• Tribology and Lubricants
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• v.1 no.1
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• pp.38-45
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• 1985

Ferrograms prepared from off samples collected during testing in the transition region were originally diluted at 20:1. To obtain some information about the effect of dilution on the analysis procedures, a series of measurements were made on ferrograms prepared to different dilutions in the range 6 to 30:1 from oil samples collected after testing in the four ball machine at the 51 kg and 55 kg load, respectively, Fig. 1. The variations in area covered, perimeter, intercept and particle count were then plotted as a function of dilution level and appropriate mathematical expressions established such that the results obtained at any dilution level specified within the range can then be corrected back to an equivalent undiluted value. The effect of dilution on the variance of the particle size distribution was also investigated. The main results are tabulated, Tables 1-5 and also plotted as a function of dilution, level Figs. 2-9.

• Communications for Statistical Applications and Methods
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• v.19 no.3
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• pp.345-358
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• 2012

In a parametric sample selection model, the distribution assumption is critical to obtain consistent estimates. Conventionally, the normality assumption has been adopted for both error terms in selection and main equations of the model. The normality assumption, however, may excessively restrict the true underlying distribution of the model. This study introduces the $S_U$-normal distribution into the error distribution of a sample selection model. The $S_U$-normal distribution can accommodate a wide range of skewness and kurtosis compared to the normal distribution. It also includes the normal distribution as a limiting distribution. Moreover, the $S_U$-normal distribution can be easily extended to multivariate dimensions. We provide the log-likelihood function and expected value formula based on a bivariate $S_U$-normal distribution in a sample selection model. The results of simulations indicate the $S_U$-normal model outperforms the normal model for the consistency of estimators. As an empirical application, we provide the sample selection model for car ownership and a car expense relationship.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.28 no.5
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• pp.320-325
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• 2015

This paper dealt with a defect identification algorithm which is based on single partial discharge (PD) pulse analysis in gas insulated structure. Four types of electrode systems such as a needle-plane, a plane-needle, a free particle and a crack inside spacer were fabricated to simulate defects in gas insulated switchgear (GIS). We measured single PD pulse by an oscilloscope with a sampling rate of 5 GS/s and a frequency bandwidth of 1 GHz. Data aquisition and signal processing were controlled by a LabVIEW program. Physical shapes of PD pulses were compared with kurtosis, skewness and time-based parameters as rising time, falling time and pulse-width. These parameters were analysed by an algorithm with a back propagation algorithm (BPA). By applying the algorithm, the identification rate was 97% for the needle-plane electrode, 96% for the plane-needle electrode, 91% for the free particle and 93% for the crack inside spacer. The results verified that the algorithm could identify the type of defects in GIS.

• Journal of Korea Water Resources Association
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• v.40 no.10
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• pp.793-800
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• 2007

This research applied to Wavelet transform that have soft resolution time and frequency area for stage of Hadong2 station in order to extract to discharge component by rainfall and tidal level component by tide. Approximation component(A6) of last level for wavelet decomposition displayed the biggest energy value 87.77%, and detail component(D3) energy value was 10.70% with periodicity of semidiurnal tide type(about 12 hours). Also skewness, kurtosis values of D3 have similar to tidal level of Yeosu. Approximation component(A6), Detail component(D6, D5) for Hadong2 stage was runoff component, and detail component(D4, D3, D2) was tide component according to effect of tide.

