• Applied Chemistry for Engineering
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• v.33 no.6
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• pp.563-573
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• 2022

This work aimed to develop a new equation for turbidity (Turb) simulation and prediction using statistical methods based on principal component analysis (PCA) and multiple linear regression (MLR). For this purpose, water samples were collected monthly over a five year period from Cheurfa dam, an important reservoir in Northwestern Algeria, and analyzed for 12 parameters, including temperature (T°), pH, electrical conductivity (EC), turbidity (Turb), dissolved oxygen (DO), ammonium (NH₄⁺), nitrate (NO₃^-), nitrite (NO₂^-), phosphate (PO₄^3-), total suspended solids (TSS), biochemical oxygen demand (BOD₅) and chemical oxygen demand (COD). The results revealed a strong mineralization of the water and low dissolved oxygen (DO) content during the summer period. High levels of TSS and Turb were recorded during rainy periods. In addition, water was charged with phosphate (PO₄^3-) in the whole period of study. The PCA results revealed ten factors, three of which were significant (eigenvalues >1) and explained 75.5% of the total variance. The F1 and F2 factors explained 36.5% and 26.7% of the total variance, respectively and indicated anthropogenic pollution of domestic agricultural and industrial origin. The MLR turbidity simulation model exhibited a high coefficient of determination (R² = 92.20%), indicating that 92.20% of the data variability can be explained by the model. TSS, DO, EC, NO₃^-, NO₂^-, and COD were the most significant contributing parameters (p values << 0.05) in turbidity prediction. The present study can help with decision-making on the management and monitoring of the water quality of the dam, which is the primary source of drinking water in this region.

• Journal of Korean Society of Forest Science
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• v.90 no.1
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• pp.113-123
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• 2001

The main purpose of this study was to provide information on attenuation effects in forest tree belt of pine stand and oak stand. The relationships between DBH, tree height, clear length, crown area and number of trees and also between distance from noise origin, landslope etc. were analysed by correlation and multiple regression. The results obtained were as follows : 1. There was no difference between pine stand and oak stand in effecting noise attenuation. 2. The noise pressure was highly correlated with all of seven elements tested and both DBH and distance from noise origin have higher r-values than the others. For the pine stand, it was 0.9133 in DBH and 0.9630 in the distance and for the oak stand, 0.9296 in DBH and 0.9565 in the distance. 3. The optimum regression equation for pine stand and oak stand were made by combination of two variables (DBH and distance). The table of noise attenuation was made by optimum regression equation. In the case of pine stand, the attenuation ratio was 29% at 5m, 31.6~32.6% at 10m, 38.3~39.8% at 20m and 45.2~46.6% at 30m. And case of oak stand, the attenuation ratio was 29% at 5m, 31.6~34.2% at 10m, 38.6~41.4% at 20m and 45~47.2% at 30m. 4. As the noise pressure limit at the Urban housing area according to environmental laws is under 55dB, it is suggested by the table of noise attenuation that the distance, and DBH for the pine and oak stand are over 20m, 400cm and 30-35 trees, respectively.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.21 no.4
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• pp.325-334
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• 2008

The standard prestressed concrete I-girder bridge (PSC I-girder bridge) is one of the most prevalent types for small and medium bridges in Korea. When determining the member forces in a section to assess the safety of girder in this type of bridge, the general practice is to use the simplified practical equations or the live load distribution factors proposed in design standards rather than the precise analysis through the finite element method or so. Meanwhile, the live load distribution factors currently used in Korean design practice are just a reflection of overseas research results or design standards without alterations. Therefore, it is necessary to develop an equation of the live load distribution factors fit for the design conditions of Korea, considering the standardized section of standard PSC I-girder bridges and the design strength of concrete. In this study, to develop an equation of the live load distribution factors, a parametric analysis and sensitivity analysis were carried out on the parameters such as width of bridge, span length, girder spacing, width of traffic lane, etc. As a result, the major variables to determine the size of distribution factors were girder spacing, overhang length and span length in case of external girders. For internal adjacent girders, the determinant factors were girder spacing, overhang length, span length and width of bridge. For internal girders, the factors were girder spacing, width of bridge and span length. Then, an equation of live load distribution factors was developed through the multiple linear regression analysis on the results of parametric analysis. When the actual practice engineers design a bridge with the equation of live load distribution factors developed here, they will determine the design of member forces ensuring the appropriate safety rate more easily. Moreover, in the preliminary design, this model is expected to save much time for the repetitive design to improve the structural efficiency of PSC I-girder bridges.

