• Journal of Korean Clinical Nursing Research
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• v.25 no.3
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• pp.221-236
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• 2019

Purpose: The purpose of this study was to systematically review and identify factors relevant to the positive psychological capital of clinical nurses. Methods: These was no limit on year of publication. Articles related to Korean clinical nurses were retrieved from computerized database using a manual search. A systematic review was conducted based on the PRISMA flow. The total correlational effect size (ESr) for each related factor was calculated from Fisher's Zr. Funnel plots, fail-safe numbers, and Egger regression tests were used to evaluate publication bias in meta-analysis studies. The correlational effect size of 25 studies was analyzed through meta-analysis using Comprehensive Meta-Analysis software 3.0 (CMA). Results: The review included 25 studies. In the systematic review, 14 demographic factors and 46 organizational factors were found to be influential. Eleven factors (6 demographic factors and 5 organizational factors) were appropriate for meta-analysis. The overall effect size was .26. The demographic total correlation effect size of related factors was .20 and the total effect size of organization was .46. Organizational commitment (ESr=.38) and job satisfaction (ESr=.54) were statistically positively related variables. Negative variables were burnout (ESr=-.61), turnover intention (ESr=-.41) and workplace bullying (ESr=-.33). The total effect size of the organizational factors was larger than the demographic total effect size. There was no publication bias except for demographic variables. Conclusion: Organizational factors and adjustable variables have a significant impact on positive psychological capital. The results of this study support the need for development of interventions focusing on organizational factors.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.51-51
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• 2017

지역빈도해석은 짧은 기간의 자료를 보유하고 있는 계측 지점이나 자료가 없는 미계측 지점에서의 확률수문량을 산정하기 위하여 많이 쓰여 진다. 지역빈도해석을 실시하기 위한 조건으로는 우선 수집된 하천유역들을 대상으로 수문학적 동질 지역을 구분하는 것이 중요하다. 그리고 구분되어진 지역에 포함되는 모든 지점들의 자료를 빈도해석 함으로써 관심 지점의 신뢰할 만한 확률수문량을 산정하는 것이다. 그동안의 지역빈도해석은 주로 비건조지역을 중심으로 홍수와 같은 재난재해 대비 그리고 수자원 관리를 위한 연구들을 실시해왔다. 본 연구의 주 목적은 건조지역의 수자원 관리를 위해 건조지역 하천유역을 중심으로 지역빈도해석을 실시하여 신뢰할만한 확률수문량을 산정하는 것이다. 확률수문량 산정값의 정확도를 향상시키기 위해 지역빈도해석 모델에 쓰여 지는 새로운 지형학적 변수들을 제공하였고 수문학적 동질 지역을 구분 위해 수집된 각 하천유역의 형상들을 확인하여 동질 지역을 정의하였다. 예를 들면, 수지형 유역, 부채형 유역, 격자형 유역과 같은 다른 형상들을 구분하여 각 유역 형상 종류별로 동질 지역을 만들었다. 건조지역의 지역빈도해석을 위해 미국 건조지역의 105개 하천유역 유량자료들을 수집 및 이용하였다. 확률수문량 산정을 위하여 앙상블 인경신경망 (Ensemble Artificial Neural Network)과 정준 상관 계수(Canonical Correlation Analysis)를 이용한 지역빈도해석 모델을 만들었다. 제안된 모델의 수행평가와 정확성 평가를 위해 리샘플링 기법인 10-겹 교차 검증 (10-fold cross-validation), 잭나이프 (Jackknife) 기법들을 이용하였고 모델로부터 산정된 확률수문량값을 편향 (Bias), 상대 편향(rBias), 평균 제곱근 오차 (RMSE), 상대 평균 제곱근 오차 (rRMSE)를 통하여 산정 값과 실제 관측 값의 차이를 분석하였다. 그 결과 건조지역의 지역빈도해석을 위해 새롭게 제시된 지형학적 변수들을 사용하였을 때 모델의 수행능력이 향상되었음을 확인하였다. 또한 하천유역 형상에 따라 동질 지역을 구분하였을 때 향상된 확률수문량이 산정되었다. 향상된 지역빈도해석 모델을 통해 건조지역의 신뢰할만한 확률수문량을 산정함으로써 건조지역의 효과적인 수자원 관리를 위한 수공시설물 설계에 중요한 정보들을 제공할 것이다.

• Journal of the Korean Society of Clothing and Textiles
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• v.45 no.6
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• pp.978-985
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• 2021

This study aims to propose a prediction model for the drape coefficient using artificial neural networks and to analyze the nonlinear relationship between the drape properties and physical properties of fabrics. The study validates the significance of each factor affecting the fabric drape through multiple linear regression analysis with a sample size of 573. The analysis constructs a model with an adjusted R² of 77.6%. Seven main factors affect the drape coefficient: Grammage, extruded length values for warp and weft (m_warp, m_weft), coefficients of quadratic terms in the tensile-force quadratic graph in the warp, weft, and bias directions (c_warp, c_weft, c_bias), and force required for 1% tension in the warp direction (f_warp). Finally, an artificial neural network was created using seven selected factors. The performance was examined by increasing the number of hidden neurons, and the most suitable number of hidden neurons was found to be 8. The mean squared error was .052, and the correlation coefficient was .863, confirming a satisfactory model. The developed artificial neural network model can be used for engineering and high-quality clothing design. It is expected to provide essential data for clothing appearance, such as the fabric drape.