• Imaging Science in Dentistry
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• v.43 no.3
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• pp.153-161
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• 2013

Purpose: To prevent low bone mineral density (BMD), that is, osteoporosis, in postmenopausal women, it is essential to diagnose osteoporosis more precisely. This study presented an automatic approach utilizing a histogram-based automatic clustering (HAC) algorithm with a support vector machine (SVM) to analyse dental panoramic radiographs (DPRs) and thus improve diagnostic accuracy by identifying postmenopausal women with low BMD or osteoporosis. Materials and Methods: We integrated our newly-proposed histogram-based automatic clustering (HAC) algorithm with our previously-designed computer-aided diagnosis system. The extracted moment-based features (mean, variance, skewness, and kurtosis) of the mandibular cortical width for the radial basis function (RBF) SVM classifier were employed. We also compared the diagnostic efficacy of the SVM model with the back propagation (BP) neural network model. In this study, DPRs and BMD measurements of 100 postmenopausal women patients (aged >50 years), with no previous record of osteoporosis, were randomly selected for inclusion. Results: The accuracy, sensitivity, and specificity of the BMD measurements using our HAC-SVM model to identify women with low BMD were 93.0% (88.0%-98.0%), 95.8% (91.9%-99.7%) and 86.6% (79.9%-93.3%), respectively, at the lumbar spine; and 89.0% (82.9%-95.1%), 96.0% (92.2%-99.8%) and 84.0% (76.8%-91.2%), respectively, at the femoral neck. Conclusion: Our experimental results predict that the proposed HAC-SVM model combination applied on DPRs could be useful to assist dentists in early diagnosis and help to reduce the morbidity and mortality associated with low BMD and osteoporosis.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.5
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• pp.1861-1870
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• 2013

A climate change-driven increased hydrological variability has been widely acknowledged over the past decades. In this regards, rainfall simulation techniques are being applied in many countries to consider the increased variability. This study proposed a Homogeneous Hidden Markov Chain(HMM) designed to recognize rather complex patterns of rainfall with discrete hidden states and underlying distribution characteristics via mixture probability density function. The proposed approach was applied to Seoul and Jeonju station to verify model's performance. Statistical moments(e.g. mean, variance, skewness and kurtosis) derived by daily and seasonal rainfall were compared with observation. It was found that the proposed HMM showed better performance in terms of reproducing underlying distribution characteristics. Especially, the HMM was much better than the existing Markov Chain model in reproducing extremes. In this regard, the proposed HMM could be used to evaluate a long-term runoff and design flood as inputs.

• Korean Journal of Clinical Pharmacy
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• v.21 no.2
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• pp.74-80
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• 2011

Population pharmacokinetics for gentamicin were compared with 20 Korean patients (14 male and 6 female) and 25 Caucasian appendicitis patients (16 male and 9 female). Two to six blood specimens were collected from all patients at the following times : just before a regularly scheduled infusion and at 0.5 hour after the end of a 0.5 hour infusion. Nonparametric expected maximum(NPEM) algorithm for population modeling was used. The estimated parameters were the elimination rate constant(K), the slope(KS) of the relationship between K versus creatinine clearance(Ccr), the apparent volume of distribution (V), the slope(VS) of the relationship between V versus weight, gentamicin clearance(CL) and the slope(CS) of the relationship between CL versus Ccr and the V. The output includes two marginal probability density function(PDF), means, medians, modes, variance, skewness, kurtosis, and CV%. The mean K(KS) were$0.402{\pm}0.129hr^{-1}$ ($0.00486{\pm}0.00197[hr{\cdot}mL/min/1.73m^2]^{-1}$) and $0.425{\pm}0.137hr^{-1}$($0.00432{\pm}0.00168[hr{\cdot}mL/min/1.73m^2]^{-1}$) for Korean and Caucasian populations, respectively. The mean V(VS) were not different at $14.3{\pm}3.69L$($0.241{\pm}0.0511L/kg$) and $15.8{\pm}4.81L$($0.236{\pm}0.0531L/kg$) for Korean and Caucasian populations, respectively (P>0.2). The mean CL(CS) were $5.68{\pm}1.69L/hr$ ($0.0714{\pm}0.0222L/kg[hr{\cdot}mL/min/1.73m^2]$) and $6.29{\pm}1.84L/hr$ ($0.0629{\pm}0.0189L/kg[hr{\cdot}mL/min/1.73m^2]$) for Korean and Caucasian populations, respectively. There are no differences in gentamicin pharmacokinetics between Korean and Caucasian appendicitis patients.

