• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.5
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• pp.2142-2147
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• 2012

This study is aimed at decreasing wrong diagnosis with corrected EF(Ejection Fraction) of 2D echo cardiography by analysing the physical time-resolution difference between Cine MRI and 2D echo cardiography and applying the corrected EF in 2D echocardiography. From February 2010 to December 2011, among the 110 patients who had undergone both 2D echo cardiography and cine MRI only 37 patient were selected suffering aortic valve regurgitation. ED, ES and SV were measured and EF was calculated in each system while normal ranges of Cine MRI and 2D echocardiography were compared to evauate misdiagnosis rate. The correlation of physical time resolution between 2D echocardiography and MRI was evaluated and the differences were corrected with linear regression coefficient which is derived from linear regression analysis. Blandt-Altman plot was used to evaluate the reliability of corrected 2D echo cardiography EF and compare the error among measured values. The values were compared with MRI normal range and misdiagnosis rate was measured again. As a result, misdiagnosis rates of physical time resolution were measured to be 32.4%(12people) before the correction of EF and 18.9%(7people) after the correction. Also, EF confirmed in Blandt-Altman plot were almost the same with MRI EF. In conclusion, when diagnosing aortic regurgitation disease, simply using 2D echocardiography can easily raise the misdiagnosis rates, therefore considering the MRI machine's physical merits, correcting the time resolution difference is important by calculating time resolution wrong diagnosis would decrease and it is considered to be useful in clinical circumstances.

• Journal of Preventive Medicine and Public Health
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• v.28 no.4 s.51
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• pp.863-873
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• 1995

This report describes a preperation and characterization of canine blood lead(Pb) standard reference material(SRM). Three adult beagle dogs(A, B, and C)were orally dosed with gelatin capsules containing $Pb(NO_3)_2$, equivalent to $10\sim80mg$ Pb/kg body weight. Blood was drawn 24 hours after the dose from the cephalic vein into lead free 500ml Pyrex beaker in which EDTA.K was contained as an anticoagulant. The amount of lead given to individual dog was varied arbitrarily. Three month later, 3 canine animals were orally dosed with lead secondarily to make mixed SRM(D1) which was mixed different concentrations of lead in bloods with A1, B1, and C1 in vitro. The SRMs for A, B, C, A1, B1, C1, and D1 were distributed 2ml each into more than 300 lead free bottles, and were stored in refregerator at $4^{\circ}C$. The amount of lead in canine whole blood samples were determined using a Varian 30A atomic absorption spectrophotometer(AAS) with a model GTA-96 graphite tube atomizer with D2 background correction and a Hitachi Z-8100 AAS with Zeeman background correction. The sensitivity and detection limits for lead determination of Varian 30A were $0.46{\mu}g/L,\;0.34{\mu}g/L,\;and\;0.56{\mu}g/L,\;0.14{\mu}g/L$ of Hitachi Z-8100, respectively. Day to day variations in determination of blood lead concentration in a certain sample were $31.11{\pm}1.36{\mu}g/100ml$ by Varian 30A, and $33.08{\pm}0.82{\mu}g/100ml$ by Hitachi Z-8100, showing the difference of 3% between the two results. At the blood lead concentrations of $56.31{\pm}1.98{\mu}g/100ml(A),\;40.89{\pm}0.80{\mu}g/100ml(B),\;59.01{\pm}1.38{\mu}g/100ml(C)$, the precisions of replicated measurements by AAS were 3.52%, 1.96%, and 2.34%, respectively. Coefficient variation(CV) of SRMs(A, B, and C) within a standard sample were ranged from 0.92% to 7.50%, and those between 5 standard samples were 1.21%, 2.64%, and 1.11%, respectively, showing inter-vial variation of $1{\mu}g/100ml$. Lead levels in SRMs during one month storage were unchanged. The overall recoveries were $89.6\sim100.4%,\;91.6\sim101.9%,\;90.3\sim100.0%$ for A, B, and C SRMs, means were $56.46{\pm}2.69{\mu}g/100ml,\;39.35{\pm}1.89{\mu}g/100ml,\;57.40{\pm}2.31{\mu}g/100ml$, and measurement ranges were$52.88{\pm}59.26{\mu}g/100ml,\;37.47{\pm}41.68{\mu}g/100ml,\;54.80{\pm}60.69{\mu}g/100ml$, respectively. Those results were laid within confidence limits values. The lead concentrations in the mixed sample(D1) stored over one month period were ranged from $32.76{\mu}g/100ml\;to\;33.54{\mu}g/100ml$, with CV ranging from 1.2% to 2.7%. The results were similiar to each of single samples(A1, B1, and C1) in respect of homogeneity and stability. Results of the mixed blood sample analysed after 1 month storage at $4^{\circ}C$ by four other laboratories(L1, L2, L3, L4) were similar with those of our laboratory($L5;31.18{\pm}0.24{\mu}g/100ml$, acceptable range by $CDC;25.18\sim37.18{\mu}g/100ml$), showing the concentrations of $25.91{\pm}1.19{\mu}g/100ml(L1),\;34.16{\pm}0.22{\mu}g/100ml(L2),\;35.68{\pm}0.85{\mu}g/100ml(L3),\;30.95{\pm}0.46{\mu}g/100ml(L4)$ in a each samples.

