• Nuclear Engineering and Technology
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• v.53 no.8
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• pp.2767-2773
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• 2021

We used the GEANT4 Monte Carlo MC Toolkit to simulate carbon ion beams incident on water, tissue, and bone, taking into account nuclear fragmentation reactions. Upon increasing the energy of the primary beam, the position of the Bragg-Peak transfers to a location deeper inside the phantom. For different materials, the peak is located at a shallower depth along the beam direction and becomes sharper with increasing electron density NZ. Subsequently, the generated depth dose of the Bragg curve is then benchmarked with experimental data from GSI in Germany. The results exhibit a reasonable correlation with GSI experimental data with an accuracy of between 0.02 and 0.08 cm, thus establishing the basis to adopt MC in heavy-ion treatment planning. The Kolmogorov-Smirnov K-S test further ascertained from a statistical point of view that the simulation data matched the experimentally measured data very well. The two-dimensional isodose contours at the entrance were compared to those around the peak position and in the tail region beyond the peak, showing that bone produces more dose, in comparison to both water and tissue, due to secondary doses. In the water, the results show that the maximum energy deposited per fragment is mainly attributed to secondary carbon ions, followed by secondary boron and beryllium. Furthermore, the number of protons produced is the highest, thus making the maximum contribution to the total dose deposition in the tail region. Finally, the associated spectra of neutrons and photons were analyzed. The mean neutron energy value was found to be 16.29 MeV, and 1.03 MeV for the secondary gamma. However, the neutron dose was found to be negligible as compared to the total dose due to their longer range.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.2
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• pp.97-104
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• 2019

The purpose of this study was to establish the estimation method of irrigation water amount for sewage treated water reuse for agricultural purpose. To calculate the irrigation water amount, we adopted Penman-Monteith for potential evapotranspiration estimation and applied crop coefficient and irrigation efficiency factor. We developed the irrigation water amount calculation program using C language in Xcode environment. The target district for calculation is having 259 ha of agricultural land located near the Jinyeong Clear Water Circulation Center in Hanrim-myeon, Gimhae city. The meteorological data of the study area were obtained from Changwon weather station from 1986 to 2017. Calculated average and maximum of annual mean potential evapotranspiration were 2.72 mm/day and 6.22 mm/day, respectively. We used K-S (Kolmogorov-Smirnov) for goodness-of-fit test to find optimal probability distribution of annual mean and maximum evapotranspiration. As a result, the normal distribution was selected for the appropriate distribution. The annual mean and maximum potential evapotranspiration for 10-year return period by applying normal distribution were 2.88 mm/day and 6.76 mm/day, respectively. Assuming that the irrigation efficiency is 80%, the irrigation water requirement was calculated as $36.05m^3/day/ha$ and $84.45m^3/day/ha$, respectively, when annual mean and maximum potential evapotranspiration were applied. The actual irrigation water amount can be calculated by applying the crop coefficient and cropping days for the study area based on the developed irrigation water amount estimation program in this study.

• The Journal of the Acoustical Society of Korea
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• v.38 no.1
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• pp.82-95
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• 2019

In this study, we analyzed the beam time series of ocean reverberation which was conducted in the eastsouthern region of East Sea, Korea during the August, 2015. The reverberation data was gathered by moving research vessel towing LFM (Linear Frequency Modulation) source and triplet receiver array. After signal processing, we analyzed the variation of ocean reverberation level according to the seafloor bathymetry, source/receiver depth and sound speed profile. In addition, we used the normalized data by using cell averaging algorithm and identified the statistical characteristics of seafloor scatterer by using moment estimation method and estimated shape parameter. Also, we analyzed the coincidence of data with Rayleigh and K-distribution probability by Kolmogorov-Smirnov test. The results show that there is range dependency of reverberation according to the bathymetry and also that the time delay and the intensity level change depend on the depths of source and receiver. In addition, we observed that statistical characteristics of similar Rayleigh probability distribution in the ocean reverberation.