• Korean Journal of Environmental Agriculture
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• v.4 no.1
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• pp.31-36
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• 1985

In order to choose a suitable soil extractant for the prediction model of heavy metal content in brown rice, four extractants-0.1 M HCl, 0.1 M $HNO_3$, 0.1 M $NH_4$-oxalate and 0.001 M 2Na-EDTA, were compared by analyzing 84 soil and 45 brown rice samples collected from paddy fields adj-acent to five old zinc-mining sites. Content of cadmium and zinc in brown rice had the highest correlation coefficient to 0.001 M 2Na-EDTA and 0.1 M HCl extractants, respectively. However, the lead content in brown rice was significantly correlated with only 0.1 M $NH_4$oxalate solution. For the simultaneous prediction of zinc, cadmium and lead in brown rice, 0.1 M $NH_4$-oxalate solution was the most effective. On the multiple analysis by using various chemical characteristics of soils, pH and calcium content of soils were effective variables for the estimation of cadmium content in brown rice, while CEC and magnesium content were more effective for the estimation of zinc content in brown rice. Furthermore, for the estimation of lead content in brown rice, factors such as pH, CEC, calcium, magnesium, potassium and organic matter content were important variables in the multiple regression equation.

• Journal of Biosystems Engineering
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• v.36 no.5
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• pp.326-333
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• 2011

The need for rapid on-site monitoring of hydroponic macronutrients has led to the use of ion-selective electrodes, because of their advantages over spectrophotometric methods, including simple methodology, direct measurement of analyte, sensitivity over a wide concentration range, and low cost. Stability and repeatability of response can be a concern when using multiple ion-selective electrodes to measure concentrations in a series of samples because accuracy might be limited by drifts in electrode potential. A computer-based measurement system could improve accuracy and precision because of both consistent control of sample preparation and easy calibration of sensors. Our goal was to investigate the applicability of a cobalt-based electrode used in conjunction with a laboratory-made automated test stand for quantitative determination of ${PO_4}^-$ in hydroponic solution. Six hydroponic solutions were prepared by diluting highly concentrated paprika hydroponicsolution to provide a concentration range of 1 to 300 ppm $PO_4$-P. A calibration curve relating electrode response to phosphate in paprika hydroponic solution titrated to pH 4 with 0.025M KHP was developed based on the Nikolskii-Eisenman equation with a coefficient of determination ($R^2$) of 0.94. The laboratory-made test stand consisting of three cobalt-based electrodes measured phosphate concentrations similar to those obtained with standard laboratory methods (a regression slope of 0.98 with $R^2$ = 0.80). However, the y intercept was relatively high, 30 ppm, probably due to the relatively large amount of variation present among multiple measurements of the same sample. Further studies on the high variation in EMFs obtained with cobalt electrodes during replicate measurements were required for P estimations comparable to those obtained with standard laboratory instruments.

• Korean Journal of Soil Science and Fertilizer
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• v.36 no.2
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• pp.57-65
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• 2003

Mapping of salinity distribution in the reclaimed lands was attempted by using the electromagnetic inductance technique. Field study was conducted to monitor ground conductivity with an electromagnetic inductance, EM 38 (Geonics), and electrical conductivity of the saturated extract, ECe of the soils, at the Daeho reclaimed land. EM values of horizontal mode, EMh, and vertical mode, EMv, mode were recorded at the interval of $2m{\times}2m$ from the ground. Soil samples were taken through the profile down to 100cm for calibration. ECe of poor drained area of Daeho, were in the range of $19.50-91.50ds\;m^{-1}$, while ECe of well-drained area ranged from $1.10-34.40ds\;m^{-1}$. Multiple regression equations for the measured EMv, EMh, and ECe were highly significant. The EMh showed higher correlation with ECe than EMv. With the multiple equation, ECgM could be calculated. Correlation between ECe and ECgM was the highest ($r=0.753^{***}$), when EMI readings were taken on the ground. The relationships were highly significant below 30 cm height of measurement, With the EM38 measurement, the salinity distribution was effectively expressed for the experimental filed in Daeho reclaimed land.

• Journal of Chest Surgery
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• v.39 no.8 s.265
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• pp.579-587
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• 2006

Background: Preoperative risk analysis for Fontan candidates is still less than optimal in that patients with apparently low risks may have poor surgical outcome; prolonged pleural drainage, protein losing enteropathy, pulmonary thromboembolism and death. We hypothesized that low pulmonary vascular compliance (PVC) is a risk factor for prolonged pleural effusion drainage after the Fontan operation. Material and Method: A retrospective review of 96 consecutive patients who underwent the Extracardiac Fontan procedures (median age: 3.9 years) was performed. Fontan risk score (FRS) was calculated from 12 categorized preoperative anatomic and physiologic variables. PVC $(mm^2/m^2{\cdot}mmHg)$ was defined as pulmonary artery index $(mm^2/m^2)$ divided by total pulmonary resistance $(W.U{\cdot}/m^2)$ and pulmonary blood flow $(L/min/m^2)$ based on the electrical circuit analogue of the pulmonary circulation. Chest tube indwelling time was log-transformed (log indwelling time, LIT) to fit normal distribution, and the relationship between preoperative predictors and LIT was analyzed by multiple linear regression. Result: Preoperative PVC, chest tube indwelling time and LIT ranged from 6 to 94.8 $mm^2/mmHg/m^2$ (median: 24.8), 3 to 268 days (median: 20 days), and 1.1 to 5.6 (mean: 2.9, standard deviation: 0.8), respectively. FRS, PVC, cardiopulmonary bypass time (CPB) and central venous pressure at postoperative 12 hours were correlated with LIT by univariable analyses. By multiple linear regression, PVC (p=0.0018) and CPB (p=0.0024) independently predicted LIT, explaining 21.7% of the variation. The regression equation was LIT=2.74-0.0158 PVC+0.00658 CPB. Conclusion: Low pulmonary vascular compliance is an important risk factor for prolonged pleural effusion drainage after the extracardiac Fontan procedure.

