• Journal of Korea Water Resources Association
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• v.47 no.3
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• pp.285-295
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• 2014

We applied the ISPSO-GLUE method, which integrates the Isolated-Speciation-based Particle Swarm Optimization (ISPSO) with the Generalized Likelihood Uncertainty Estimation (GLUE) method, to the uncertainty analysis of the Topography Model (TOPMODEL) and compared its performance with that of the GLUE method. When we performed the same number of model runs for the both methods, we were able to identify the point where the performance of ISPSO-GLUE exceeded that of GLUE, after which ISPSOGLUE kept improving its performance steadily while GLUE did not. When we compared the 95% uncertainty bounds of the two methods, their general shapes and trends were very similar, but those of ISPSO-GLUE enclosed about 5.4 times more observed values than those of GLUE did. What it means is that ISPSOGLUE requires much less number of parameter samples to generate better performing uncertainty bounds. When compared to ISPSO-GLUE, GLUE overestimated uncertainty in the recession limb following the maximum peak streamflow. For this recession period, GLUE requires to find more behavioral models to reduce the uncertainty. ISPSO-GLUE can be a promising alternative to GLUE because the uncertainty bounds of the method were quantitatively superior to those of GLUE and, especially, computationally expensive hydrologic models are expected to greatly take advantage of the feature.

• Journal of the Korean Geotechnical Society
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• v.22 no.8
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• pp.107-118
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• 2006

Among a variety of influencing components, time-variant seepage and long-term underground motion are important to understand the abnormal behavior of tunnels. Excessiveness of these two components could be the direct cause of severe damage on tunnels, however, it is not easy to quantify the effect of these on the behavior of tunnels. These parameters can be estimated by using inverse methods once the appropriate relationship between inputs and results is clarified. Various inverse methods or parameter estimation techniques such as artificial neural network and least square method can be used depending on the characteristics of given problems. Numerical analyses, experiments, or monitoring results are frequently used to prepare a set of inputs and results to establish the back analysis models. In this study, a back analysis method has been developed to estimate geotechnically hard-to-known parameters such as permeability of tunnel filter, underground water table, long-term rock mass load, size of damaged zone associated with seepage and long-term underground motion. The artificial neural network technique is adopted and the numerical models developed in the first part are used to prepare a set of data for learning process. Tunnel behavior, especially the displacements of the lining, has been exclusively investigated for the back analysis.

• The Korean Journal of Applied Statistics
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• v.37 no.2
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• pp.225-237
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• 2024

In the analysis of competing risks data, some of covariates may not be fully observed for some subjects. In such cases, excluding subjects with missing covariate values from the analysis may result in biased estimates and loss of efficiency. In this paper, we studied multiple imputation and the augmented inverse probability weighting method for regression parameter estimation in the cause-specific proportional hazards model with missing covariates. The performance of estimators obtained from multiple imputation and the augmented inverse probability weighting method is evaluated by simulation studies, which show that those methods perform well. Multiple imputation and the augmented inverse probability weighting method were applied to investigate significant risk factors for the risk of death from breast cancer and from other causes for breast cancer data with missing values for tumor size obtained from the Prostate, Lung, Colorectal, and Ovarian Cancer Screen Trial Study. Under the cause-specific proportional hazards model, the methods show that race, marital status, stage, grade, and tumor size are significant risk factors for breast cancer mortality, and stage has the greatest effect on increasing the risk of breast cancer death. Age at diagnosis and tumor size have significant effects on increasing the risk of other-cause death.

• Journal of Korean Society of Forest Science
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• v.81 no.4
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• pp.337-345
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• 1992

