• Journal of Korea Water Resources Association
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• v.45 no.6
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• pp.545-555
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• 2012

A numerical modeling has become increasingly popular and more important to the study of water waves with a rapid advancement of computer technology. However, different types of problems are induced during simulating wave motion. One of the key problems is re-reflection to a computation domain at the incident boundary. The internal wave generating-absorbing boundary conditions have been commonly used in numerical wave models to prevent re-reflection. For the Navier-Stokes equations model, the internal wave maker using a mass source function of the continuity equation has been used to generate various types of waves. Nonetheless, almost every numerical experiment is performed in two dimensions and only a few tests have been expanded to three dimensions. More recently, a momentum source function of the Boussinesq equations is applied to generate essentially directional waves in the three dimensional Navier-Stokes equations model. In this study, the internal wave maker using a momentum source function is employed to generate targeted linear waves in the three-dimensional LES model.

• International Journal of Highway Engineering
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• v.10 no.4
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• pp.151-159
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• 2008

Performances of retroreflectivity vary place to place, according to traffic volumes and time lengths after striping, depending on pavement marking materials and colors. The present paper uses the nation wide data of retroreflectivity, which has been collected from freeways and then tries to develop the regression curve setting traffic volume and service life as independent variables and retroreflectivities as dependent variables. The DB system includes two year's measurement in $2005{\sim}2006$ over Korean freeway pavement marking at an interval of three months for the period. The mobile measurement system, a laserlux, was employed for the purpose. The DB has provided a lot of information about materials and performance of the specific pavement marking such as geometric features, traffic volumes, material characteristics and the installation date. This study provides the comparison of pavement marking performances under diversified conditions. Based on accumulated pavement marking performances, this study provides performance curves based on the diversified factors. The goal of the retroreflectivity modeling is to develop equations that can be used to estimate an average retroreflectivity of pavement markings as a function time since application and traffic volume. After representing the variation of retroreflectivities and estimating regression curves by linear, exponential, logarithmic and power function, the regression curve which had the highest coefficient of determination and the value similar to the last field measurement was regarded as the retroreflectivity decay model. As a result of verification, the decay model showed the signification within the 90% confidence level and especially showed the clear relation with field data according to increase of cumulative vehicle exposure. Accordingly, these models can be used to determine service lives, retroreflectivity degradation rates, and retroreflectivity of new markings.

• Korean Journal of Soil Science and Fertilizer
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• v.33 no.6
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• pp.398-404
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• 2000

We examined the effect of soil:water ratio on the equivalent concentration of individual electrolyte species and the electrical conductivities (EC) of the diluted extracts of 24 soil samples (loam or silt loam) collected from rose-cultivated plastic houses to estimate the EC of saturated soil-paste extracts (ECe) from diluted soil extracts. With increasing volume ratio of water (higher dilution), the equivalent concentrations of each electrolyte species and their sum increased. The relative contribution to the EC, however, was highest for $NO_3{^-}$, irrespective of soil:water ratio. The measured ECe was 6.36 for loam and $8.09dS\;m^{-1}$ for silt loam soils and the corresponding soil:water ratio was 0.38 and 0.50, respectively. The EC_e estimated from the EC of diluted extracts at 1:1, 1:2, or 1:5 soil:water ratios using their corresponding uniform diluted factors was lower than the measured EC_e and this difference was greater with higher dilution and EC values. Therefore, the alternative diluted factors (y) for each soil: water ratio were obtained following the definition of diluted factor and were correlated significantly with volume ratios of added water (x): y=1.55x+0.5 for loam and y=1.21x+0.48 for silt loam soils. On the other hand, correlation analyses of the EC of soil extracts (y) to the volume ratio of added water (x) on log-log scale yielded linear models: logy = -0.805logx + logb, SD of slope=0.05, b=sample specific constant, n=24). With known saturation percentage of a sample representing a group and and the EC of diluted extract of a given soil, the EC_e could be predicted using the proposed logarithmic equation.