• Journal of Korean Biological Nursing Science
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• v.25 no.3
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• pp.160-171
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• 2023

Purpose: To identify factors influencing health-related quality of life for young single-person households, this study investigated physical and mental health status, health behavior, depression, resilience, and health-related quality of life. Methods: An online survey was administered to members of young single-person households from March 22 to 30, 2022. The data were analyzed using the chi-square test, independent t-test, one-way analysis of variance, Pearson correlation coefficients, multiple regression, and a simple mediation model applying the PROCESS macro model 4 with 95% bias-corrected bootstrapped confidence intervals. Results: The participants were 229 members of young single-person households. Health-related quality of life showed significant relationships with residence (t = 2.80, p = .006), month (F = 3.70, p = .026), mental health status (F = 20.33, p < . 001), and high-intensity exercise (F = 7.35, p = .001) among general and health-related characteristics. Health-related quality of life had significant correlations with depression (r = -.72, p < .001) and resilience (r = .58, p < .001). Multiple regression analysis showed that depression (β = -.57, p < .001) and resilience (β = .21, p < .001) influenced health-related quality of life. Moreover, resilience had a mediating effect between depression and health-related quality of life (indirect effect = -0.002, 95% bias-corrected bootstrapped confidence interval = -0.003 to -0.001). Conclusion: Members of young single-person households tended to be more vulnerable to emergency situations, such as during the coronavirus disease 2019 pandemic, when lockdowns and quarantines were frequent. To improve health-related quality of life in young single-person households, people with high levels of depression or low levels of resilience need special attention and support to promote mental health.

• Journal of Cardiovascular Imaging
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• v.31 no.3
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• pp.135-141
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• 2023

BACKGROUND: Global longitudinal strain (GLS) is an accurate and reproducible parameter of left ventricular (LV) systolic function which has shown meaningful prognostic value. Fast, user-friendly, and accurate tools are required for its widespread implementation. We aim to compare a novel web-based tool with two established algorithms for strain analysis and test its reproducibility. METHODS: Thirty echocardiographic datasets with focused LV acquisitions were analyzed using three different semi-automated endocardial GLS algorithms by two readers. Analyses were repeated by one reader for the purpose of intra-observer variability. CAAS Qardia (Pie Medical Imaging) was compared with 2DCPA and AutoLV (TomTec). RESULTS: Mean GLS values were -15.0 ± 3.5% from Qardia, -15.3 ± 4.0% from 2DCPA, and -15.2 ± 3.8% from AutoLV. Mean GLS between Qardia and 2DCPA were not statistically different (p = 0.359), with a bias of -0.3%, limits of agreement (LOA) of 3.7%, and an intraclass correlation coefficient (ICC) of 0.88. Mean GLS between Qardia and AutoLV were not statistically different (p = 0.637), with a bias of -0.2%, LOA of 3.4%, and an ICC of 0.89. The coefficient of variation (CV) for intra-observer variability was 4.4% for Qardia, 8.4% 2DCPA, and 7.7% AutoLV. The CV for inter-observer variability was 4.5%, 8.1%, and 8.0%, respectively. CONCLUSIONS: In echocardiographic datasets of good image quality analyzed at an independent core laboratory using a standardized annotation method, a novel web-based tool for GLS analysis showed consistent results when compared with two algorithms of an established platform. Moreover, inter- and intra-observer reproducibility results were excellent.

• Advances in materials Research
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• v.13 no.1
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• pp.63-86
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• 2024

Asphalt concrete (AC), is a mixture of bitumen and aggregates, which is very sensitive in the design of flexible pavement. In this study, the Marshall stability of the glass and carbon fiber bituminous concrete was predicted by using Artificial Neural Network (ANN), Support Vector Machine (SVM), Random Forest (RF), and M5P Tree machine learning algorithms. To predict the Marshall stability, nine inputs parameters i.e., Bitumen, Glass and Carbon fibers mixed in 100:0, 75:25, 50:50, 25:75, 0:100 percentage (designated as 100GF:0CF, 75GF:25CF, 50GF:50 CF, 25GF:75CF, 0GF:100CF), Bitumen grade (VG), Fiber length (FL), and Fiber diameter (FD) were utilized from the experimental and literary data. Seven statistical indices i.e., coefficient of correlation (CC), mean absolute error (MAE), root mean squared error (RMSE), relative absolute error (RAE), root relative squared error (RRSE), Scattering index (SI), and BIAS were applied to assess the effectiveness of the developed models. According to the performance evaluation results, Artificial neural network (ANN) was outperforming among other models with CC values as 0.9147 and 0.8648, MAE values as 1.3757 and 1.978, RMSE values as 1.843 and 2.6951, RAE values as 39.88 and 49.31, RRSE values as 40.62 and 50.50, SI values as 0.1379 and 0.2027 and BIAS value as -0.1 290 and -0.2357 in training and testing stage respectively. The Taylor diagram (testing stage) also confirmed that the ANN-based model outperforms the other models. Results of sensitivity analysis showed that the fiber length is the most influential in all nine input parameters whereas the fiber combination of 25GF:75CF was the most effective among all the fiber mixes in Marshall stability.