In this research, a kinematic wave model was applied for the runoff analysis, Regulation of streamflow was estimated by the calibration of roughness coefficient as a parameter. The data analyzed were obtained from Ananomiya and Shirasaka experimental basins at Tokyo University Forest in Aichi. Estimation methods and characteristics of roughness coefficient as a evaluation method of hydrological function of forest are summarized as follows ; 1. Roughness coefficient($N_s$) indicates the resistance of hillslope to the flowing water of surface runoff. There exists an hypothesis that resistance of hillslope to flowing water increase with the growth forest and development of the $A_o$ layer. 2. Roughness coefficient($N_s$) was estimated by the parameter when the stream direct runoff was calculated by using the kinematic wave. 3. Secular change of '$N_s$' in ananomiya has a curve which has an upper limit and increases exponentially near the limit. The curve quickly increased from 1935 to 1945 when results of afforestation for erosion control were thought to be effective. On the other hand, slight increase of '$N_s$' in Shirasaka indicates that there was not such a big change in the surface of soil layer. 4. The increase of '$N_s$' was related with decrease of direct runoff and increase of base flow. It was recognized that the rate of direct runoff decreased with the improvement of forest physiognomy and the rate of base flow was increased. But absolute value of water runoff per one storm decreased in chronological order.

• Journal of Animal Science and Technology
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• v.46 no.4
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• pp.509-516
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• 2004

This study is to investigate the amount of biased estimates for heritability and genetic correlation according to data structure on marbling scores in Korean cattle. Breeding population with 5 generations were simulated by way of selection for carcass weight, Longissimus muscle area and latent values of marbling scores and random mating. Latent variables of marbling scores were categorized into five by the thresholds of 0, I, 2, and 3 SD(DSI) or seven by the thresholds of -2, -1, 0,1I, 2, and 3 SD(DS2). Variance components and genetic pararneters(Heritabilities and Genetic correlations) were estimated by restricted maximum likelihood on multivariate linear mixed animal models and by Gibbs sampling algorithms on multivariate threshold mixed animal models in DS1 and DS2. Simulation was performed for 10 replicates and averages and empirical standard deviation were calculated. Using REML, heritabilitis of marbling score were under-estimated as 0.315 and 0.462 on DS1 and DS2, respectively, with comparison of the pararneter(0.500). Otherwise, using Gibbs sampling in the multivariate threshold animal models, these estimates did not significantly differ to the parameter. Residual correlations of marbling score to other traits were reduced with comparing the parameters when using REML algorithm with assuming linear and normal distribution. This would be due to loss of information and therefore, reduced variation on marbling score. As concluding, genetic variation of marbling would be well defined if liability concepts were adopted on marbling score and implemented threshold mixed model on genetic parameter estimation in Korean cattle.

• Journal of Soil and Groundwater Environment
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• v.12 no.5
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• pp.19-32
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• 2007

In Korea, there have been various methods of estimating groundwater recharge which generally can be subdivided into three types: baseflow separation method by means of groundwater recession curve, water budget analysis based on lumped conceptual model in watershed, and water table fluctuation method (WTF) by using the data from groundwater monitoring wells. However, groundwater recharge rate shows the spatial-temporal variability due to climatic condition, land use and hydrogeological heterogeneity, so these methods have various limits to deal with these characteristics. To overcome these limitations, we present a new method of estimating recharge based on water balance components from the SWAT-MODFLOW which is an integrated surface-ground water model. Groundwater levels in the interest area close to the stream have dynamics similar to stream flow, whereas levels further upslope respond to precipitation with a delay. As these behaviours are related to the physical process of recharge, it is needed to account for the time delay in aquifer recharge once the water exits the soil profile to represent these features. In SWAT, a single linear reservoir storage module with an exponential decay weighting function is used to compute the recharge from soil to aquifer on a given day. However, this module has some limitations expressing recharge variation when the delay time is too long and transient recharge trend does not match to the groundwater table time series, the multi-reservoir storage routing module which represents more realistic time delay through vadose zone is newly suggested in this study. In this module, the parameter related to the delay time should be optimized by checking the correlation between simulated recharge and observed groundwater levels. The final step of this procedure is to compare simulated groundwater table with observed one as well as to compare simulated watershed runoff with observed one. This method is applied to Mihocheon watershed in Korea for the purpose of testing the procedure of proper estimation of spatio-temporal groundwater recharge distribution. As the newly suggested method of estimating recharge has the advantages of effectiveness of watershed model as well as the accuracy of WTF method, the estimated daily recharge rate would be an advanced quantity reflecting the heterogeneity of hydrogeology, climatic condition, land use as well as physical behaviour of water in soil layers and aquifers.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.9
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• pp.328-334
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• 2012

