An, Tae-Jin;Ryu, Hui-Jeong;Jeong, Gwang-Geun;Sim, Myeong-Pil
Journal of Korea Water Resources Association
/
v.33
no.3
/
pp.365-374
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2000
This paper is to present the determination of the optimal Joss rate parameters and urnt bydrographs from the observed single rainfall-runoff event using optimization models coupled with a stochastic technique for the global solution. Two kinds of the linear program models are formulated to derive the optimal unit hydrographs and loss rate parameters for gaged basins; one mimmizes the summation of the absolute residual between predlCted and observed runoff ordinates and the other, the maximum absolute residuaL Multistart algorithm which is one or stochastic techniques for the global optimum is adopted to perturb the parameters of the loss rate equations. Multistart efficiently searches the feasIble region to identify the global optimlUll for loss rate parameters, which yields the optimal loss rate parameters and unit hydrograph for Kostiakov's, Plulip's, and Horton's equation. The unique unit hydrograph ordinates for a gIven rainfall-runoff event iS exclusrvely obtained WIth $\Phi$ index, but unit hydrograph ordinates depend upon the parameters [or each loss rate equations. The parameters of Green-Ampt's are determined through a trial and error method. In this paper the single rainfall-nmoff event observed from a watershed is considered to test the proposed method. The optimal unit hydrograph herein found has smaller deviations than the ones reported previously by other researchers.
For the evaluation of roadway safety, diverse methods, including before-after studies, simple comparison using historic traffic accident data, methods based on experts' opinion or literature, have been applied. Especially, many research efforts have developed traffic accident prediction models in order to identify critical elements causing accidents and evaluate the level of safety. A traffic accident prediction model must secure predictability and transferability. By acquiring the predictability, the model can increase the accuracy in predicting the frequency of accidents qualitatively and quantitatively. By guaranteeing the transferability, the model can be used for other locations with acceptable accuracy. To this end, traffic accident prediction models using non-linear regression, artificial neural network, and structural equation were developed in this study. The predictability and transferability of three models were compared using a model development data set collected from 90 signalized intersections and a model validation data set from other 33 signalized intersections based on mean absolute deviation and mean squared prediction error. As a result of the comparison using the model development data set, the artificial neural network showed the highest predictability. However, the non-linear regression model was found out to be most appropriate in the comparison using the model validation data set. Conclusively, the artificial neural network has a strong ability in representing the relationship between the frequency of traffic accidents and traffic and road design elements. However, the predictability of the artificial neural network significantly decreased when the artificial neural network was applied to a new data which was not used in the model developing.
The cautious blasting works had been used with emulsion explosion electric M/S delay caps. Drill depth was from 3m to 6m with Crawler Drill ${\phi}70mm$ on the calcalious sand stone (soft -modelate -semi hard Rock). The total numbers of test blast were 88. Scale distance were induced 15.52-60.32. It was applied to propagation Law in blasting vibration as follows. Propagtion Law in Blasting Vibration $V=K(\frac{D}{W^b})^n$ were V : Peak partical velocity(cm/sec) D : Distance between explosion and recording sites(m) W : Maximum charge per delay-period of eight milliseconds or more (kg) K : Ground transmission constant, empirically determind on the Rocks, Explosive and drilling pattern ets. b : Charge exponents n : Reduced exponents where the quantity $\frac{D}{W^b}$ is known as the scale distance. Above equation is worked by the U.S Bureau of Mines to determine peak particle velocity. The propagation Law can be catagorized in three groups. Cubic root Scaling charge per delay Square root Scaling of charge per delay Site-specific Scaling of charge Per delay Plots of peak particle velocity versus distoance were made on log-log coordinates. The data are grouped by test and P.P.V. The linear grouping of the data permits their representation by an equation of the form ; $V=K(\frac{D}{W^{\frac{1}{3}})^{-n}$ The value of K(41 or 124) and n(1.41 or 1.66) were determined for each set of data by the method of least squores. Statistical tests showed that a common slope, n, could be used for all data of a given components. Charge and reduction exponents carried out by multiple regressional analysis. It's divided into under loom over loom distance because the frequency is verified by the distance from blast site. Empirical equation of cautious blasting vibration is as follows. Over 30m ------- under l00m ${\cdots\cdots\cdots}{\;}41(D/sqrt[2]{W})^{-1.41}{\;}{\cdots\cdots\cdots\cdots\cdots}{\;}A$ Over 100m ${\cdots\cdots\cdots\cdots\cdots}{\;}121(D/sqrt[3]{W})^{-1.66}{\;}{\cdots\cdots\cdots\cdots\cdots}{\;}B$ where ; V is peak particle velocity In cm / sec D is distance in m and W, maximLlm charge weight per day in kg K value on the above equation has to be more specified for further understaring about the effect of explosives, Rock strength. And Drilling pattern on the vibration levels, it is necessary to carry out more tests.
