• Journal of the Korean Society of Combustion
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• v.18 no.1
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• pp.13-20
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• 2013

Leading edge statistics are obtained by direct numerical simulation(DNS) of freely propagating incompressible and stagnating compressible turbulent premixed flames. Conditional averages of velocities in terms of reaction progress variable, c, and local flame surface density, ${\sum}^{\prime}_f$, are defined and compared through the flame brush. It holds asymptotically that $<u>_f=<S_d>_f$ and $<u>_u-<u>_b=D_t/L_w$ with the characteristic length scale of $\bar{c}$ variation, $L_w$. It also holds that $<u>_b=<u>_f$ for a freely propagating flame under no mean strain rate. The turbulent burning velocity, $S_T$, is determined by the conditional statistics at the leading edge under large activation energy.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.22 no.9
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• pp.1335-1348
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• 1998

Flow characteristics in transitional boundary layers on a flat plate were experimentally investigated under three different freestream conditions i. e. uniform flow with 0.1 % and 3.7% freestream turbulent intensity and cylinder-wake with 3.7% maximum turbulent intensity. Instantaneous streamwise velocities in laminar, transitional and turbulent boundary layers were measured by I-type hot-wire probe. For estimation of wall shear stresses on the flat plate, measured mean velocities near the wall were applied to the principle of Computational Preston Tube Method (CPM). Distributions of skin friction coefficients were reasonably predicted in all developed boundary layers. Intermittency profiles, which were estimated using Conditional Sampling Technique in transitional boundary layers, were also consistent with previously published data. It was predicted that the incoming turbulent intensity had more influence on transition onset point and transition process than freestream turbulent intensity existed just over the transition region. It was also confirmed that non-turbulent and turbulent profiles in transitional boundary layers could not be simply treated as Blasius and fully turbulent profiles.

• The Korean Journal of Applied Statistics
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• v.28 no.1
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• pp.115-122
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• 2015

This article is concerned with count time series taking values in non-negative integers. Along with the first order mean of the count time series, conditional variance (volatility) has recently been paid attention to and therefore various integer-valued GARCH(generalized autoregressive conditional heteroscedasticity) models have been suggested in the last decade. We introduce diverse integer-valued GARCH(INGARCH, for short) processes to count time series and a real data application is illustrated as a case study. In addition, zero inflated INGARCH models are discussed to accommodate zero-inflated count time series.

• The Korean Journal of Applied Statistics
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• v.21 no.1
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• pp.95-107
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• 2008

Survey on the rural living indicators was the statistic approved from National Statistical Office and the survey executed by rural resources development institute. This study was used the raw data of survey on the rural living indicators in 2005. After editing procedure for raw data, we were studied 1,582 households which is acquired through elimination of case included nonresponses, and imputed a nonresponses of 15 item selected from 146 item. The imputation methods and efficiency of imputation for simulation was adapted differently from type of data. For continuous data, we imputed the nonresponses with mean imputation, regression imputation, adjusted grey-based k-NN imputation(DU, DW, WU, WW) and compared the results with RMSE. For categorical data, we imputed the nonresponses with mode method, probability imputation, conditional mode method, conditional probability method, hot-deck imputation, and compared the results with Accuracy. By the results, regression imputation and adjusted grey-based k-NN imputation appropriated for continuous data and hot-deck imputation appropriated for categorical data.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.1
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• pp.175-186
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• 1996

An optimal channel input-traffic control (OCIC) policy is proposed for slotted frequency-hopped spread-spectrum multiple access communication systems. When the number of channel input packets is set to the optimal number, the conditional throughput for the OCIC policy is analyzed. The state transition probability is derived, the steady state performance is analyzed, and the mean pracket delay is obtained. It is shown that the mean packet delay decreases considerably when the priority of transmission is given to backlogged users. The smaller is the number of requency slots, the larger are the differences between the preformance of the OCIC policy and that of the other policies.