• Safety and Health at Work
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• v.10 no.1
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• pp.54-60
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• 2019

Background: Increasing the establishment of integrated management systems (IMSs) is done with the purpose of leaving traditional management methods and replacing them with modern management methods. Thus, the present study sought to analyze the events and investigate the impact of IMS on health and safety performance indices in an Iranian combined cycle power plants. Methods: This case study was conducted in 2012 in all units of the Yazd Combined Cycle Power Plant on accident victims before and after the implementation of IMS. For data analysis and prediction of indices after the implementation of IMS, descriptive statistics and Kolmogorov-Smirnov test, Chi-square, linear regression, and Cubic tests were conducted using SPSS software. Results: The number of people employed in the power plant in an 8-year period (2004-2011) was 1,189, and 287 cases of work-related accidents were recorded. The highest accident frequency rate and accident severity rate were in 2004 (32.65) and 2008 (209), respectively. Safe T-score reached to below -3 during 2010-2011. In addition, given the regression results, the relation between all predictor variables with outcomes was significant (p < 0.05), except for the variable $X^1$ belonging to the accident severity rate index. Conclusion: The implementation of safety programs especially that of IMS and its annual audits has had a significant impact on reducing accident indices and improving safety within the study period. Accordingly, health and safety management systems are appropriate tools for reducing accident rate, and the use of regression models and accident indices is also a suitable way for monitoring safety performance.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.160-160
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• 2023

Generally, Global Climate Models (GCM) cannot be used directly due to their inherent error arising from over or under-estimation of climate variables compared to the observed data. Several bias correction methods have been devised to solve this problem. Most of the traditional bias correction methods are one dimensional as they bias correct the climate variables separately. One such method is the Quantile Mapping method which builds a transfer function based on the statistical differences between the GCM and observed variables. Laux et al. introduced a copula-based method that bias corrects simulated climate data by employing not one but two different climate variables simultaneously and essentially extends the traditional one dimensional method into two dimensions. but it has some limitations. This study uses objective functions to address specifically, the limitations of Laux's methods on the Quantile Mapping method. The objective functions used were the observed rank correlation function, the observed moment function and the observed likelihood function. To illustrate the performance of this method, it is applied to ten GCMs for 20 stations in South Korea. The marginal distributions used were the Weibull, Gamma, Lognormal, Logistic and the Gumbel distributions. The tested copula family include most Archimedean copula families. Five performance metrics are used to evaluate the efficiency of this method, the Mean Square Error, Root Mean Square Error, Kolmogorov-Smirnov test, Percent Bias, Nash-Sutcliffe Efficiency and the Kullback Leibler Divergence. The results showed a significant improvement of Laux's method especially when maximizing the observed rank correlation function and when maximizing a combination of the observed rank correlation and observed moments functions for all GCMs in the validation period.

• Imaging Science in Dentistry
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• v.54 no.2
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• pp.147-157
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• 2024

Purpose: The aim of this study was to explore the correlations of cone-beam computed tomographic findings with the apnea-hypopnea index in patients with obstructive sleep apnea. Materials and Methods: Forty patients with obstructive sleep apnea were selected from the ear-nose-throat (ENT) outpatient clinic, Faculty of Medicine, Mansoura University. Cone-beam computed tomography was performed for each patient at the end of both inspiration and expiration. Polysomnography was carried out, and the apnea-hypopnea index was obtained. Linear measurements, including cross-sectional area and the SNA and SNB angles, were obtained. Four oral and maxillofacial radiologists categorized pharyngeal and retropalatal airway morphology and calculated the airway length and volume. Continuous data were tested for normality using the Kolmogorov-Smirnov test and reported as the mean and standard deviation or as the median and range. Categorical data were presented as numbers and percentages, and the significance level was set at P<0.05. Results: The minimal value of the cross-sectional area, SNB angle, and airway morphology at the end of inspiration demonstrated a statistically significant association (P<0.05) with the apnea-hypopnea index, with excellent agreement. No statistically significant difference was found in the airway volume, other linear measurements, or retropalatal airway morphology. Conclusion: Cone-beam computed tomographic measurements in obstructive sleep apnea patients may be used as a supplement to a novel radiographic classification corresponding to the established clinical apnea-hypopnea index classification.