Journal of the Korea Academia-Industrial cooperation Society
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v.10
no.5
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pp.1082-1090
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2009
Peak expiratory flow rate(PEF) is a very important diagnostic parameter obtained from the forced vital capacity(FVC) test. The expiratory flow rate increases during the short initial time period and may cause measurement error in PEF particularly due to non-ideal dynamic characteristic of the transducer. The present study evaluated the initial rise slope($S_r$) on the flow rate signal to compensate the transducer output data. The 26 standard signals recommended by the American Thoracic Society(ATS) were generated and flown through the velocity-type respiratory air flow transducer with simultaneously acquiring the transducer output signal. Most PEF and the corresponding output($N_{PEF}$) were well fitted into a quadratic equation with a high enough correlation coefficient of 0.9997. But only two(ATS#2 and 26) signals resulted significant deviation of $N_{PEF}$ with relative errors>10%. The relationship between the relative error in $N_{PEF}$ and $S_r$ was found to be linear, based on which $N_{PEF}$ data were compensated. As a result, the 99% confidence interval of PEF error was turned out to be approximately 2.5%, which was less than a quarter of the upper limit of 10% recommended by ATS. Therefore, the present compensation technique was proved to be very accurate, complying the international standards of ATS, which would be useful to calibrate respiratory air flow transducers.
Objectives: It is certain that Radioactive iodine thyroid uptake(RAIU) rate should be measured with the standard counts considering the thyroid gland depth in enlarged thyroid patients for the variation from geometric factors. The purpose of this paper is to consider the effects of geometric factors according to detector to source distance and the effective thyroid depth on RAIU rate with experiment test. Materials and Methods: I-131 370 kBq ($10{\mu}Ci$) point source was measured by Captus-3000 thyroid uptake system (Capintec, NJ, USA) with a change Detector-Source Distance from 20 cm to 30 cm at an interval of 1 cm. And we changed the Neck phantom surface-Source Depth in the phantom with 1 cm, 2 cm, 5 cm using the neck phantom in order to reproduce the effective thyroid depth. Results: Every experimental group follows power curve as inverse square curve ($$R2{\geq_-}0.915$$). The average count rates in the case not using a phantom and the every case applied the effective thyroid depth using a phantom was not identical each other. There was significant fluctuations upon the effective thyroid depths applied the effective thyroid depth above 1 cm in $364.4 keV{\pm}10%$ energy ROI (p<0.01). There was not significant difference between the count rates of 1 cm and 2 cm in $364.4keV{\pm}20%$ and $637.1keV{\pm}6.2%$ (p=0.354, p=0.397). In assumed RAIU rate from regression equation, $364.4keV{\pm}20%$ was lower difference than $364.4keV{\pm}10%$ as 6.42% and 5.09% per 1 cm. Every change of count rate upon depth appears decreased line on Linear Regression, but the case of $284.3keV{\pm}10%$ increased only. And also, The graphs of coefficient of variation upon depth increased as straight line on every experimental group. Conclusion: The result appears that application of $364.4keV{\pm}20%$ energy ROI is more suitable for reducing error from the effective thyroid depth. And also, we can estimate the error of 20 cm should be highly reduced than 30 cm for Inverse Square Law. Therefore, If there is not information of the thyroid depth, it is considered that the error from thyroid depth can reduce through set up energy ROIs for $364.4keV{\pm}20%$, and increase Detector-Source Distances.
