방사영향을 고려해 반사도 간의 비율자료와 선행연구에서 활용된 반사도를 활용하였으며 알고리즘은 다중선형회귀분석(Multi Linear Regression Model)과 Random Forest를 활용하였다. MLR의 경우 결정계수(R2)가 학습 및 검증에서 각각 0.68, 0.59의 성능을 보였으며, RF의 경우 각각 0.94, 0.85의 성능을 보였다. 해당알고리즘으로 생성된 Chl-a 시공간농도 자료는 담수호내 조류발생 특성을 분석하고 효율적 조류관리 및 대처에 활용될 것으로 판단된다.

• Applied Chemistry for Engineering
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• v.33 no.6
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• pp.563-573
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• 2022

This work aimed to develop a new equation for turbidity (Turb) simulation and prediction using statistical methods based on principal component analysis (PCA) and multiple linear regression (MLR). For this purpose, water samples were collected monthly over a five year period from Cheurfa dam, an important reservoir in Northwestern Algeria, and analyzed for 12 parameters, including temperature (T°), pH, electrical conductivity (EC), turbidity (Turb), dissolved oxygen (DO), ammonium (NH₄⁺), nitrate (NO₃^-), nitrite (NO₂^-), phosphate (PO₄^3-), total suspended solids (TSS), biochemical oxygen demand (BOD₅) and chemical oxygen demand (COD). The results revealed a strong mineralization of the water and low dissolved oxygen (DO) content during the summer period. High levels of TSS and Turb were recorded during rainy periods. In addition, water was charged with phosphate (PO₄^3-) in the whole period of study. The PCA results revealed ten factors, three of which were significant (eigenvalues >1) and explained 75.5% of the total variance. The F1 and F2 factors explained 36.5% and 26.7% of the total variance, respectively and indicated anthropogenic pollution of domestic agricultural and industrial origin. The MLR turbidity simulation model exhibited a high coefficient of determination (R² = 92.20%), indicating that 92.20% of the data variability can be explained by the model. TSS, DO, EC, NO₃^-, NO₂^-, and COD were the most significant contributing parameters (p values << 0.05) in turbidity prediction. The present study can help with decision-making on the management and monitoring of the water quality of the dam, which is the primary source of drinking water in this region.

• Journal of Preventive Medicine and Public Health
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• v.43 no.6
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• pp.479-485
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• 2010

Objectives: The Korean Genome and Epidemiology Study (KoGES), a multicenter-based multi-cohort study, has collected information on body composition using two different bioelectrical impedence analysis (BIA) machines. The aim of the study was to evaluate the possibility of whether the test values measured from different BIA machines can be integrated through statistical adjustment algorithm under excellent inter-rater reliability. Methods: We selected two centers to measure inter-rater reliability of the two BIA machines. We set up the two machines side by side and measured subjects' body compositions between October and December 2007. Duplicated test values of 848 subjects were collected. Pearson and intra-class correlation coefficients for inter-rater reliability were estimated using results from the two machines. To detect the feasibility for data integration, we constructed statistical compensation models using linear regression models with residual analysis and R-square values. Results: All correlation coefficients indicated excellent reliability except mineral mass. However, models using only duplicated body composition values for data integration were not feasible due to relatively low $R^2$ values of 0.8 for mineral mass and target weight. To integrate body composition data, models adjusted for four empirical variables that were age, sex, weight and height were most ideal (all $R^2$ > 0.9). Conclusions: The test values measured with the two BIA machines in the KoGES have excellent reliability for the nine body composition values. Based on reliability, values can be integrated through algorithmic statistical adjustment using regression equations that includes age, sex, weight, and height.

• Journal of the Korean Applied Science and Technology
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• v.39 no.3
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• pp.433-441
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• 2022

The purpose of this study is to investigate the relationship between media engagement, media empathy, and media value of MCN sports broadcasting. To achieve this purpose, a survey was conducted on 324 MCN sports broadcast viewers. Exploratory factor analysis was performed to confirm validity, and Cronbach's α test was performed to investigate reliability. In addition, correlation analysis was performed to verify discriminant validity, and linear regression analysis was performed to verify the research hypothesis, and the following conclusions were drawn. Media engagement had a positive effect on media value. Media engagement had a positive effect on media empathy. Media empathy has a positive effect on media value.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.29 no.3
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• pp.162-168
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• 2017

Shallow-water bathymetry survey has been conducted using high definition color images obtained at the altitude of 100 m above sea level using a drone. Shallow-water bathymetry data are one of the most important input data for the research of beach erosion problems. Especially, accurate bathymetry data within closure depth are critically important, because most of the interesting phenomena occur in the surf zone. However, it is extremely difficult to obtain accurate bathymetry data due to wave-induced currents and breaking waves in this region. Therefore, optical remote sensing technique using a small drone is considered to be attractive alternative. This paper presents the potential utilization of image processing algorithms using multi-variable linear regression applied to red, green, blue and grey band images for estimating shallow water depth using a drone with HD camera. Optical remote sensing analysis conducted at Wolpo beach showed promising results. Estimated water depths within 5 m showed correlation coefficient of 0.99 and maximum error of 0.2 m compared with water depth surveyed through manual as well as ship-board echo-sounder measurements.