• Journal of Korean Medicine Rehabilitation
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• v.31 no.4
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• pp.157-166
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• 2021

Objectives This study is designed to evaluate the safety of Bojungikgi-tang soft extract in healthy male volunteers. Methods 12 healthy male volunteers were recruited and this study was carried out by a single center. Laboratory test results, vital signs of the volunteers were collected to evaluate safety. According to registration order, the 12 subjects were allocated by serial number. To evaluate safety, blood samples were taken and vital signs were checked 4 times - screening, pre administration, post administration and follow up-during the whole trial. The difference between pre (before medication [0 hr]) and post-administration (after medication [48 hr]) variables was summarized as mean±standard deviation. The normality test was performed using the Kolmogorov-Smirnov test and Shapiro-Wilk test. When the normality is satisfied, the paired t-test is applied. Otherwise, the non-parametric method, Wilcoxon signed rank test is applied. The significance level was p<0.05. The incidence of all adverse effects are shown in percentage. Results In the case of red blood cell, hemoglobin, hematocrit, lymphocytes, neutrophils, protein, γ-glutamyl transpeptidase values, the normality test result of the variable for the difference value before and after the dosing has a significance level <0.05. But most of values did not deviate from the normal range, and the deviation from the normal range could not be regarded as the significance associated with this clinical trial. And adverse event wasn't observed associated with the clinical trial drug. Conclusions Bojungikgi-tang soft extract were considered to be safe for healthy male volunteers.

• Journal of Korea Water Resources Association
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• v.42 no.10
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• pp.857-866
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• 2009

In this study, basic data is consisted annual maximum rainfall at 56 stations that has the rainfall records more than 30years in Korea. The 14 probability distributions which has been widely used in hydrologic frequency analysis are applied to the basic data. The method of moments, method of maximum likelihood and probability weighted moments method are used to estimate the parameters. And 4-tests (chi-square test, Kolmogorov-Smirnov test, Cramer von Mises test, probability plot correlation coefficient (PPCC) test) are used to determine the goodness of fit of probability distributions. This study emphasizes the necessity for considering the variability of the estimate of T-year event in hydrologic frequency analysis and proposes a framework for evaluating probability distribution models. The variability (or estimation error) of T-year event is used as a criterion for model evaluation as well as three goodness of fit criteria (SLSC, MLL, and AIC) in the framework. The Jackknife method plays a important role in estimating the variability. For the annual maxima of rainfall at 56 stations, the Gumble distribution is regarded as the best one among probability distribution models with two or three parameters.

• Journal of Navigation and Port Research
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• v.43 no.3
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• pp.186-196
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• 2019

Berthing energy is majorly influenced by the berthing velocity. It is necessary to design an appropriate berthing velocity for each pier, since excessive berthing velocity can cause berthing accident causing damage to the ship and pier. In this study, as a statistical approach for berthing velocity, the probability distributions suitable for the berthing velocities were confirmed using the K-S test, the A-D test and the Q-Q plot. As a result, the frequency distribution of the berthing velocity was found to be suitable using the Weibull distribution as well as the lognormal distribution. Additionally, the predicted values obtained through estimation of the berthing velocity using the concept of probability of exceedance in this study is proposed as a reference of design berthing velocity. It can be observed that the design berthing velocity is set to be somewhat low so that it does not practically match with the reality. This study and its results can be expected to contribute to the development of a proper design velocity calculation method.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.4
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• pp.87-96
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• 2021

Determining design rainfall is the first step to plan an agricultural drainage facility. The objective of this study is to evaluate whether the current method for parameter estimation is reasonable for computing the design rainfall. The current Gumbel-Kendall (G-K) method was compared with two other methods which are Gumbel-Chow (G-C) method and Probability weighted moment (PWM). Hourly rainfall data were acquired from the 60 ASOS (Automated Synoptic Observing System) stations across the nation. For the goodness-of-fit test, this study used chi-squared (𝛘²) and Kolmogorov-Smirnov (K-S) test. When using G-K method, 𝛘² statistics of 18 stations exceeded the critical value (𝑥²_a=0.05,df=4=9.4877) and 10, 3 stations for G-C method, PWM method respectively. For K-S test, none of the stations exceeded the critical value (D^a=0.05_n=0.19838). However, G-K method showed the worst performances in both tests compared to other methods. Subsequently, this study computed design rainfall of 48-hour duration in 60 ASOS stations. G-K method showed 5.6 and 6.4% higher average design rainfall and 15.2 and 24.6% higher variance compared to G-C and PWM methods. In short, G-K showed the worst performance in goodness-of-fit tests and showed higher design rainfall with the least robustness. Likewise, considering the basic assumptions of the design rainfall estimation, G-K is not an appropriate method for the practical use. This study can be referenced and helpful when revising the agricultural drainage standards.