• Explosives and Blasting
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• v.9 no.1
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• pp.3-13
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• 1991

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.

• Tuberculosis and Respiratory Diseases
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• v.49 no.6
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• pp.752-759
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• 2000

Background : Many studies have shown that pulmonary function differs widely among race, age and geographical residency. By virtue of the improvement of nutrition and environment, the elderly population in Korea is markedly increasing and so are the ages of patients complaining respiratory symptoms. However, we do not have our own data on the pulmonary functional reserve of elderly persons in Korea. We evaluate the deterioration of pulmonary functional reserve and standardize the predictive values of pulmonary function in the elderly population. Method : Pulmonary function tests were conducted in 100 men and 100 women over the age of 65. We analyzed changes of FVC and $FEV_1$ according to age and height by linear regression. We compared our new multiple linear regression equation with other equations currently used in Korea. Results : In men, the mean age was $71.5{\pm}5.2$(mean${\pm}$SD) years and the mean height was $163.6{\pm}6.2$cm. The mean FVC was $3.42{\pm}0.49{\ell}$ and the mean $FEV_1, $2.72{\pm}v$. In women, the mean age was $72.0{\pm}5.1$ years and the mean height was $149.1{\pm}5.9$cm. The mean FVC was $2.22{\pm}0.42{\ell}$ and the mean $FEV_1$ $1.83{\pm}0.34{\ell}$. Multiple linear regression equation using age and height as an independent factors was as follows : FVC(${\ell}$)=1.857-0.0356$\times$age(year)+0.02517$\times$height(cm) (p<0.01, $R^2$=0.279), $FEV_1(${\ell}$)=1.340-0.02698$\times$age(year)+0.02021$\times$height(cm) (p<0.01, $R^2$=0.255) in men, FVC(${\ell}$) =-0.09765-0.03332$\times$age(year)+0.03164$\times$height(cm) (p<0.01, $R^2$=0.435), $FEV_1(${\ell}$)=-0.l69-0.02469$\times$age(year)+0.02539$\times$height(cm) (p<0.01, $R^2$=0.41) in women. Conclusion : We established prediction regressions for pulmonary functional tests in the elderly Korean population. We also confirmed that currently adopted equations do not exactly anticipate the expected pulmonary functional reserve in the aged person over 65 years old. We suggest that our new equations from this study should be applied to interpret the pulmonary function tests in the elderly population in Korea.

• Tuberculosis and Respiratory Diseases
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• v.64 no.6
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• pp.433-438
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• 2008

Background: Measurement of the maximum oxygen uptake in patients with chronic obstructive pulmonary disease (COPD) has been used to determine the intensity of exercise and to estimate the patient's response to treatment during pulmonary rehabilitation. However, cardiopulmonary exercise testing is not widely available in Korea. The 6-minute walk test (6MWT) is a simple method of measuring the exercise capacity of a patient. It also provides high reliability data and it reflects the fluctuation in one' s exercise capacity relatively well with using the standardized protocol. The prime objective of the present study is to develop a regression equation for estimating the peak oxygen uptake ($VO_2$) for men with moderate to very severe COPD from the results of a 6MWT. Methods: A total of 33 male patients with moderate to very severe COPD agreed to participate in this study. Pulmonary function testing, cardiopulmonary exercise testing and a 6MWT were performed on their first visits. The index of work ($6M_{work}$, 6-minute walk distance [6MWD]${\times}$body weight) was calculated for each patient. Those variables that were closely related to the peak $VO_2$ were identified through correlation analysis. With including such variables, the equation to predict the peak $VO_2$ was generated by the multiple linear regression method. Results: The peak $VO_2$ averaged $1,015{\pm}392ml/min$, and the mean 6MWD was $516{\pm}195$ meters. The $6M_{work}$ (r=.597) was better correlated to the peak $VO_2$ than the 6MWD (r=.415). The other variables highly correlated with the peak $VO_2$ were the $FEV_1$ (r=.742), DLco (r=.734) and FVC (r=.679). The derived prediction equation was $VO_2$ (ml/min)=($274.306{\times}FEV_1$)+($36.242{\times}DLco$)+($0.007{\times}6M_{work}$)-84.867. Conclusion: Under the circumstances when measurement of the peak $VO_2$ is not possible, we consider the 6MWT to be a simple alternative to measuring the peak $VO_2$. Of course, it is necessary to perform a trial on much larger scale to validate our prediction equation.