Continuous fetal heart beat monitoring has assisted clinicians in assuring fetal well-being during antepartum and intrapartum. Fetal heart rate (FHR) is an important parameter of fetal health during pregnancy. The Doppler ultrasound is one of very useful methods that can non-invasively measure FHR. Although it has been commonly used in clinic, inaccurate heart rate reading has not been completely resolved.. The objective of this study is to improve detection algorithm of FHR from Doppler ultrasound signal with simple method. We modified autocorrelation function to enhance signal periodicity and adopted adaptive window size and shifted for data segment to be analysed. The proposed method was applied to real measured data, and it was verified that beat-to-beat FHR estimation result was comparable with the reference fetal ECG data. This simple and effective method is expected to be implemented in the embedded system.

• Sleep Medicine and Psychophysiology
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• v.11 no.2
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• pp.100-105
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• 2004

Objectives: Major depression is associated with an increased risk of cardiovascular mortality. One possible explanation for this association is that major depression influences autonomic neurocardiac regulation. However, previous studies on the relationship between heart rate variability (HRV) and major depression have revealed conflicting results. The purpose of this study is to clarify that major depressive patients compared to healthy controls show a reduction in HRV as an expression of reduced modulation of vagal activity to the heart. Methods: According to DSM-IV, the time and frequency domain HRV indices (5-min resting study) of 30 patients with major depressive disorder were compared with those of 30 healthy controls. Standardized HRV tests enable quantitative estimation of autonomic nervous system function. Results: After controlling for age and gender, subjects with major depression showed a higher heart rate and significantly lower modulation of cardiovagal activity compared to controls. The total power (TP) band, very low frequency (VLF: 0.003-0.04 Hz) band, low frequency (LF: 0.04-0.15 Hz) band, and high frequency (HF: 0.15-0.4 Hz) band were significantly reduced in subjects with major depression compared to control subjects. Conclusion: Patients with major depression may suffer from functional disturbances in the interaction between the sympathetic and parasympathetic autonomic systems.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.4 no.1
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• pp.103-112
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• 1984

This study is an effort to develop a series of empirical procedure for the determination of design flood for a small watershed based on the unit hydrograph theory. It is shown that a flood discharge of a watershed with a specific return period can be expressed as a product of its watershed area, rainfall factor, runoff factor and flood peak reduction factor. Since the procedures for the determination of rainfall factor and runoff factor were already developed in the previous study (13) a series of step-by-step procedure is devised to empirically determine the flood peak reduction factor in the present study. Using the methodology developed herein the 50-year design flood, which is of concern in the drainage of agricultural lands, is estimated for a watershed on upper Kyungan River and compared with the design floods by the existing methods now in use. The flood peak reduction factor was correlated with the dimensionless parameter consisted of the rainfall duration divided by the basin lag time, which was computed from the derived unit hydrographs by the method of moment. The unit hydrographs of various durations were synthesized by the method of build up and S-curve. A multiple correlation was also made between the basin lag time and the physiographic parameters of the watershed, i.e., the stream length and the average stream slope.

• Journal of Wetlands Research
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• v.13 no.3
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• pp.499-514
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• 2011

An underlying assumption of traditional hydrologic frequency analysis is that climate, and hence the frequency of hydrologic events, is stationary, or unchanging over time. Under stationary conditions, the distribution of the variable of interest is invariant to temporal translation. Water resources infrastructure planning and design, such as dams, levees, canals, bridges, and culverts, relies on an understanding of past conditions and projection of future conditions. But, Water managers have always known our world is inherently non-stationary, and they routinely deal with this in management and planning. The aim of this paper is to give a brief introduction to non-stationary extreme value analysis methods. In this paper, a non-stationary hydrologic frequency analysis approach is introduced in order to determine probability rainfall consider changing climate. The non-stationary statistical approach is based on the conditional Generalized Extreme Value(GEV) distribution and Maximum Likelihood parameter estimation. This method are applied to the annual maximum 24 hours-rainfall. The results show that the non-stationary GEV approach is suitable for determining probability rainfall for changing climate, sucha sa trend, Moreover, Non-stationary frequency analyzed using SOI(Southern Oscillation Index) of ENSO(El Nino Southern Oscillation).