This study is to estimate soil moisture (SM) using Sentinel-1A/B C-band SAR (synthetic aperture radar) images and Multiple Linear Regression Model(MLRM) in the Yongdam-Dam watershed of South Korea. Both the Sentinel-1A and -1B images (6 days interval and 10 m resolution) were collected for 5 years from 2015 to 2019. The geometric, radiometric, and noise corrections were performed using the SNAP (SentiNel Application Platform) software and converted to backscattering coefficient of VV and VH polarization. The in-situ SM data measured at 6 locations using TDR were used to validate the estimated SM results. The 5 days antecedent precipitation data were also collected to overcome the estimation difficulty for the vegetated area not reaching the ground. The MLRM modeling was performed using yearly data and seasonal data set, and correlation analysis was performed according to the number of the independent variable. The estimated SM was verified with observed SM using the coefficient of determination (R2) and the root mean square error (RMSE). As a result of SM modeling using only BSC in the grass area, R2 was 0.13 and RMSE was 4.83%. When 5 days of antecedent precipitation data was used, R2 was 0.37 and RMSE was 4.11%. With the use of dry days and seasonal regression equation to reflect the decrease pattern and seasonal variability of SM, the correlation increased significantly with R2 of 0.69 and RMSE of 2.88%.
Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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2001.06a
/
pp.2111-2111
/
2001
A chemoinfometrical method for evaluating the quantitative determination of crystallinity one polymorphs based on fourie-transformed near-infrared (FT-NIR) spectroscopy was established. A direct comparison of the data with the ones collected from using the and compared with the conventional powder X-ray diffraction method was performed. [Method] The pPure a and g forms of indomethacin (IMC) were prepared by reportedusing published methods. Six kinds of standard samples obtained by physically mixing of a and g forms. After the powder X-ray diffraction profiles of samples have been measured, the intensity values were normalized to against the intensity of silicon powder as the as an external standard. The calibration curves for quantification of crystal content were based upon the total relative intensity of four diffraction peaks from of the form g crystal. FT-NIR spectra of six calibration sample sets were recorded 5 times with the NIR spectrometer (BRAN+LUEBBE). Chemoinfometric analysis was performed on the NIR spectral data sets by applying the principal component regression (PCR). [Results] The relation between the actual and predicted polymorphic contents of form g IMC measured using by the X-ray diffraction method shows a good straight linen linear relation., and it has slope of 0.023, an intercept of 0.131 and a correlation coefficient of 0.986. PCR analyses wereis was performed based on normalized NIR spectra sets offer standard samples of known content of IMC g form. IMC. A calibration equation was determined to minimize the root mean square error of the predictionthe prediction. Figure 1 shows a plot of the calibration data obtained by NIR method between the actual and predicted contents of form g IMC. The predicted values were reproducible and had a smaller standard deviation. Figure 2 shows that the plot for the predicted transformation rate (%) of form a IMC to form g as measured by X-ray diffractomeoy against to those as measured by NIR method. The plot has a slope of 1.296, an intercept of 1,109, and a correlation coefficient of 0.992. The line represents a satisfactory correlation between the two predicted values of form g IMC content. Thus NIR spectroscopy is an effective method for the evaluation to the pharmaceutical products of quantitative of polymorph.
