• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.205-205
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• 2021

Surface soil moisture, which governs the partitioning of precipitation into infiltration and runoff, plays an important role in the hydrological cycle. The assimilation of satellite soil moisture retrievals into a land surface model or hydrological model has been shown to improve the predictive skill of hydrological variables. This study aims to improve streamflow prediction with Weather Research and Forecasting model-Hydrological modeling system (WRF-Hydro) by assimilating Soil Moisture Active and Passive (SMAP) data at 3 km and analyze its impacts on hydrological components. We applied Cumulative Distribution Function (CDF) technique to remove the bias of SMAP data and assimilate SMAP data (April to July 2015-2019) into WRF-Hydro by using an Ensemble Kalman Filter (EnKF) with a total 12 ensembles. Daily inflow and soil moisture estimates of major dams (Soyanggang, Chungju, Sumjin dam) of South Korea were evaluated. We investigated how hydrologic variables such as runoff, evaporation and soil moisture were better simulated with the data assimilation than without the data assimilation. The result shows that the correlation coefficient of topsoil moisture can be improved, however a change of dam inflow was not outstanding. It may attribute to the fact that soil moisture memory and the respective memory of runoff play on different time scales. These findings demonstrate that the assimilation of satellite soil moisture retrievals can improve the predictive skill of hydrological variables for a better understanding of the water cycle.

• ETRI Journal
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• v.46 no.2
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• pp.227-237
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• 2024

This study proposes a novel, conditionally applied neural network technique to reduce the overall peak-to-average power ratio (PAPR) of an orthogonal frequency division multiplexing (OFDM) system while maintaining an acceptable bit error rate (BER) level. The main purpose of the proposed scheme is to adjust only those subcarriers whose peaks exceed a given threshold. In this respect, the developed C-ANN algorithm suppresses only the peaks of the targeted subcarriers by slightly shifting the locations of their corresponding frequency samples without affecting their phase orientations. In turn, this achieves a reasonable system performance by sustaining a tolerable BER. For practical reasons and to cover a wide range of application scenarios, the threshold for the subcarrier peaks was chosen to be proportional to the saturation level of the nonlinear power amplifier used to pass the generated OFDM blocks. Consequently, the optimal values of the factor controlling the peak threshold were obtained that satisfy both reasonable PAPR reduction and acceptable BER levels. Furthermore, the proposed system does not require a recovery process at the receiver, thus making the computational process less complex. The simulation results show that the proposed system model performed satisfactorily, attaining both low PAPR and BER for specific application settings using comparatively fewer computations.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.19 no.2
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• pp.105-112
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• 2007

Sediment transport model based on the Lagrangian concept considering the grain size distribution(GSD) was setup and the change of the sediment diffusion range was analysed in the condition of considering and not considering the GSD. The GSD curve is assumed as the Log-normal distribution function in order to consider the GSD with respect to the Lagrangian concept and the random numbers, i.e. sediment particles, are generated based on the distribution function. The sediment particles is assumed as the spherical type and the random numbers based on the sediment weight is converted to the sediment diameters. Sediment transport patterns are analysed by the settling simulation, in which the settling velocity is computed by the van Rijn formulae and the horizontal diffusion coefficient is used as the constant parameter. The diffusion patterns are very similar to the patterns with GSD condition. The diffusion range defined as the range including 90%, 99% sediment weight of the total sediment weight, however, is larger than without considering GSD condition in 90%-option and shorter than with considering GSD condition in 99-option, respectively. The diffusion range is defined as tile p-percentage of the cumulative sediment weight region with reference to the 50% region, 90%- option, 99%-option, respectively.

• Journal of Korean Society of Forest Science
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• v.102 no.4
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• pp.477-483
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• 2013

The purpose of this study was to calculate uncertainty of emission factor collected data and to evaluate the applicability of Monte Carlo simulation technique. To estimate the distribution of emission factors (Such as Basic wood density, Biomass expansion factor, and Root-to-shoot ratio), four probability density functions (Normal, Lognormal, Gamma, and Weibull) were used. The two sample Kolmogorov-Smirnov test and cumulative density figure were used to compare the optimal probability density function. It was observed that the basic wood density showed the gamma distribution, the biomass expansion factor results the log-normal distribution, and root-shoot ratio showd the normal distribution for Pinus densiflora in the Gangwon region; the basic wood density was the normal distribution, the biomass expansion factor was the gamma distribution, and root-shoot ratio was the gamma distribution for Pinus densiflora in the central region, respectively. The uncertainty assessment of emission factor were upper 62.1%, lower -52.6% for Pinus densiflora in the Gangwon region and upper 43.9%, lower -34.5% for Pinus densiflora in the central region, respectively.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.12
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• pp.1186-1192
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• 2008

The reliability of gas turbine engine blades was studied. Yield strength, Young’s modulus, engine speed and gas temperature were considered as statistically independent random variables. The failure probability was calculated using five different methods. Advanced Mean Value Method was the most efficient without significant loss in accuracy. When random variables were assumed to have normal, lognormal and Weibull distributions with the same means and standard deviations, the CDF of limit state equation did not change significantly with the distribution functions of random variables. The normalized sensitivity of failure probability with respect to standard deviations of random variables was the largest with gas temperature. The effect of means and standard deviations of random variables was studied. The increase in the mean of gas temperature and the standard deviation of engine speed increased the failure probability the most significantly.

