• Journal of Environmental Science International
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• v.24 no.4
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• pp.437-447
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• 2015

Estimation of runoff peak is needed to assess water availability, in order to support the multifaceted water uses and functions, hence to underscore the modalities for efficient water utilization. The magnitude of storm rainfall acts as a primary input for basin level runoff computation. The rainfall-runoff linkage plays a pivotal role in water resource system management and feasibility level planning for resource distribution. Considering this importance, a case study has been carried out in the Hancheon basin of Jeju Island where distinctive hydrological characteristics are investigated for continuous storm rainfall and high permeable geological features. The study aims to estimate unit hydrograph parameters, peak runoff and peak time of storm rainfalls based on Clark unit hydrograph method. For analyzing observed runoff, five storm rainfall events were selected randomly from recent years' rainfall and HEC-hydrologic modeling system (HMS) model was used for rainfall-runoff data processing. The simulation results showed that the peak runoff varies from 164 to 548 m3/sec and peak time (onset) varies from 8 to 27 hours. A comprehensive relationship between Clark unit hydrograph parameters (time of concentration and storage coefficient) has also been derived in this study. The optimized values of the two parameters were verified by the analysis of variance (ANOVA) and runoff comparison performance were analyzed by root mean square error (RMSE) and Nash-Sutcliffe efficiency (NSE) estimation. After statistical analysis of the Clark parameters significance level was found in 5% and runoff performances were found as 3.97 RMSE and 0.99 NSE, respectively. The calibration and validation results indicated strong coherence of unit hydrograph model responses to the actual situation of historical storm runoff events.

• Journal of Korean Academy of Nursing
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• v.47 no.5
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• pp.700-711
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• 2017

Purpose: This study aimed to test a proposed structural equation model in which bullying experience, conflict management styles and psychological empowerment predict psychological well-being among Chinese nursing students in clinical placement. Methods: Three hundred and sixty-six nursing students recruited from five hospitals in J city and Y city were assessed with self-report questionnaires on bullying experience, conflict management styles, psychological empowerment and psychological well-being including depression, self-esteem, and academic major satisfaction. Data were analyzed using SPSS version 20.0 and AMOS version 22.0. Results: The evaluation parameters included the comparative fit index at .90, the goodness of fit index at .93, the root mean square error of approximation at .07, and ${\chi}^2/df$ ratio at 2.66, indicating that the proposed structural equation model provided a good fit to the data. Experience of being bullied during clinical placement, conflict management styles and psychological empowerment explained 93.0% of the variance and had significant effects on psychological well-being, with conflict management styles and psychological empowerment mediating the association between bullying and psychological well-being. Conclusion: The findings indicated that mediation by conflict management styles and psychological empowerment alleviated the negative influence of bullying on psychological well-being. To limit bullying and its negative effects, development of effective guidelines to deal with bullying will be a critical tool for both Chinese nursing students and their instructors. Further research should incorporate conflict management styles and psychological empowerment into the specific intervention strategies for handling bullying behaviors among nursing students and staff nurses and promoting nursing students' psychological well-being.

• Industrial Engineering and Management Systems
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• v.4 no.1
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• pp.54-67
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• 2005

This paper provides an evaluation of an optimization-based, multiple-input double-output (MIDO) run-to-run (R2R) control scheme for general semiconductor manufacturing processes. The controller in this research, termed adaptive dual response optimizing controller (ADROC), can serve as a process optimizer as well as a recipe regulator between consecutive runs of wafer fabrication. In evaluation, it is assumed that the equipment model could be appropriately described by a pair of second-order polynomial functions in terms of a set of controllable variables. Of practical relevance is to consider a drifting effect in the equipment model since in common semiconductor practice the process tends to drift due to machine aging and tool wearing. We select a typical application of R2R control to chemical mechanical planarization (CMP) in semiconductor manufacturing in this evaluation, and there are five different CMP process scenarios demonstrated, including mean shift, variance increase, and IMA disturbances. For the controller, ADROC, an on-line estimation technique is implemented in a self-tuning (ST) control manner for the adaptation purpose. Subsequently, an ad hoc global optimization algorithm based on the dual response approach, arising from the response surface methodology (RSM) literature, is used to seek the optimum recipe within the acceptability region for the execution of next run. The main components of ADROC are described and its control performance is assessed. It reveals from the evaluation that ADROC can provide excellent control actions for the MIDO R2R situations even though the process exhibits complicated, nonlinear interaction effects between control variables, and the drifting disturbances.

