• Structural Monitoring and Maintenance
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• v.5 no.2
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• pp.231-242
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• 2018

Subway tunnel structure has been rapidly developed in many cities for its strong transport capacity. The model-based damage detection of subway tunnel structure is usually difficult due to the complex modeling of soil-structure interaction, the indetermination of boundary and so on. This paper proposes a new data-based method for the damage detection of subway tunnel structure. The root mean square acceleration and cross correlation function are used to derive a statistical pattern recognition algorithm for damage detection. A damage sensitive feature is proposed based on the root mean square deviations of the cross correlation functions. X-bar control charts are utilized to monitor the variation of the damage sensitive features before and after damage. The proposed algorithm is validated by the experiment of a full-scale two-rings subway tunnel lining, and damages are simulated by loosening the connection bolts of the rings. The results verify that root mean square deviation is sensitive to bolt loosening in the tunnel lining and X-bar control charts are feasible to be used in damage detection. The proposed data-based damage detection method is applicable to the online structural health monitoring system of subway tunnel lining.

• Journal of Korean Academy of Nursing Administration
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• v.11 no.4
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• pp.371-384
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• 2005

Purpose: The aim of this study was to analysis path model of the research variables. Methods: The subjects of this study were 647 nurses who were working in the 8 general hospitals located in Seoul and Incheon area. The data were collected by self-reporting questionnaires. The data were analyzed using descriptive statistics and path analysis. Results: In the modified path model, overall fitness indexes were $X^2$= 223.27, goodness of fit index=0.90, root mean square residual=0.039, root mean square error of approximation=0.12, non-normed fit index=0.96, and normed fit index=0.90. From the model, among research variables that influence organizational effectiveness motivator, job satisfaction and organizational identification affected directly work performance. In internal marketing factors, paid-leave, communication and reward affected directly motivator. Motivator and hygiene factors affected directly job satisfaction, organizational commitment and organizational identification. Conclusion: With these findings, paid-leave, communication, reward, motivator, job satisfaction and organizational identification were direct or indirect predictors of the work performance. Therefore nursing managers ought to develop internal marketing strategies and motivation enhancing system for nurses based on this path model in order to improve the nursing organizational effectiveness.

• Advances in materials Research
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• v.11 no.1
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• pp.75-90
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• 2022

In this paper, functionality of soft computing algorithms such as Group method of data handling (GMDH), Random forest (RF), Random tree (RT), Linear regression (LR), M5P, and artificial neural network (ANN) have been looked out to predict the compressive strength of concrete mixed with marble powder. Assessment of result suggests that, the overall performance of ANN based model gives preferable results over the different applied algorithms for the estimate of compressive strength of concrete. The results of coefficient of correlation were maximum in ANN model (0.9139) accompanied through RT with coefficient of correlation (CC) value 0.8241 and minimum root mean square error (RMSE) value of ANN (4.5611) followed by RT with RMSE (5.4246). Similarly, other evaluating parameters like, Willmott's index and Nash-sutcliffe coefficient value of ANN was 0.9458 and 0.7502 followed by RT model (0.8763 and 0.6628). The end result showed that, for both subsets i.e., training and testing subset, ANN has the potential to estimate the compressive strength of concrete. Also, the results of sensitivity suggest that the water-cement ratio has a massive impact in estimating the compressive strength of concrete with marble powder with ANN based model in evaluation with the different parameters for this data set.

• The Journal of Korean Academic Society of Nursing Education
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• v.29 no.2
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• pp.148-160
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• 2023

Purpose: The purpose of this study was to construct and test a structural model of nursing students' performing communication skills. Methods: The data collection was conducted from October 13 to October 20, 2020. The participants were 286 students from nursing colleges located in three cities. The data analysis method was a covariance structure analysis with using IBM SPSS statistics version 23.0 and AMOS 21.0 statistical programs. Results: The hypothetical model showed a proper fit with the data: root mean square error of approximation=.08, standardized root mean square residual=.06, adjusted goodness of fit=.85, normed fit index=.91, and comparative fit index=.94. The model fit indices were normed to fit index=2.96. Statistically significant explanatory variables for the performing communication skills of nursing students were peer support, emotional intelligence, ethical sensitivity, and communication self-efficacy. The variables accounted for 66.1% of the performing communication skills of nursing students. Conclusion: Based on the above results, it appears necessary to develop strategies for improving the performing communication skills of nursing students, and having positive effects on health outcomes of the subjects by considering the variables of peer support, emotional intelligence, ethical sensitivity, and communication self-efficacy. Such strategies could potentially have positive effects on the health outcomes of the patients.