• Journal of the Korean Society of Radiology
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• v.12 no.6
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• pp.755-762
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• 2018

The purpose of this study was to compare the FA(faractional anisotropy) and ADC(apparent diffusion coefficient) values, which were derived from diffusion tensor imaging in breast cancer patients. The diffusion gradient used in this study was derived from quantitative diffusion indices using 20 directions(b-value, 0 and $1,000s/mm^2$). Quantitative analysis was analyzed using Pearson's correction and qualitative analysis using for correction coefficients. As a result, $FA_{min}$, $FA_{mean}$ and $FA_{max}$ were $0.098{\pm}0.065$, $0.302{\pm}0.142$ and $0.634{\pm}0.236$, respectively(p > 0.05). The $ADC_{min}$, $ADC_{mean}$ and $ADC_{max}$ were $0.741{\pm}0.403$, $1.095{\pm}0.394$ and $1.530{\pm}0.447$, respectively(p > 0.05). The $FA_{min}$, $FA_{mean}$, and $FA_{max}$ mean values were $0.132{\pm}0.050$, $0.418{\pm}0.094$, and $0.770{\pm}0.164$ for Category 6 and Kinetic Curve Pattern III, respectively. $ADC_{min}$, $ADC_{mean}$, and $ADC_{max}$ were $0.753{\pm}0.189$, $1.120{\pm}0.236$, and $1.615{\pm}0.372$, respectively. Quantitative analysis showed negative correlation between $ADC_{mean}-FA_{mean}$ and $ADC_{max}-FA_{max}$(p = 0.001, 0.003). The qalitative analysis showed ADC 0.628(p = 0.001), FA 0.620(p = 0.001) in the internal evaluations, ADC 0.677(p = 0.001), FA 0.695(p = 0.001) in external evaluations. In conclusion, based on the morphological examination, time to signal intensity graph is the form of wash-out(pattern III) in the dynamic contrast enhance examination, As a result, the $ADC_{mean}$ $1.120{\pm}0.236$ and $FA_{mean}$ values were $0.032{\pm}0.142$ with a negative correlation (Y=1.44-1.12X). Therefore, If we understand the shape of time to signal intensity graph and the relationship between ADC and FA, It will be a criterion for distinguishing malignant diseases in breast cancer.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.53 no.spc
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• pp.108-114
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• 2008