• The Korean Journal of Applied Statistics
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• v.28 no.2
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• pp.289-294
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• 2015

Linear mixed models are commonly used in the clinical pharmaceutical studies to analyze repeated measures such as the crossover study data of bioequivalence studies. In these models, random effects describe the correlation between repeated outcomes and variance-covariance matrix explain within-subject variabilities. Bioequivalence analysis verifies whether a 90% confidence interval for geometric mean ratio of Cmax and AUC between reference drug and test drug is included in the bioequivalence margin [0.8, 1.25] performed using linear mixed models with period, sequence and treatment effects as fixed and sequence nested subject effects as random. A Levofloxacin study is referred to for an example of real data analysis.

• Child Health Nursing Research
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• v.25 no.2
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• pp.234-243
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• 2019

Purpose: The purpose of this study was to investigate associations between self-management and diabetes knowledge, diabetes-related attitudes, family support, and self-efficacy in adolescents with type 1 diabetes mellitus based on the information-motivation-behavior skills model. Methods: Data collection was conducted between March 18 and September 30, 2018. Patients (N=87) aged 12 to 19 years were recruited from the outpatient clinic of S children's hospital and an online community for patient with type 1 diabetes mellitus. Data were analyzed using descriptive statistics, the independent t-test, one-way ANOVA, Pearsons correlation, and hierarchical multiple linear regression with SPSS IBM 23.0, with the two-tailed level of significance set at 0.05. Results: The mean score of self-management in adolescents with type 1 diabetes mellitus was $61.23{\pm}10.00$ out of 80. The regression analysis showed that self-efficacy and family support significantly explained 56.9% of the variance in self-management (F=21.38, p<.001). Self-efficacy (${\beta}=.504$, p<.001) and family support (${\beta}=.188$, p<.001) were significant predictors of self-management. Conclusion: It is necessary to develop individual interventions to improve self-efficacy and family support for adolescents with type 1 diabetes mellitus to help them enhance their self-management.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.905-915
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• 2021

This study examines the relationship between financial behavior, financial literacy, self-efficacy, and self-coping among emerging adults. The study population is 790 respondents from 11 Credit Counselling and Debt Management (CCDM). Statistical Package for Social Science (SPSS) was used to analyze Pearson Correlation and Multiple regression. It was used to determine the relationships and recognize determinants of emerging adults' financial behavior respectively. In this study, financial literacy, self-efficacy, self-coping, and financial behavior variables were entered into the regression. A total of 790 respondents aged 40 and below were selected. An independent sample t-test was administered to compare the financial behavior scores for females and males. The results reveal that there was significant difference in the mean of financial behavior scores for females (M = 87.20, SD = 18.00) and males (M = 89.70, SD = 16.80; t (765) = 2.010, p = 0.045, two-tailed). The multiple regression results indicate that the model explained 13.4% of the variance in financial behavior, which is predicted significantly by the model (F = 38.361, p = 0.000). This study will be beneficial to policymakers to improve living conditions and to promote good financial behavior, financial literacy, self-efficacy as well as self-coping especially for emerging adults in Malaysia.

• The Journal of Economics, Marketing and Management
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• v.6 no.4
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• pp.1-16
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• 2018

Purpose - This study will investigate and identify the relationship between brand image, brand attitude and intent to purchase based on subjects that have remembered or watched more than one storytelling marketing ad related to airlines. The purpose of the project is to secure market competitiveness by presenting the basis for and use of the marketing strategy using storytelling, which can capture the goodwill of the aerospace competition market in the future. Research, design, data, and methodology - Prior to the research model and hypothesis testing phase, a verification factor analysis was conducted to assess internal consistency among each measurement item and to ensure reliability and validity of the measurement tool. Further, the organization was assessed for validity by calculating the mean variance estimation (AVE) and the construction concept reliability (CCR) through a positive factor analysis. Hypothesis verification was analyzed through a structural equation model, and each concept set in the hypothesis was entered as a potential variable, and each measurement item was entered as an observation variable. Results - Airline's storytelling marketing has a significant impact on the brand image and two emotional and cognitive responses have been shown to influence the brand image. In addition, airline storytelling marketing has a significant impact on brand attitudes and airline storytelling marketing derived from factor analysis has shown two emotional and cognitive responses to brand attitudes. Conclusions - The parts derived based on the research results show that storytelling marketing has a strong influence on the airline's brand image and attitude, and that it is necessary for airlines to have a brand image and attitude. Also, forming a favorable brand image has a significant impact on brand attitudes. We believe that by presenting basic data to the aviation industry in future research on airline storytelling, we will be able to increase understanding and contribution to development of storytelling marketing in aviation.

