• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.101-101
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• 2020

Traditional stochastic simulation of hydroclimatological variables often underestimates the variability and correlation structure of larger timescale due to the difficulty in preserving long-term memory. However, the Long Short-Term Memory (LSTM) model illustrates a remarkable long-term memory from the recursive hidden and cell states. The current study, therefore, employed the LSTM model in stochastic generation of hydrologic and climate variables to examine how much the LSTM model can preserve the long-term memory and overcome the drawbacks of conventional time series models such as autoregressive (AR). A trigonometric function and the Rössler system as well as real case studies for hydrological and climatological variables were tested. Results presented that the LSTM model reproduced the variability and correlation structure of the larger timescale as well as the key statistics of the original time domain better than the AR and other traditional models. The hidden and cell states of the LSTM containing the long-memory and oscillation structure following the observations allows better performance compared to the other tested conventional models. This good representation of the long-term variability can be important in water manager since future water resources planning and management is highly related with this long-term variability.

• Research in Community and Public Health Nursing
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• v.27 no.4
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• pp.309-318
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• 2016

Purpose: This study investigated the correlation between person-centered care (PCC) and nursing service quality of nurses in long-term care hospitals. Methods: The subjects were 114 nurses working in 8 long-term care hospitals. Instruments for evaluating PCC and nursing service quality were used. The data were analyzed by descriptive statistics, two samples-test, one-way ANOVA, Pearson's correlation and Multiple regression. Results: The mean of PCC was $3.25{\pm}0.45$ out of 5 and the nursing service quality was $3.87{\pm}0.40$. There were significant differences in PCC in terms of age and income satisfaction, the application of their opinions, the satisfaction of hospital managers, administrators and nurse managers. There were significant differences in nursing service quality according to age, position, the satisfaction of hospital managers, administrators and nurse managers. Nurses' PCC showed a significant positive correlation with nursing service quality. Factors influencing nursing service quality included PCC, their position and age and the most influencing one was PCC. Conclusion: This study suggests that the PCC is the strongest affecting element to the quality of nursing service in long-term care hospitals. Therefore, the strategies to improve the practice of person-centered care should be carried out to enhance the quality of nursing service.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.4
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• pp.1271-1279
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• 2013

In this paper, a study on the prediction method of basic wind speed at the construction site of long-span bridge using short-term measurements was conducted. To determine the basic wind speed in the wind resistant design for the long-span bridge away from the weather station, statistical analysis of long-term data at site is required. Wind observation mast was installed at site, and short-term measurements were gathered and the correlation analysis between the site and the station was done using regression analysis and MCP(Measure-Correlate-Predict). The long-term wind data of the site was obtained from correlation formula after topographical revision of long-term data of the station. And basic wind speed could be estimated by extreme probability distribution analysis. The research results show that the wind speed by regression analysis is predicted lower than by MCP and after this study a series of correlation analyses at several sites will show clearly the difference two methods. And also a quality control of long-term wind data is very important in estimation of wind speed.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2003.09a
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• pp.565-569
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• 2003

One-year-long groundwater-level data have been collected from 18 wells in Cheon-an area. The result of barometric efficiency, autocorrelation, cross-correlation and statistical distribution evaluated from the measurement data shows that groundwater-level measurements from observation wells are the principal source of information about aquifer characteristics. Data from WA-2 has high barometric efficiency as well as steady decreasing auto-correlation coefficient, which means nonleaky confined aquifer, Most aquifers in this study show the unconfined properties so that barometric efficiencies are mostly low and the coefficients of cross-correlation between groundwater-level and precipitation are commonly high. This study showed that the long-term groundwater-level monitoring data without artificial stress such as pumping would give accurate information about aquifer characteristics.

• Journal of Engineering Education Research
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• v.21 no.1
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• pp.44-55
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• 2018

The purpose of this study is to investigate the relationship between post - employment job satisfaction and both short-term (4-12 weeks) and long-term (12+weeks) on-site training. For this purpose, 405 graduates who had completed on-site training (205 short-term, 200 long term) during the school year were surveyed. The results of the comparative analysis of both short-term and long-term on-site training participants are as follows: In both short-term and long-term on-site training, it was found that on-site performance during the school year did not directly affect post-employment job satisfaction. In the case of short-term on-site training participants, job match and organizational commitment were found to have no mediating effect on the correlation between on-site training performance and job satisfaction. On the other hand, in the case of long-term on-site training participants, the analysis showed that job match and organizational commitment had mediating effects on the correlation between on-site training performance and job satisfaction. These effects are not solely attributable to differences in duration of training; the differences in operating systems and the degree of preparation derived from these systems also affect the level of on-site training for students, businesses, and schools. This paper summarizes these findings and suggests the following improvement plans for on-site training in the future: First, short-term on-site training is required to establish a systematic basis in order to enhance students' preparedness level. Second, both short-term and long-term on-site training should improve the skills and field understanding for students' majors through systematic quality management during the training period. Third, it is necessary for universities to increase expectations and quality of short-term on-site training for all involved while simultaneously reducing the gap between educational goals and practice in this field.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.49 no.8
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• pp.380-389
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• 2000

This paper presents a method for the regional long-term load forecasting in metropolitan area considering econimic indicator with the assumption that energy demands propoprtionally increases under the economic indicators. For the accurate load forecasting, it is very important to scrutinize the correlation among the regional electric power demands, economic indicator and other characteristics because load forecasting results may vary depending on many different factors such as electric power demands, gross products, social trend and so on. Three steps for the regional long-term load forecasting are microscopically and macroscopically used for the regional long -term load forecasting in order to increase the accuracy and practicality of the results.