• Journal of Korea Water Resources Association
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• v.48 no.12
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• pp.1023-1035
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• 2015

This study applies 3-D N-S solver based on PBM (Porous Body Model), LED-WASS-3D ver 2.0 to directly analyze non-linear interaction of seawater-freshwater-coastal aquifer in order to simulate the seawater infiltration into coastal aquifer. This numerical simulation is the first trial in Korea, as well as unusual and new numerical analysis abroad. Firstly, to validate the applied numerical model, the validity and effectiveness was verified for the numerical model by comparing and considering it with the result of laboratory experiment for seawater-freshwater interface in coastal aquifer. And then it simulated the seawater infiltration into coastal aquifer considering the changed levels of seawater and groundwater in order to analyze the distribution characteristics of flow field and seawater-freshwater interface of coastal aquifer as the level difference between seawater and groundwater and rate of seawater level (${\Delta}h/h$) increased. In addition, the characteristics of seawater infiltration were analyzed from the vertical salinity in the coastal aquifer by ${\Delta}h/h$, which cannot be obtained from existing non-diffusion numerical models. Finally, it analyzed the effect of ${\Delta}h/h$ on the seawater infiltration distance in coastal aquifer, which was indexed.

• Korean Journal of Psychosomatic Medicine
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• v.15 no.1
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• pp.44-50
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• 2007

Objectives: previous studies have suggested the possible predisposing personality in fibromyalgia(FM). The aim of this study is to investigate the personality traits in female patients with FM compared to healthy female controls using the Temperament and Character Inventory(TCI) and furthermore, to evaluate the personality traits affecting the severity of the symptoms of FM. Methods Forty female patients with FM and 40 healthy female controls were examined using the TCI and the Hamilton depression rating scale. The FM patients were also evaluated the severity of the symptoms of FM using the fibromyalgia impact questionnaire(FIQ). Results : ANCOVA with age and depression levels as covariates showed that the FM patients scored significantly higher on the harm avoidance(F=2.187, p=0.047) and lower on the self-directedness(F=4.551, p=0.036) than the healthy controls. The FIQ scores showed positive correlation with the harm avoidance scores in the FM patients when adjusting for age and depression level(R=0.399, p=0.013) Multiple linear regression models revealed that the harm avoidance scores would affect the FIQ scores in FM patients(95% Cl=0.004-1.942, p=0.049). Conclusions : These results suggest that the female FM patients have distinctive temperament and character dimensions compared to the healthy female controls. Moreover, the harm avoidance may be the predictive personality to affect the severity of the symptoms of female FM patients.

• Ecology and Resilient Infrastructure
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• v.7 no.2
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• pp.114-125
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• 2020

Despite the various artificial neural networks that have been developed, most of the discharge models in previous studies have been developed using deep neural networks. This study aimed to develop a discharge model using a convolution neural network (CNN), which was used to solve classification problems. Furthermore, the applicability of CNN was evaluated. The photographs (pictures or images) for input data to CNN could not clearly show the characteristics of the study area as well as precipitation. Hence, the model employed in this study had to use numerical images. To solve the problem, the CN of NRCS was used to generate images as input data for the model. The generated images showed a good possibility of applicability as input data. Moreover, a new application of CN, which had been used only for discharge prediction, was proposed in this study. As a result of CNN training, the model was trained and generalized stably. Comparison between the actual and predicted values had an R² of 0.79, which was relatively high. The model showed good performance in terms of the Pearson correlation coefficient (0.84), the Nash-Sutcliffe efficiency (NSE) (0.63), and the root mean square error (24.54 ㎥/s).

• Korean Journal of Social Welfare
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• v.66 no.1
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• pp.251-276
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• 2014

This study scrutinizes the common sense in the field of disability employment that the bigger the size of a firm, the lower the employment rate of people with disabilities. This common sense has been established by conventional cross-tabulation and multiple regression analyses without taking into account possible interactions between the sizes of firms and the industries in which they operate. This study shows that the distribution of the disability employment rate violates the linearity and homoscedasticity assumptions of the OLS. In an effort to find models that explain the data better, this study fits the OLS model, the weighted linear regression model, and the multinomial logit model as well as the path analysis which is meant to examine the relationships between firm size and other variables relevant to disability employment. The result shows that, when an interaction term between firm size and industry is added to the model, firm size does not have any significant effect on disability employment rate for those firms with 100 or more regular employees, to the contrary of the findings of prior studies. It also demonstrates that other factors such as job setting, the extent of helpfulness of disability employment employers perceive, employers' care for disability, and employers' awareness of disability policies may matter more than does firm size. This study proposes that future research and policy implementation for disability employment should pay no less attention to industry and other factors mentioned above than to firm size.