• Korean Journal of Environmental Agriculture
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• v.39 no.3
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• pp.204-213
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• 2020

BACKGROUND: Since the number of crops cultivated in reclaimed land is huge, it is very difficult to quantify the total crop production. Therefore, a non-destructive method for predicting crop production is needed. Salt tolerant root vegetables such as red beets and sugar beet are suitable for cultivation in reclaimed land. If their underground biomass can be predicted, it helps to estimate crop productivity. Objectives of this study are to investigate maximum leaf length and weight of red beet, sugar beet, and turnips grown in reclaimed land, and to determine optimal model with regression analysis for linear and allometric growth models. METHODS AND RESULTS: Maximum leaf length, width, and root fresh weight of red beets, sugar beets, and turnips were measured. Ten linear models and six allometric growth models were selected for estimation of root fresh weight and non-linear regression analysis was conducted. The allometric growth model, which have a variable multiplied by square of maximum leaf length and maximum leaf width, showed highest R² values of 0.67, 0.70, and 0.49 for red beets, sugar beets, and turnips, respectively. Validation results of the models for red beets and sugar beets showed the R² values of 0.63 and 0.65, respectively. However, the model for turnips showed the R² value of 0.48. The allometric growth model was suitable for estimating the root fresh weight of red beets and sugar beets, but the accuracy for turnips was relatively low. CONCLUSION: The regression models established in this study may be useful to estimate the total production of root vegetables cultivated in reclaimed land, and it will be used as a non-destructive method for prediction of crop information.

• The Korean Journal of Applied Statistics
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• v.31 no.6
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• pp.785-799
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• 2018

With the development of renewable energy sector, the importance of solar energy is continuously increasing. Solar radiation forecasting is essential to accurately solar power generation forecasting. In this paper, we used time series models (ARIMA, ARIMAX, seasonal ARIMA, seasonal ARIMAX, ARIMA GARCH, ARIMAX-GARCH, seasonal ARIMA-GARCH, seasonal ARIMAX-GARCH). We compared the performance of the models using mean absolute error and root mean square error. According to the performance of the models without exogenous variables, the Seasonal ARIMA-GARCH model showed better performance model considering the problem of heteroscedasticity. However, when the exogenous variables were considered, the ARIMAX model showed the best forecasting accuracy.

• Nuclear Engineering and Technology
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• v.53 no.12
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• pp.4179-4188
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• 2021

This study identifies efficient earthquake intensity measures (IMs) for seismic performances and fragility evaluations of the reactor containment building (RCB) in the advanced power reactor 1400 (APR1400) nuclear power plant (NPP). The computational model of RCB is constructed using the beam-truss model (BTM) for nonlinear analyses. A total of 90 ground motion records and 20 different IMs are employed for numerical analyses. A series of nonlinear time-history analyses are performed to monitor maximum floor displacements and accelerations of RCB. Then, probabilistic seismic demand models of RCB are developed for each IM. Statistical parameters including coefficient of determination (R²), dispersion (i.e. standard deviation), practicality, and proficiency are calculated to recognize strongly correlated IMs with the seismic performance of the NPP structure. The numerical results show that the optimal IMs are spectral acceleration, spectral velocity, spectral displacement at the fundamental period, acceleration spectrum intensity, effective peak acceleration, peak ground acceleration, A95, and sustained maximum acceleration. Moreover, weakly related IMs to the seismic performance of RCB are peak ground displacement, root-mean-square of displacement, specific energy density, root-mean-square of velocity, peak ground velocity, Housner intensity, velocity spectrum intensity, and sustained maximum velocity. Finally, a set of fragility curves of RCB are developed for optimal IMs.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.3
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• pp.29-41
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• 2010

In this study, the prediction errors of various spatial interpolation methods used to model values at unmeasured locations was compared and the accuracy of these predictions was evaluated. The root mean square (RMS) was calculated by processing different parameters associated with spatial interpolation by using techniques such as inverse distance weighting, kriging, local polynomial interpolation and radial basis function to known elevation data of the east coastal area under the same condition. As a result, a circular model of simple kriging reached the smallest RMS value. Prediction map using the multiquadric method of a radial basis function was coincident with the spatial distribution obtained by constructing a triangulated irregular network of the study area through the raster mathematics. In addition, better interpolation results can be obtained by setting the optimal power value provided under the selected condition.

• International Area Studies Review
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• v.22 no.3
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• pp.67-84
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• 2018

The purpose of this paper is to investigate the Balassa-Samuelson effect that real exchange rate could deviate from its long-run equilibrium. To analyze this effect, I estimated the long-run relationship between real exchange and productivity using the dynamic panel ordinary least square(DOLS) and panel error correction model(ECM) after conducting the unit root and cointegration test. The results show that all variables except for the real exchange rate have the unit root. Then I conducted the cointegration test to find out whether there exist the stable long-run relationships. The results show that the variables are cointegrated and significant statistically. The DOLS and ECM methods are used to estimate the coefficient of the cointegrated variables. The major finding are that the estimates are statistically significant and that they show the same sign as the economic theory predicts.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.1-10
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• 2024

The radio propagation characteristics of the 6, 10, and 17 GHz frequency bands in multiple paths in an indoor lobby environment were analyzed. The line-of-sight (LOS) and non-LOS (NLOS) paths were measured from a distance of 2-16 m (0.5 m intervals) from the transmitting to the receiving antenna positions. For basic transmission losses, three parameters were compared using the floating intercept path loss model corresponding to the path. For a root mean square delay spread, the measurement results were compared for cumulative probabilities of 10, 50, and 90%. Propagation loss and propagation delay occurred in all measured frequencies owing to the existence of pillars and an unusual lobby structure. Thus, a measurement scenario for an indoor lobby environment and the provision of standard measurement data was proposed. The results may facilitate research on the radio propagation characteristics of 5G and millimeter-wave bands in indoor lobby environments with various structures.