• Journal of Information Processing Systems
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• v.14 no.6
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• pp.1508-1520
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• 2018

In this paper, we propose an improved model to provide users with a better long-term prediction of waterworks operation data. The existing prediction models have been studied in various types of models such as multiple linear regression model while considering time, days and seasonal characteristics. But the existing model shows the rate of prediction for demand fluctuation and long-term prediction is insufficient. Particularly in the deep running model, the long-short-term memory (LSTM) model has been applied to predict data of water purification plant because its time series prediction is highly reliable. However, it is necessary to reflect the correlation among various related factors, and a supplementary model is needed to improve the long-term predictability. In this paper, convolutional neural network (CNN) model is introduced to select various input variables that have a necessary correlation and to improve long term prediction rate, thus increasing the prediction rate through the LSTM predictive value and the combined structure. In addition, a multiple linear regression model is applied to compile the predicted data of CNN and LSTM, which then confirms the data as the final predicted outcome.

• Korean Journal of Occupational Health Nursing
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• v.31 no.4
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• pp.178-186
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• 2022

Purpose: The purpose of this study is to identify the relationship between professional self-concept and job satisfaction of nurses working in long-term care hospitals and to consider strategies to improve these factors. Methods: Data were collected using structured questionnaires given to 135 nurses working at six long-term care hospitals in C City. The data were analyzed with SPSS 23.0 by descriptive statistics, Cronbach's α, t-test, one-way ANOVA, a Scheffé test, and with Pearson's correlation coefficient. Results: The average score for professional self-concept was 2.78 points (out of 4 points), and the average score for job satisfaction was 3.11 points (out of 5 points). Significant differences were found for professional self-concept according to age, marriage status, total work experience, number of patients per nurse, and position, while job satisfaction showed significant differences depending on age and the number of patients in the ward. Professional self-concept and job satisfaction showed a significant positive correlation (r=.46, p<.001). Conclusion: In long-term care hospitals, it is necessary to provide education programs about nursing practice, communication, and leadership to enhance the professional self-concept of nurses. With regard to job satisfaction for nurses, it is imperative to improve the work environment of long-term care hospitals.

• Journal of Environmental Impact Assessment
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• v.6 no.2
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• pp.81-92
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• 1997

This paper presents the results from the comparison analysis and evaluation between the air pollutant dispersion modeling results and the observation data in the area within a 10 km radius from the Boryong thermal power plants. The observation data used in this study were the air pollutant concentrations which had been continuously measured from 8 locations around the Boryong power plants by TMS(tele-monitoring system) for 3 months from September to November, 1996. The short-term and long-term predictions were carried out using ISC3 model and LPDM(Lagrangian Panicle Dispersion Model). The results of ISC3 modeling in a short-term showed highly as 0.7 in a correlation coefficient, but in a long-term showed just 0.54. On the other hand, LPDM showed 0.78 in a correlation coefficient for a long-term, but in a short-term showed highly value than the observation concentrations.

• Investigative Magnetic Resonance Imaging
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• v.22 no.3
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• pp.158-167
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• 2018

Purpose: To investigate the surgical, perfusion, and molecular characteristics of glioblastomas which influence long-term survival after treatment, and to explore the association between MR perfusion parameters and the presence of MGMT methylation and 1p/19q deletions. Materials and Methods: This retrospective study was approved by our institutional review board. A total 43 patients were included, all with pathologic diagnosis of glioblastoma with known MGMT methylation and 1p/19q deletion statuses. We divided these patients into long-term (${\geq}60\;months$, n = 7) and short-term (< 60 months, n = 36) survivors, then compared surgical extent, molecular status, and rCBV parameters between the two groups using Fisher's exact test or Mann-Whitney test. The rCBV parameters were analyzed according to the presence of MGMT methylation and 1p/19q deletions. We investigated the relationship between the mean rCBV and overall survival using linear correlation. Multivariable linear regression was performed in order to find the variables related to overall survival. Results: Long-term survivors (100% [7 of 7]) demonstrated a greater percentage of gross total or near total resection than short-term survivors (54.5% [18 of 33]). A higher prevalence of 1p/19q deletions was also noted among the long-term survivors (42.9% [3 of 7]) than the short-term survivors (0.0% [0 of 36]). The rCBV parameters did not differ between the long-term and short-term survivors. The rCBV values were marginally lower in patients with MGMT methylation and 1p/19q deletions. Despite no correlation found between overall survival and rCBV in the whole group, the short-term survivor group showed negative correlation ($R^2=0.181$, P = 0.025). Multivariable linear regression revealed that surgical extent and 1p/19q deletions, but not rCBV values, were associated with prolonged overall survival. Conclusion: While preoperative rCBV and 1p/19q deletion status are related to each other, only surgical extent and the presence of 1p/19q deletion in GBM patients may predict long-term survival.