• Geomechanics and Engineering
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• v.39 no.1
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• pp.1-11
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• 2024

Geotechnical parameter estimation is critical to the design, performance, safety, and cost and schedule management in Tunnel Boring Machine projects. Since these parameters vary within a certain range, relying on mean values for evaluation introduces significant risks to the project. Due to the non-homogeneous characteristics of geological formation, data may not exhibit a normal distribution and the presence of outliers might be deceptive. Therefore, the use of reliable analyses and simulation models is inevitable in the course of the data evaluation process. Advanced modeling techniques enable comprehensive analysis of the project data and allowing to model the uncertainty in geotechnical parameters. This study involves using Monte Carlo Simulation method to predict probabilistic distributions of field data, and therefore, establish a basis for designs and in turn to minimize project risks. In the study, 166 sets of geotechnical data Obtained from 35 boreholes including Standard Penetration Test, Limit Pressure, Liquid Limit, and Plastic Limit values, which are mostly utilized parameters in estimating project requirements, were used to estimate the geotechnical data distribution of the study field. In this context, firstly, the data was subjected to multi-parameter linear regression and variance analysis. Then, the obtained equations were implemented into a Monte Carlo Simulation, and probabilistic distributions of the geotechnical data of the field were simulated and corresponding to the 90% probability range, along with the minimum and maximum values at the 5% probability levels presented. Accordingly, while the average SPT N30 value is 42.86, but the highest occurrence rate is 50.81. For Net Limit Pressure, the average field data is 17.07 kg/cm², with the maximum occurrence between 9.6 kg/cm² and 13.7 kg/cm². Similarly, the average Plastic Limit value is 22.32, while the most probable value is 20.6. The average Liquid Limit value is 56.73, with the highest probability at 54.48, as indicated in the statistical data distribution. Understanding the percentage distribution of data likely to be encountered in the project allows for accurate forecasting of both high and low probability scenarios, offering a significant advantage, particularly in ordering TBM requirements.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.544-552
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• 2019

The purpose of this study was to find concrete measures to improve the subjective health level, happiness and quality of life of the elderly according to economic level and to propose social and policy alternatives accordingly. As a research method, 63,929 elderly people aged 65 or older were surveyed using the Community Health Survey (Indicator Bank) _v09, and the frequency of health use by economic level, subjective health level, euphoria and quality of life Analysis and Chi square analysis and independent t-test. Multi variate logistic regression analysis was performed with subjective health level as a dependent variable and multiple linear regression analysis was performed to determine the factors affecting euphoria and quality of life. The results of the study are as follows. In the case of recipients, medical use was lower than that of non-recipients, lower education level, female age of 75 years or older, and less stress, In case of present or past recipients, the result of non - receipt increased as the subjective health level was worse, and the non - recipient had higher euphoria and quality of life. As a result, there is a need for alternatives to increase opportunities for medical use among the recipients, with particular attention being paid to women and elderly people over 75 years old. It is expected to be used as a basic data to effectively improve the health promotion, happiness and quality of life of the elderly people of low income group.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.14 no.1
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• pp.179-193
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• 1994

In the development of engineering designs, decisions are required irrespective of the state of completeness and quality of information, and are formulated under conditions of uncertainty. Furthermore, under conditions of uncertainty the design invokes risks. Thus, in the design of the structures, the currently used deterministic design method does not provide a realistic assessment of the actual safety or the reliability of the structures. It is desirable that decisions required in The process of the design invariably must be made based on the reliability analysis. Properties of soil material are subject to more uncertainty than those of other structural material. In the field of soil mechanics and foundation engineering, it needed to develop reliability-based design methods. In order to simplify the reliability analysis or the reliability-based design process of the structures associated with the active earth pressure, it is necessary to find the variation and the distribution type of the active earth pressure calculated from the basic properties of soils. Monte Carlo simulation is performed to obtain the relationship between the variation of the active earth pressure for cohessionless soils calculated by using Rankine formula and the basic soil properties and the distribution type of the earth pressure. A series of regression equations obtained by utilizing the multi-linear regression analysis is suggested in this paper and the sensitivity of the basic soil properties to the variation of The earth pressure is investigated. The type of distribution of the active earth pressure was found to be the beta distribution in most cases or to be very similar to the beta distribution, if the basic soil variables are normally distributed.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.9 no.3
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• pp.119-128
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• 2014

One of the theoretically and empirically grounded black boxes in HRD and firm performance link is employee' attitudes such as organizational commitment and job satisfaction. However, most studies were conducted with the regression analysis at the organizational level. This study used HLM(hierarchical linear modeling) analysis, which made it possible to estimate more accurate relationship between variables that were measured from two different levels. In addition, this study attempted to open an the black box(learning culture) in the relationship between HRD and employee attitudes. The result showed that the HRD have a positive effect on the organizational commitment and the job satisfaction. Also the HRD showed full mediation effect of organization commitment and the job satisfaction on the Learning culture. And the result showed that the HRD in 2007 have a positive effect on employee' attitudes in 2009. These findings concluded that systematic HRD like employee's education and training must be built and also the positive culture for employee's learning like support of management's learning organization must be improved in order to promote the organizational performance(organizational commitment, job satisfaction) in company.