• The Korean Journal of Applied Statistics
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• v.22 no.5
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• pp.971-979
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• 2009

In this paper, we introduce the method that reduces the bias when the transformation and back-transformation approach is applied in GARCH models. A parametric bootstrap is employed to compute the conditional expectation which is the prediction value to minimize mean square errors in the original scale. Through the analyese of returns of KOSPI and KOSDAQ, we verified that the proposed method provides a bias-reduced estimation for the prediction value.

• Journal of the Korean Society of Combustion
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• v.6 no.2
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• pp.43-49
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• 2001

Instantaneous, three-dimensional scalar dissipation rates of the reaction progress variable are measured in turbulent premixed Bunsen flames of lean hydrocarbon/air mixtures with the two-sheet, two-dimensional Rayleigh scattering technique. The flames investigated are located in the turbulent flame-front regime on a newly proposed combustion diagram for premixed flames. The conditionally-averaged mean scalar dissipation rates, $N_{\zeta}$ are found to be lower than the calculated laminar values, indicating a locally broadened flame front. In agreement with previous measurements, the maximum of $N_{\zeta}$, decreases strongly with increasing Karlovitz numbers. The conditional probability density functions are close to a log-normal distribution for scalar dissipation rates conditioned at the progress variable value where the scalar dissipation is maximum in unstretched laminar flame calculations. The time scale for the Favre-averaged mean scalar dissipation rate decreases in general across the turbulent flame brush from the unburnt to burnt side.

• Journal of Environmental Science International
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• v.26 no.9
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• pp.1073-1080
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• 2017

Manufacturing and technology industries produce large amounts of air pollutants. Ulsan Metropolitan City, South Korea, is well-known for its large industrial complexes; in particular, the concentration of $SO_2$ here is the highest in the country. We assessed $SO_2$ monitoring sites based on conditional and joint entropy, because this is a common method for determining an optimal air monitoring network. Monthly $SO_2$ concentrations from 12 air monitoring sites were collected, and the distribution of spatial locations was determined by kriging. Mean absolute error, Root Mean Squared Error (RMSE), bias and correlation coefficients were employed to evaluate the considered algorithms. An optimal air monitoring network for Ulsan was suggested based on the improvement of RMSE.

• Journal of Korean Society for Quality Management
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• v.23 no.3
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• pp.126-139
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• 1995

We describe a formal approach to the construction of optimal classification rule for the two-group normal classification with equal population mean problem. Based on the utility function of Bernardo, we suggest a balanced design for the classification and construct the optimal rule under the balanced design condition. The rule is characterized by a constrained minimization of total risk of misclassification, the constraint of which is constructed by the process of equation between expected utilities of the two group conditional densities. The efficacy of the suggested rule is examined through numerical studies. This indicates that, in case little is known about the relative population sizes, dramatic gains in accuracy of classification result can be achieved.

• Journal of Korea Water Resources Association
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• v.45 no.8
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• pp.815-826
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• 2012

The underestimating trend using existing ordinary regression (OR) based trend analysis has been a well-known problem. The existing OR method based on least squares approximate the conditional mean of the response variable given certain values of the time t, and the usual assumption of the OR method is normality, that is the distribution of data are not dissimilar form a normal distribution. In this regard, this study proposed a quantile regression that aims at estimating either the conditional median or other quantiles of the response variable. This study assess trend in annual daily maximum rainfall series over 64 weather stations through both in OR and QR approach. The QR method indicates that 47 stations out of 67 weather stations are a strong upward trend at 5% significance level while OR method identifies a significant trend only at 13 stations. This is mainly because the OR method is estimating the condition mean of the response variable. Unlike the OR method, the QR method allows us flexibly to detect the trends since the OR is designed to estimate conditional quantiles of the response variable. The proposed QR method can be effectively applied to estimate hydrologic trend for either non-normal data or skewed data.