• Water for future
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• v.29 no.2
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• pp.235-247
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• 1996

Meteorological and soil water content data measured from semiarid watersheds of Lucky Hills and Kendall during the summer rainy and winter periods were used to study the interrelationships between the controlling variables of the evapotranspiration, and to evaluate the effects of variables on daily actual evapotranspiration (ET) estimation. Simple and multiple linear regression (MLR) analyses were employed to evaluate the order of importance of the meteorological and soil water factors involved. The information gained was used for MLR model development. Theavailable energy and vapor pressure deficit were found to be the important variables to estimate actual ET (AET) for both periods and at both watersheds. Therefore, the important variables of evapotranspiration process in these semiarid watersheds appear to be simply the components of energy term in available energy and aerodynamic term in vapor pressure deficit of Penman potential evapotranspiration (PET) equation.

• Journal of Korean Academy of Nursing
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• v.50 no.5
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• pp.728-736
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• 2020

Purpose: This study aimed to identify the relationship between workplace violence and turnover intention, and the mediation effect of resilience on the relationship in hospital nurses. Methods: This was a cross-sectional study. A total of 237 registered nurses were recruited from three hospitals in South Korea from April to May 2019. Participants were invited to complete self-reported questionnaires that measure workplace violence, turnover intention, resilience, and demographic information. The data obtained were analyzed using multiple regression and a simple mediation model applying the PROCESS macro with 95% bias-corrected bootstrap confidence interval (5,000 bootstrap resampling). Results: After controlling demographic covariates, workplace violence significantly accounted for the variance of turnover intention. It was also demonstrated that resilience partially mediated the relationship between workplace violence and turnover intention in hospital nurses. A 73.8% of nurses had experienced workplace violence (such as attack on personality, attack on professional status, isolation from work, or direct attack). Conclusion: Workplace violence directly influences turnover intention of nurses and indirectly influences it through resilience. Therefore, hospital administrators need to develop and provide a workplace violence preventive program and resilience enhancement program to decrease nurses' turnover intention, and leaving.

• Korean Journal of Remote Sensing
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• v.25 no.6
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• pp.487-499
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• 2009

Atmospheric correction of satellite measurements is a major step to estimate accurate surface reflectance of solar spectrum channels. In this study, Simplified Method for the Atmospheric Correction (SMAC) radiative transfer model used to retrieve surface reflectance from MODIS (MODerate resolution Imaging Spectrometer) top of atmosphere (TOA) reflectance. It is fast and simple atmospheric correction method, so it uses for work site operation in various satellite. This study attempts a test of accuracy of SMAC through a sensitivity test to detected error sources and to improve accuracy of surface reflectance using SMAC. The results of SMAC as compared with MODIS surface reflectance (MOD09) was represented that low accuracy ($R^2\;=\;0.6196$, Root Means Square Error (RMSE) = 0.00031, bias = - 0.0859). Thus sensitivity analysis of input parameters and coefficients was conducted to searching error sources. Among the input parameters, Aerosol Optical Depth (AOD) is the most influence input parameter. In order to modify AOD term in SMAC code, Stepwise multiple regression was performed with testing and remove variable in three stages with independent variables of AOD at 550nm, solar zenith angle, viewing zenith angle. Surface reflectance estimation by using Newly proposed AOD term in the study showed that improve accuracy ($R^2\;=\;0.827$, RMSE = 0.00672, bias = - 0.000762).

• Journal of Internet of Things and Convergence
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• v.9 no.1
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• pp.105-115
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• 2023