• The Journal of the Korea Contents Association
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• v.12 no.6
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• pp.380-389
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• 2012

In this study, Systematic review and meta-analysis using the correlation coefficients was carried out to integrate precedent studies on factors affecting domestic occupational therapists' job stress. It aims at providing basic information resources of preventing and reducing stress of occupational therapists and effective counter-measurement to improve quality of occupational therapy and to establish efficient human resource management policy. Systematic review and meta-analysis were performed on eight thesis proven relevant to selection criteria in order to figure out correlation coefficients value by total, and factors correlation coefficients value. Also homogeneity test and publication bias test was performed too. The total correlation coefficients value of occupational therapists was .30 which was statistically significant. As to job stress factors, the organization related factor showed the highest correlation of coefficiency, followed by factors other than the organization related, physical environment, job related factor and personal factor. This research result can be used as a reference to prevent and reduce job stress of occupational therapists and to develop an effective measurement scheme.

• Journal of Venture Innovation
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• v.2 no.2
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• pp.117-126
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• 2019

This study conducted correlation analysis and multiple regression analysis using financial statements, loan structure, ROA and ROA volatility of domestic commercial banks, regional banks and special banks for the past five years (2012 ~ 2016). The result is as follows. First, as a result of correlation analysis, bank's ROA is positively related to household loans and SME loans, but it is negatively correlated with the ratio of loans to large companies, sector bias, and loan loss provision ratio. Second, ROA volatility was negatively related to household loans and SME loans, but it was positively correlated with large corporate loans, sector bias ratio, and loan loss provision ratio. Third, as a result of the regression analysis, the variables that have a statistically significant effect on the ROA volatility of banks were household loans, SME loans, and large enterprise loans. From these empirical results, special banks with high volatility in profits need to diversify loan types and sectors in order to achieve business performance outside of policy finance. and Especially, Suhyup Bank and Nonghyup Bank, which have a large commercial role, have a large size per unit by focusing on short-term profit and Rather than focusing on large companies or large loans that are easy to obtain financial information, it is necessary to focus management capabilities on household loans and SME loans by developing capabilities such as screening techniques.

• Journal of Life Science
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• v.20 no.11
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• pp.1738-1741
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• 2010

Caliper measurements of tumor volume have been widely used in the assessment of tumors in animal models. However, experiments based on caliper data have resulted in unreliable estimates of tumor growth, due to necrotic areas of tumor mass. To overcome this systematic bias, we engineered a new luciferase-expressing rat prostate cancer cell line (MLL-Luc) that produces bioluminescence from viable cancer cells. MLL-Luc cells showed a strong correlation between bioluminescence intensity and cell number ($R^2$=0.99) and also accurately quantified tumor growth, with reduced bioluminescence signals caused by necrotic cells in a subcutaneous MLL-Luc xenograft model. The accurate quantification of tumor growth with bioluminescence imaging (BLI) was confirmed by a better antitumor effect of combination chemotherapy, compared to that based on caliper measurements with a correlation between the bioluminescence signal and tumor volume ($R^2$=0.84). These data suggest that bioluminescent MLL xenografts are a powerful and quantitative tool for monitoring tumor growth and are useful in evaluating the efficacy of anticancer drugs, with less systematic bias.

• Journal of Radiation Protection and Research
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• v.36 no.4
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• pp.223-229
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• 2011

Ba is the most useful element to get the $Ba(Ra)SO_4$ precipitate. However, when the high concentrations of ions such as sulfate, calcium are existed in the leachate of phosphogypsum stack, it is difficult to get the $Ba(Ra)SO_4$ precipitate. Since this reason, the developed method for the Ba coprecipitate using EDTA was performed to determine the $^{226}Ra$ concentration in the high sulfate sample. The average concentration of $^{226}Ra$ in a leachate of phosphogypsum using this method was 0.102 $Bq{\cdot}kg^{-1}$ and the minimal detectable activity is 3.4 $mBq{\cdot}kg^{-1}$. The $mBq{\cdot}kg^{-1}$ method was 0.102 $Bq{\cdot}kg^{-1}$ and the minimal detectable activity is 3.4 $mBq{\cdot}kg^{-1}$. The $^{226}Ra$ stock solution and the CRM (Certified Reference Material) were analyzed to verify this method. In analyzed $^{226}Ra$ stock solution, bias with added concentration was approximately 1% and the correlation curve between $^{226}Ra$ concentration in simulated standard sample and measured $^{226}Ra$ concentration showed good agreement with a correlation coefficient ($R^2$) of 0.99. In analyzed CRM, maximum bias with reference value was 5.8% (k=1) and the analytical results were in good agreement with the reference value.