• Magazine of the Korean Society of Agricultural Engineers
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• v.40 no.4
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• pp.45-57
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• 1998

This study was conducted to derive optimal design floods by Generalized Extreme Value (GEV) distribution for the annual maximum series at ten watersheds along Han, Nagdong, Geum, Yeongsan and Seomjin river systems. Adequacy for the analysis of flood data used in this study was established by the tests of Independence, Homogeneity, detection of Outliers. L-coefficient of variation, L-skewness and L-kurtosis were calculated by L-moment ratio respectively. Parameters were estimated by the Methods of Moments and L-Moments. Design floods obtained by Methods of Moments and L-Moments using different methods for plotting positions in GEV distribution were compared by the Relative Mean Errors(RME) and Relative Absolute Errors(RAE). The results were analyzed and summarized as follows. 1. Adequacy for the analysis of flood data was acknowledged by the tests of Independence, Homogeneity and detection of Outliers. 2. GEV distribution used in this study was found to be more suitable one than Pearson type 3 distribution by the goodness of fit test using Kolmogorov-Smirnov test and L-Moment ratios diagram in the applied watersheds. 3. Parameters for GEV distribution were estimated using Methods of Moments and L-Moments. 4. Design floods were calculated by Methods of Moments and L-Moments in GEV distribution. 5. It was found that design floods derived by the method of L-Moments using Weibull plotting position formula in GEV distribution are much closer to those of the observed data in comparison with those obtained by method of moments using different formulas for plotting positions from the viewpoint of Relative Mean Errors and Relative Absolute Errors.

• Wind and Structures
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• v.26 no.1
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• pp.11-24
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• 2018

Full-scale measurements of wind action on the open roof structure of the WuXi grand theater, which is composed of eight large-span free-form leaf-shaped space trusses with the largest span of 76.79 m, were conducted during the passage of Typhoons HaiKui and SuLi. The wind pressure field data were continuously and simultaneously monitored using a wind pressure monitoring system installed on the roof structure during the typhoons. A detailed analysis of the field data was performed to investigate the characteristics of the fluctuating wind pressure on the open roof, such as the wind pressure spectrum, spatial correlation coefficients, peak wind pressures and non-Gaussian wind pressure characteristics, under typhoon conditions. Three classical methods were used to calculate the peak factors of the wind pressure on the open roof, and the suggested design method and peak factors were given. The non-Gaussianity of the wind pressure was discussed in terms of the third and fourth statistical moments of the measured wind pressure, and the corresponding indication of the non-Gaussianity on the open roof was proposed. The result shows that there were large pulses in the time-histories of the measured wind pressure on Roof A2 in the field. The spatial correlation of the wind pressures on roof A2 between the upper surface and lower surface is very weak. When the skewness is larger than 0.3 and the kurtosis is larger than 3.7, the wind pressure time series on roof A2 can be taken as a non-Gaussian distribution, and the other series can be taken as a Gaussian distribution.

• Environmental and Resource Economics Review
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• v.16 no.4
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• pp.947-978
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• 2007

In this paper, we investigated a Value-at-Risk approach to the volatility of two crude oil markets (Brent and Dubai). We also assessed the performance of various VaR models (RiskMetrics, GARCH, IGARCH and FIGARCH models) with the normal and skewed Student-t distribution innovations. The FIGARCH model outperforms the GARCH and IGARCH models in capturing the long memory property in the volatility of crude oil markets returns. This implies that the long memory property is prevalent in the volatility of crude oil returns. In addition, from the results of VaR analysis, the FIGARCH model with the skewed Student-t distribution innovation predicts critical loss more accurately than other models with the normal distribution innovation for both long and short positions. This finding indicates that the skewed Student-t distribution innovation is better for modeling the skewness and excess kurtosis in the distribution of crude oil returns. Overall, these findings might improve the measurement of the dynamics of crude oil prices and provide an accurate estimation of VaR for buyers and sellers in crude oil markets.