This study seeks to find a way to induce users to expand their direct participation in sports through the acceptance of digital technology. From July 1 to August 30, 2022, a survey was conducted targeting home training users who applied the Internet of Things (IoT). 129 people participated in the survey through non-face-to-face self-administration method. For data processing, frequency analysis, exploratory factor analysis, reliability analysis, correlation analysis, multiple regression analysis, and 3-step mediation regression analysis were conducted using IBM's SPSS 21.0 program. The results of the study are as follows. First, in the relationship between the home training PPM model and direct participation in sports, ease appeared to have a mediating effect. In the factors of push, simple functionality showed a complete mediating effect, and inefficiency showed a partial mediating effect. Among pull factors, enjoyment and possibility of experience showed a complete mediating effect. In the mooring factors, individual innovativeness showed a complete mediating effect. Second, in the relationship between home training PPM model and direct participation in sports, usefulness showed a mediating effect. In the factors of push, simple functionality showed a complete mediating effect, and inefficiency showed a partial mediating effect. Among pull factors, enjoyment and possibility of experience showed a complete mediating effect. Among the mooring factors, individual innovativeness showed a partial mediating effect. Through this research, it is expected that the sports industry will contribute to the expansion of consumption expenditure and economic growth through the expansion of digital technologies such as NFT, Metaverse, and virtual/augmented reality.

• The Korean Journal of Franchise Management
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• v.11 no.4
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• pp.7-15
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• 2020

Purpose: The purpose of this study is to clarify the role of decoupling between job characteristics, innovation behavior, and innovation resistance in order to seek ways for companies to survive and grow continuously through innovation activities in various uncertain situations. Research design, data and methodology: A total of 263 valid questionnaires were collected and used for analysis for employees working at the company. For the analysis, simple and multiple regression analysis, and 3-step mediated regression analysis were conducted using SPSS 24.0 and AMOS 24.0. Results: First, it was found that skill variety, task identity, autonomy, and feedback increase decoupling, and decoupling increases innovation resistance. In addition, it was confirmed that decoupling had a mediating effect between job characteristics and innovation resistance excluding task significance. Finally, it was found that task significance and feedback increase innovation behavior, and decoupling and task identity increase innovation resistance, but feedback can alleviate innovation resistance. Conclusions: As a result of the analysis, the fact that job characteristics excluding task importance have a positive effect on decoupling means that there are two sides of job characteristics perceived by employees. In other words, it means that the results of analysis on the jobs that the company assigns to its members may not be effective. In addition, decoupling, a phenomenon that seems to be accepting on the outside, but perceives that it is negative on the inside, means that there is a possibility to reject innovation. Therefore, prior to carrying out innovation activities, companies should give clear job specifications and meanings for the job and give them autonomy when assigning jobs to their members. In order to provide appropriate feedback, the company must design, operate, and provide feedback. It was found that there was a need to review the overall effectiveness. In addition, efforts such as strengthening corporate-level fairness, maintaining psychological contracts, and realizing authentic leadership should be preceded to reduce decoupling.

• Journal of Korea Water Resources Association
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• v.43 no.12
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• pp.1083-1091
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• 2010

Distributed hydrologic models typically require spatial estimates of precipitation interpolated from sparsely located observational points to the specific grid points. However, widely used estimation schemes fail to describe the realistic variability of daily precipitation field. We compare and contrast the performance of statistical methods for the spatial estimation of precipitation in two hydrologically different basins, and propose a two-step process for effective daily precipitation estimation. The methods assessed are: (1) Inverse Distance Weighted Average (IDW); (2) Multiple Linear Regression (MLR); (3) Climatological MLR; and (4) Locally Weighted Polynomial Regression (LWP). In the suggested simple two-step estimation process, precipitation occurrence is first generated via a logistic regression model before applying IDW scheme (one of the local scheme) to estimate the amount of precipitation separately on wet days. As the results, the suggested method shows the better performance of daily rainfall interpolation which has spatial differences compared with conventional methods. And this technique can be used for streamflow forecasting and downscaling of atmospheric circulation model effectively.

• Journal of Korea Society of Industrial Information Systems
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• v.13 no.3
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• pp.38-53
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• 2008

This study focuses on identifying motivation factors affecting knowledge sharing behavior in virtual communities. To achieve this research objective, a research model has been developed through two major coordinated theories such as social cognitive theory(self-efficacy and community-related outcome expectation) and social exchange theory (codification effort, image, reciprocity, and enjoyment in helping others). 246 samples have been collected and simple regression and multiple regression methods have been used for empirical analysis. The research result is that self-efficacy has a positive influence on image, reciprocity, enjoyment in helping others, and community-related outcome expectation and thus this result reveals that self-efficacy indirectly affects knowledge sharing behavior. Among the antecedents of knowledge sharing behavior, codification effort, enjoyment in helping others and community-related outcome expectation are significant, but image and reciprocity are not. The research results help to derive practical strategic implications related to knowledge sharing to activate a virtual community.