Near infrared spectroscopy (NIRS) is a rapid and accurate analytical method for determining the composition of agricultural products and feeds. The applicability of near infrared reflectance spectroscopic method was tested to determine the color value (L, a, b) of green tea. A total of 162 green tea calibration samples and 82 validation samples were used for NIRS equation development and validation, respectively. In the developed NIRS equation for analysis of the color value (L, a, b), the most accurate equation for L value was obtained at 2, 8, 6, 1 (2nd derivative, 8 nm gap, 6 points smoothing, and 1pointsecond smoothing), and for a, and b value were obtained at 1, 4, 4, 1 (1st derivative, 4 nm gap, 4points smoothing, and 1 point second smoothing) math treatment condition with SNVD (Standard Normal Variate and Detrend) scatter correction method and entire spectrum ($400{\sim}2,500\;nm$) by using MPLS (Modified Partial Least Squares) regression. Validation results of these NIRS equations showed very low bias (L: 0.005%, a: 0.003%, b: -0.013%) and standard error of prediction (SEP, L: 0.361%, a: 0.141%, b: 0.306%) as well as high coefficient of determination ($R^2$, L: 0.905, a: 0.986, b: 0.931). Therefore, these NIRS equations can be applicable and reliable for determination of color value (L, a, b) of green tea, and NIRS method could be used as a mass screening technique for breeding programs and quality control in the green tea industry.

• Journal of the Institute of Convergence Signal Processing
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• v.14 no.2
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• pp.136-146
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• 2013

In this paper, the residual delay compensation algorithm is proposed for FX-type KJJVC. In case of initial version as that design algorithm of KJJVC, the integer calculation and the cos/sin table for the phase compensation coefficient were introduced in order to speed up of calculation. The mismatch between data timing and residual delay phase and also between bit-jump and residual delay phase were found and fixed. In final design of KJJVC residual delay compensation algorithm, the initialization problem on the rotation memory of residual delay compensation was found when the residual delay compensated value was applied to FFT-segment, and this problem is also fixed by modifying the FPGA code. Using the proposed residual delay compensation algorithm, the band shape of cross power spectrum becomes flat, which means there is no significant loss over the whole bandwidth. To verify the effectiveness of proposed residual delay compensation algorithm, we conducted the correlation experiments for real observation data using the simulator and KJJVC. We confirmed that the designed residual delay compensation algorithm is well applied in KJJVC, and the signal to noise ratio increases by about 8%.

• The Journal of the Acoustical Society of Korea
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• v.32 no.1
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• pp.14-21
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• 2013

The erosion, suspension, and transport of sediment frequently occur in the coastal waters and estuarine. These processes often generate the so-called fluid mud layer, which is defined as a high-concentration aqueous suspension of fine grained sediment (> 10 g/l), consisting mainly of silt and clay-size particles. Therefore the high-resolution ultrasound is mostly used to detect or monitor the fluid mud layer. Because the sound attenuation tends to increase rapidly with the suspended sediment concentration, it is necessary to consider the accurate attenuation correction to estimate the backscattering strengths from the suspended sediment layers. In this paper, the volume backscattering strengths with various suspended sediment concentrations were measured using 5-MHz ultrasound signal in a small-scale water tank. The sound attenuation due to the viscosity and scattering from suspended sediment particles was predicted by the Richard's model and applied to the sonar equation to estimate the volume backscattering strengths from the suspended sediment concentrations. For the case that the additional attenuation was not considered, the volume backscattering strengths increased to the concentration of 20 g/l, and over this point, the backscattering strengths were roughly constant. However, for the case that the attenuation due to the suspended sediment concentration was considered, the backscattering strengths increased with the concentration.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.3
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• pp.93-101
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• 2017

The distribution of inter-annual variation in temperature would help evaluate the likelihood of a climatic risk and assess suitable zones of crops under climate change. In this study, we evaluated two methods to estimate the standard deviation of temperature in the areas where weather information is limited. We calculated the monthly standard deviation of temperature by collecting temperature at 0600 and 1500 local standard time from 10 automated weather stations (AWS). These weather stations were installed in the range of 8 to 1,073m above sea level within a mountainous catchment for 2011-2015. The observed values were compared with estimates, which were calculated using a geospatial correction scheme to derive the site-specific temperature. Those estimates explained 88 and 86% of the temperature variations at 0600 and 1500 LST, respectively. However, it often underestimated the temperatures. In the spring and fall, it tended to had different variance (e.g., increasing or decreasing pattern) from lower to higher elevation with the observed values. A regression analysis was also conducted to quantify the relationship between the standard deviation in temperature and the topography. The regression equation explained a relatively large variation of the monthly standard deviation when lapse-rate corrected temperature, basic topographical variables (e.g., slope, and aspect) and topographical variables related to temperature (e.g., thermal belt, cold air drainage, and brightness index) were used. The coefficient of determination for the regression analysis ranged between 0.46 and 0.98. It was expected that the regression model could account for 70% of the spatial variation of the standard deviation when the monthly standard deviation was predicted by using the minimum-maximum effective range of topographical variables for the area.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.2
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• pp.277-287
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• 2017