The retention behaviors of natural gas components were studied on a single column by gas chromatography. The dead time, $t_0$ was obtained by using extrapolation of homologous series to determine capacity factors. The plots of retention data for homologous series and carbon number at different temperatures were shown to converge into a single point, which point was determined as a dead time. The results of the effect of temperature on the column efficiency for n-butane exhibited the plate number, N incerased with temperature, but the resolution among the fast eluted components decreased. The adsorption enthalpy (${\Delta}H^0{_{ads}}$) for each component on 28% DC 200 stationary phase was determined, and in order to investigate the retention behaviors of natural gas components the regression analysis of log $t_R$, log k' and log ${\alpha}$ vs. van der Waals volume(Vw), molecular connectivity index(X) and hydrophobic fragmental constant(f) were carred out. Good correlation was found between log k' vs. Vw, and log k' vs. f. The correlations between the physical properties of natural gas and the physical parameters were investigated by the linear regression analysis. The relationships between Vw vs. molecular weight and heating value(${\Delta}H_{comb}$), X vs. boiling point, and f vs. molecular weight, boiling point and heating value exhibited the high correlation coefficient more than 0.99. Using the regression equation between the heating value of natural gas and Vw the predicted heating values from $C_6$ to $C_{10}$ showed good agreement with those reported in the literature within 0.2% relative error.
A response surface model was developed for predicting the growth rates of Staphylococcus aureus in tryptic soy broth (TSB) medium as a function of combined effects of temperature, pH, and NaCl. The TSB containing six different concentrations of NaCl (0, 2, 4, 6, 8, and 10%) was adjusted to an initial of six different pH levels (pH 4, 5, 6, 7, 8, 9, and 10) and incubated at 10, 20, 30, and $40^{\circ}C$. In all experimental variables, the primary growth curves were well ($r^2=0.9000$ to 0.9975) fitted to a Gompertz equation to obtain growth rates. The secondary response surface model for natural logarithm transformations of growth rates as a function of combined effects of temperature, pH, and NaCl was obtained by SAS's general linear analysis. The predicted growth rates of the S. aureus were generally decreased by basic (pH 9-10) or acidic (pH 5-6) conditions and higher NaCl concentrations. The response surface model was identified as an appropriate secondary model for growth rates on the basis of correlation coefficient (r=0.9703), determination coefficient ($r^2=0.9415$), mean square error (MSE=0.0185), bias factor ($B_f=1.0216$), and accuracy factor ($A_f=1.2583$). Therefore, the developed secondary model proved reliable for predictions of the combined effect of temperature, NaCl, and pH on growth rates for S. aureus in TSB medium.
This study was conducted to develop an automatic nutrient-solution mixing system for small-scale sewers. The nutrient-solution mixing system consisted of a low-cost and precise metering device and data acquisition & control system with a personal computer. and, the metering device was composed of three parts those were supply pumps, metering cylinders and venturi tube. The system controlled electric conductivity(EC) and pH of nutrient-solution based on the time-based feedback control method with the information about temperature, EC, and pH of the nutrient-solution. The performance of the nutrient-solution mixing system was evaluated through the control of EC and pH while compared with those of commercial system. Also an experimental cultivation of tomato was conducted to verify and to improve the developed system. Results of this study were as follows. 1. The correlation coefficient of meteing device between the flow rate and operating time was 0.9999, and the linear reuession equation computed was y=21.759x, where y is the discharge($g$) and x is the operating time(s). 2. Calculated errors for the developed metering device and two commercial pump were $\pm$0.3% $\pm$2.45% and $\pm$1.38 % FS error respectively. 3. An automatic nutrient-solution mixing system based on a low-cost and precise metering device was developed. 4. The full scale errors of the developed system in controlling EC and pH at 23$\pm$1$^{\circ}C$ were $\pm$0.05mS/cm and $\pm$0.2, respectively 5. When using the commercial system, the controlled values of EC and pH of the 500 $\ell$ of water were 1.29 mS/cm and 6.1 pH for the setting points of 1.4 mS/cm and 6.0 pH respectively at 23$pm1^{\circ}C$. 6. The developed nutrient-solution control system showed $\pm$0.05 ms/cm of deviation from the setting EC value over the experimental cultivation period. 7. The deviation from the average values of Ca and Mg mass content in the several nutrient-solution were 0.5% and 1.8% respectively.
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