• Journal of the Korean Data and Information Science Society
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• v.26 no.2
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• pp.387-397
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• 2015

In this paper, the determinants of the number of job changes in the SMEs (small and medium enterprises) youth-intern project is analysed, utilizing SMEs youth-intern DB and employment insurance DB. Since the number of job changes are count data which take integer values other than negative values, general linear regression analysis becomes inappropriate. Therefore, four models such as Poisson regression model, zero inflated Poisson regression model, negative binomial regression model and zero inflated negative binomial regression model are tried to fit count data. A zero inflated negative binomial regression model is selected to be the best model. Major results are the followings. First, the number of job changes is shown to be significantly smaller in the treatment group than in the control group. Second, the number of job changes turns out to be significantly smaller in the young-age group than in the old-age group. Third, it is also shown that the number of job changes of man is significantly greater than that of woman. Lastly, the number of job changes in the bigger firm is shown to be significantly less than that of the smaller firm.

• Clinical and Experimental Reproductive Medicine
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• v.43 no.2
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• pp.112-118
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• 2016

Objective: Ovarian reserve tests are commonly used to predict ovarian response in infertile patients undergoing ovarian stimulation. Although serum markers such as basal follicle-stimulating hormone (FSH) or random $anti-M{\ddot{u}}llerian$ hormone (AMH) level and ultrasonographic markers (antral follicle count, AFC) are good predictors, no single test has proven to be the best predictor. In this study, we developed appropriate equations and novel nomograms to predict the number of oocytes that will be retrieved using patients' age, serum levels of basal FSH and AMH, and AFC. Methods: We analyzed a database containing clinical and laboratory information of 141 stimulated in vitro fertilization (IVF) cycles performed at a university-based hospital between September 2009 and December 2013. We used generalized linear models for prediction of the number of oocytes. Results: Age, basal serum FSH level, serum AMH level, and AFC were significantly related to the number of oocytes retrieved according to the univariate and multivariate analyses. The equations that predicted the number of oocytes retrieved (log scale) were as follows: model (1) $3.21-0.036{\times}(age)+0.089{\times}(AMH)$, model (2) $3.422-0.03{\times}(age)-0.049{\times}(FSH)+0.08{\times}(AMH)$, model (3) $2.32-0.017{\times}(age)+0.039{\times}(AMH)+0.03{\times}(AFC)$, model (4) $2.584-0.015{\times}(age)-0.035{\times}(FSH)+0.038{\times}(AMH)+0.026{\times}(AFC)$. model 4 showed the best performance. On the basis of these variables, we developed nomograms to predict the number of oocytes that can be retrieved. Conclusion: Our nomograms helped predict the number of oocytes retrieved in stimulated IVF cycles.

• Korean Journal of Weed Science
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• v.30 no.2
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• pp.94-102
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• 2010

Field and pot experiments were conducted to investigate seedling emergence and early growth of Eleocharis kuroguwai panted on different dates. Non-linear regression analyses of observed data against effective accumulated temperature (EAT) with the Gompertz model showed that the Gompertz model works well in describing seedling emergence and early growth of E. kuroguwai regardless of planting date and soil burial depth. EATs required for 50% of the maximum seedling emergence of E. kuroguwai planted at 1, 3 and 5 cm soil burial depth in the pot experiment were estimated to be 54.5, 84.0 and $118.0^{\circ}C$, respectively, and $56.7^{\circ}C$ when planted at 1 cm in the field experiment. EATs required for 50% of the maximum leaf number of E. kuroguwai planted at 1, 3 and 5 cm soil burial depth in the pot experiment were estimated to be 213.3, 249.0 and $291.6^{\circ}C$, respectively, and $239.5^{\circ}C$ when planted at 1 cm in the field experiment. Therefore, models developed in this study thus predicted that if rotary tillage with water is made on 27 May under $+2^{\circ}C$ elevated temperature condition, dates for 50% of the maximum seedling emergence, 5 leaf stage and 5 cm plant height of E. kuroguwai buried at 3 cm soil depth were predicted to be 2 June, 10 June and 12 June. These dates are 1 day earlier for the seedling emergence and 3 days earlier for the early growth as compared with current temperature condition, suggesting that earlier application of herbicides is required for effective control of E. kuroguwai.