This paper describes the specifications on balanced steel ratio and maximum reinforcement for the design of RC flexural members by the Korean Highway Bridge Design Code based on limit states design. The Korean Highway Bridge Design Code (Limit States Design) is not provide for the balanced steel ratio specification for the calculation of required steel area of RC flexural members design. The maximum steel area limited the depth of the neutral axis at the ultimate limit states after redistribution of the moment, and also recommended the maximum steel area should not exceed 4 percent of the cross sectional area. However, from the maximum neutral axis depth provisions should increase the cross section is calculated to be less the maximum reinforcement area, and according to the 4% of the cross sectional area of the concrete, the tensile strain of the reinforcement is calculated to be greater than double the yielding strain, so can not guarantee a ductile behavior. This study developed a balanced reinforcement ratio that is basis for the required reinforcement calculation for tension-controlled RC flexural members design in the ultimate limit states verification provisons and material properties and applied the ultimate strain of the concrete compressive strength with a simple formular to be applied to design practice induced. And assumed the minimum allowable tensile strain of reinforcement double the yielding strain, and applying correction coefficient up to the ratio of maximum neutral axis depth, proposed maximum steel ratio that can be applied irrespective of the reinforcement yield strength and concrete compressive strength.

• Journal of The Korean Society of Grassland and Forage Science
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• v.26 no.1
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• pp.45-52
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• 2006

This study was carried out to explore the accuracy of Near Infrared Reflectance Spectroscopy (NIRS) fer the prediction of digestibility and energy value of corn silages. The spectral data were regressed against a range of digestibility and energy parameters using modified partial least squares(MPLS) multivariate analysis in conjunction with first and second order derivatization, with scatter correction procedure(SNV-Detrend) to reduce the effect of extraneous noise. Calibration models for NIRS measurements gave multivariate correlation coefficients of determination$(R^2)$ and standard errors of cross validation of 0.92(SECV 1.73), 0.91(SECV 1.13) and 0.93(SECV 1.74) for in vitro dry matter digestibility(IVDMD), in vitro true digestibility(IVTD), and cellulase dry matter digestibility(CDMD), respectively. The standard error of prediction(SEP) and the multiple correlation coefficient of validation$(R^2v)$ on the validation set(n=39) was used in comparing the prediction accuracy. The SEP value was 0.30(TDN), 0.01(NEL), and 0.01(ME). The relative ability of NIRS to predict digestibility and energy value was very good for CDMD, total digestible nutrients(TDN), net energy fer lactation(NEL) and metabolizable energy(ME). This paper shows the potential of NIRS to predict the digestibility and energy value of con silage as a routine method in feeding programmes and for giving advice to farmers.

• Journal of Korea Water Resources Association
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• v.51 no.2
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• pp.151-163
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• 2018

The objective of this study was to estimate LOADEST (LOAD Estimator) coefficients for simulating pollutant loads in ungauged watersheds. Regression models of LOADEST were used to simulate pollutant loads, and the multiple linear regression (MLR) was used for coefficients estimation on watershed characteristics. The fifth and third model of LOADEST were selected to simulate T-N (Total-Nitrogen) and T-P (Total-Phosphorous) loads, respectively. The results and statistics indicated that regression models based on LOADEST simulated pollutant loads reasonably and model coefficients were reliable. However, the results also indicated that LOADEST underestimated pollutant loads and had a bias. For this reason, simulated loads were corrected the bias by a quantile mapping method in this study. Corrected loads indicated that the bias correction was effective. Using multiple regression analysis, a coefficient estimation methods according to the watershed characteristic were developed. Coefficients which calculated by MLR were used in models. The simulated result and statistics indicated that MLR estimated the model coefficients reasonably. Regression models developed in this study would help simulate pollutant loads for ungauged watersheds and be a screen model for policy decision.