• Korean journal of applied entomology
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• v.32 no.2
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• pp.236-244
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• 1993

The development of OrientaL tobacco budworm (OTE), Heticoverpa assulta, was studied at seven constant temperatures from 18 to $33^{\circ}C$ with a 14L : 10D photoperiod on the artificial diet. The egg, larval, and pupal duration comprised ca. 10, 48, and 42% of the total developmental time (from egg to adult emergence). The lower developmental threshold temperatures for egg, larval, pupal, and overall development were 8.62, 12.65, 11.64, and $11.89^{\circ}C$, respectively. The biophysical model of Sharpe & DeMichele (1977) provided a good description of OTB's development as a function of temperature ($r^2$=0.993~O.996). The Wmbull distribution was fitted to cumulative frequency distributions of normalized developmental times for each developmental stage of OTE ($r^2$== 0.987 ~0.999).

• Journal of Korean Society on Water Environment
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• v.31 no.3
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• pp.241-252
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• 2015

Runoff behaviors by five bias correction methods were analyzed, which were Change Factor methods using past observed and estimated data by the estimation scenario with average annual calibration factor (CF_Y) or with average monthly calibration factor (CF_M), Quantile Mapping methods using past observed and estimated data considering cumulative distribution function for entire estimated data period (QM_E) or for dry and rainy season (QM_P), and Integrated method of CF_M+QM_E(CQ). The peak flow by CF_M and QM_P were twice as large as the measured peak flow, it was concluded that QM_P method has large uncertainty in monthly runoff estimation since the maximum precipitation by QM_P provided much difference to the other methods. The CQ method provided the precipitation amount, distribution, and frequency of the smallest differences to the observed data, compared to the other four methods. And the CQ method provided the rainfall-runoff behavior corresponding to the carbon dioxide emission scenario of SRES A1B. Climate change scenario with bias correction still contained uncertainty in accurate climate data generation. Therefore it is required to consider the trend of observed precipitation and the characteristics of bias correction methods so that the generated precipitation can be used properly in water resource management plan establishment.

• Journal of the Korean Geosynthetics Society
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• v.12 no.1
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• pp.51-61
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• 2013

This paper presents results from a study undertaken to quantitatively evaluate the geotextile pore sizes using optical image analysis. The evaluation was conducted by observing surfaces of coupons cut from resin-impregnated specimens of geotextile-geomembrane layered under various load conditions. Stereological concepts were applied to collect representative specimens from a series of laboratory tests. The sizes of voids enclosed by filaments were expressed in terms of the largest inscribing opening size (LIOS) distribution. The opening diameter corresponding to the 50% cumulative frequency decreased by about 45mm as the load increased from 10 to 300kPa and recovered to about 90% of its initial state on unloading back to 10kPa. The average void size was reduced by 32 and 16.5% as the geotextile was sheared against a textured geomembrane under normal stresses of 100 and 300kPa, respectively. The results showed how the LIOS distribution varied as a function of normal stress and interface shear displacement against a smooth and a textured geomembrane surfaces.

• Journal of the Korean Data and Information Science Society
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• v.27 no.5
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• pp.1253-1262
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• 2016

When there exists a change-point in hazard function, it should be estimated for exact parameter or hazard estimation. In this research, we compare the hazard change-point estimators. Matthews and Farewell (1982) parametric change-point estimator is based on the likelihood and Zhang et al. (2014) nonparametric estimator is based on the Nelson-Aalen cumulative hazard estimator. Simulation study is done for the data from exponential distribution with one hazard change-point. The simulated data generated without censoring and the data with right censoring are considered. As real data applications, the change-point estimates are computed for leukemia data and primary biliary cirrhosis data.

• Journal of the Korean Geotechnical Society
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• v.33 no.7
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• pp.29-41
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• 2017

There are uncertainties about the seismic load caused by seismic waves, which cannot be predicted due to the characteristics of the earthquake occurrence. Therefore, it is necessary to consider these uncertainties by probabilistic analysis. In this paper, procedures to develop a fragility curve that is a representative method to evaluate the safety of a structure by stochastic analysis were proposed for cut slopes. Fragility curve that considers uncertainties of soil shear strength parameters was prepared by Monte Carlo Simulation using pseudo static analysis. The fragility curve considering the uncertainty of the input ground motion was developed by performing time-history seismic analysis using selected 30 real ground input motions and the Newmark type displacement evaluation analysis. Fragility curves are represented as the cumulative probability distribution function with lognormal distribution by using the maximum likelihood estimation method.