• Asian-Australasian Journal of Animal Sciences
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• v.17 no.12
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• pp.1736-1740
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• 2004

Since the application of relatively high levels of heavy metals in the compost poses a potential hazard to plants and animals, the content of heavy metals in the compost with animal manure is important to know if it is as a fertilizer. Measurement of heavy metals content in the compost by chemical methods usually requires numerous reagents, skilled labor and expensive analytical equipment. The objective of this study, therefore, was to explore the application of near-infrared reflectance spectroscopy (NIRS), a nondestructive, cost-effective and rapid method, for the prediction of heavy metals contents in compost. One hundred and seventy two diverse compost samples were collected from forty-seven compost facilities located along the Han river in Korea, and were analyzed for Cr, As, Cd, Cu, Zn and Pb levels using inductively coupled plasma spectrometry. The samples were scanned using a Foss NIRSystem Model 6500 scanning monochromator from 400 to 2,500 nm at 2 nm intervals. The modified partial least squares (MPLS), the partial least squares (PLS) and the principal component regression (PCR) analysis were applied to develop the most reliable calibration model, between the NIR spectral data and the sample sets for calibration. The best fit calibration model for measurement of heavy metals content in compost, MPLS, was used to validate calibration equations with a similar sample set (n=30). Coefficient of simple correlation (r) and standard error of prediction (SEP) were Cr (0.82, 3.13 ppm), As (0.71, 3.74 ppm), Cd (0.76, 0.26 ppm), Cu (0.88, 26.47 ppm), Zn (0.84, 52.84 ppm) and Pb (0.60, 2.85 ppm), respectively. This study showed that NIRS is a feasible analytical method for prediction of heavy metals contents in compost.

• Smart Structures and Systems
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• v.11 no.4
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• pp.411-433
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• 2013

Due to its easy operation and wide applicability, the ambient vibration method is commonly adopted to determine the cable force by first identifying the cable frequencies from the vibration signals. With given vibration length and flexural rigidity, an analytical or empirical formula is then used with these cable frequencies to calculate the cable force. It is, however, usually difficult to decide the two required parameters, especially the vibration length due to uncertain boundary constraints. To tackle this problem, a new concept of combining the modal frequencies and mode shape ratios is fully explored in this study for developing an accurate method merely based on ambient vibration measurements. A simply supported beam model with an axial tension is adopted and the effective vibration length of cable is then independently determined based on the mode shape ratios identified from the synchronized measurements. With the effective vibration length obtained and the identified modal frequencies, the cable force and flexural rigidity can then be solved using simple linear regression techniques. The feasibility and accuracy of the proposed method is extensively verified with demonstrative numerical examples and actual applications to different cable-stayed bridges. Furthermore, several important issues in engineering practice such as the number of sensors and selection of modes are also thoroughly investigated.

• Communications for Statistical Applications and Methods
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• v.24 no.3
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• pp.241-254
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• 2017

Drawing a sample can be costly or time consuming in some studies. However, it may be possible to rank the sampling units according to some baseline auxiliary covariates, which are easily obtainable, and/or cost efficient. Ranked set sampling (RSS) is a method to achieve this goal. In this paper, we propose a modified approach of the RSS method to allocate units into an experimental study that compares L groups. Computer simulation estimates the empirical nominal values and the empirical power values for the test procedure of comparing L different groups using modified RSS based on the regression approach in analysis of covariance (ANCOVA) models. A comparison to simple random sampling (SRS) is made to demonstrate efficiency. The results indicate that the required sample sizes for a given precision are smaller under RSS than under SRS. The modified RSS protocol was applied to an experimental study. The experimental study was designed to obtain a better understanding of the pathways by which positive experiences (i.e., goal completion) contribute to higher levels of happiness, well-being, and life satisfaction. The use of the RSS method resulted in a cost reduction associated with smaller sample size without losing the precision of the analysis.