• Steel and Composite Structures
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• v.49 no.3
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• pp.337-348
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• 2023

Successive wetting and drying cycles of concrete due to weather changes can endanger the safety of engineering structures over time. Considering wetting and drying cycles in concrete tests can lead to a more correct and reliable design of engineering structures. This study aims to provide a model that can be used to estimate the resistance properties of concrete under different wetting and drying cycles. Complex sample preparation methods, the necessity for highly accurate and sensitive instruments, early sample failure, and brittle samples all contribute to the difficulty of measuring the strength of concrete in the laboratory. To address these problems, in this study, the potential ability of six machine learning techniques, including ANN, SVM, RF, KNN, XGBoost, and NB, to predict the concrete's tensile strength was investigated by applying 240 datasets obtained using the Brazilian test (80% for training and 20% for test). In conducting the test, the effect of additives such as glass and polypropylene, as well as the effect of wetting and drying cycles on the tensile strength of concrete, was investigated. Finally, the statistical analysis results revealed that the XGBoost model was the most robust one with R2 = 0.9155, mean absolute error (MAE) = 0.1080 Mpa, and variance accounted for (VAF) = 91.54% to predict the concrete tensile strength. This work's significance is that it allows civil engineers to accurately estimate the tensile strength of different types of concrete. In this way, the high time and cost required for the laboratory tests can be eliminated.

• Management & Information Systems Review
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• v.33 no.1
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• pp.139-155
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• 2014

This study is to examine the linkage of volatility between changes in the stock market of India and other countries through the integration of the world economy. The results were as follows: First, autocorrelation or serial correlation did not exist in the classic RS model, but long-term memory was present in the modified RS model. Second, unit root did not exist in the unit root test for all periods, and the series were a stable explanatory power and a long-term memory with the normal conditions in the ARFIMA model. Third, in the multivariate asymmetric BEKK and VAR model before the financial crisis, it showed that there was a strong influence of the own market of Taiwan and UK in the conditional mean equation, and a strong spillover effect from Japan to India, from Taiwan to China(Korea, US), from US(Japan) to UK in one direction. In the conditional variance equation, GARCH showed a strong spillover effect that indicated the same direction as the result of ARCH coefficient of the market itself. Asymmetric effects in three home markets and between markets existed. Fourth, after the financial crisis, in the conditional mean equation, only the domestic market in Taiwan showed strong influences, and strong spillover effects existed from India to US, from Taiwan to Japan, from Korea to Germany in one direction. In the conditional variance equation, strong spillover effects were the same as the result of the pre-crisis and asymmetric effect in the domestic market in UK was present, and one-way asymmetric effect existed in Germany from Taiwan. Therefore, the results of this study presented the linkage between the volatilities of the stock market of India and other countries through the integration of the world economy, observing and confirming the asymmetric reactions and return(volatility) spillover effects between the stock market of India and other countries.

• Journal of Korea Water Resources Association
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• v.55 no.7
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• pp.545-556
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• 2022

It is recommended to use long-term hydrometeorological data for more than the service life of the hydraulic structures and water resource planning. For the purpose of expanding rainfall data, stochastic simulation models, such as Modified Bartlett-Lewis Rectangular Pulse (BLRP) and Neyman-Scott Rectangular Pulse (NSRP) models, have been widely used. The optimal parameters of the model can be estimated by repeatedly comparing the statistical moments defined through a combination of parameters of the probability distribution in the optimization context. However, parameter estimation using relatively small observed rainfall statistics corresponds to an ill-posed problem, leading to an increase in uncertainty in the parameter estimation process. In addition, as shown in previous studies, extreme values are underestimated because objective functions are typically defined by the first and second statistical moments (i.e., mean and variance). In this regard, this study estimated the parameters of the NSRP model using the objective function with the third moment and compared it with the existing approach based on the first and second moments in terms of estimation of extreme rainfall. It was found that the first and second moments did not show a significant difference depending on whether or not the skewness was considered in the objective function. However, the proposed model showed significantly improved performance in terms of estimation of design rainfalls.