• Journal of Korea Water Resources Association
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• v.37 no.12
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• pp.979-991
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• 2004

In this study, RMA2 and RMA4, the 2-D depth-averaged models, were employed to simulate the two-dimensional mixing characteristics of the pollutants in the natural streams. The velocity and depth were first calculated using RMA2, 2-D hydrodynamic model, and then the resulting flow field was inputted to RMA4, 2-D water quality model, to compute the concentration field. RMA models were verified using the velocity and concentration data measured in S-curved meandering channel. The results showed that the RMA2 model simulated well the phenomenon that the maximum velocity line is located at the Inner bank of meandering channel, and the RMA4 model was well adapted to reproduce the general mixing behavior and the separation of tracer clouds. Comparing model simulations with measured data in the field experiments, RMA2 model simulated well general flow field and tendency that the maximum velocity line skewed toward the outer bank which were found in field experiments. The simulations of RMA4 model showed that the center of the tracer cloud tends to follow the path in which the maximum velocity occurs. In this study, the dispersion coefficients are fine-tuned based on the measured coefficients calculated using field concentration data, and the results show reasonable agreement with predictive equations.

• Journal of Crop Science and Biotechnology
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• v.11 no.2
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• pp.141-150
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• 2008

The response of grain yield(GY) and milled-rice protein content(PC) to crop growth status and nitrogen(N) rates at panicle initiation stage(PIS) is critical information for prescribing topdress N rate at PIS(Npi) for target GY and PC. Three split-split-plot experiments including various N treatments and rice cultivars were conducted in Experimental Farm, Seoul National University, Korea in 2003-2005. Shoot N density(SND, g N in shoot $m^{-2}$) and canopy reflectance were measured before N application at PIS, and GY, PC, and SND were measured at harvest. Data from the first two years(2003-2004) were used for calibrating the predictive models for GY, PC, and SND accumulated from PIS to harvest using SND at PIS and Npi by multiple stepwise regression. After that the calibrated models were used for calculating N requirement at PIS for each of nine plots based on the target PC of 6.8% and the values of SND at PIS that was estimated by canopy reflectance method in the 2005 experiment. The result showed that SND at PIS in combination with Npi were successful to predict GY, PC, and SND from PIS to harvest in the calibration dataset with the coefficients of determination ($R^2$) of 0.87, 0.73, and 0.82 and the relative errors in prediction(REP, %) of 5.5, 4.3, and 21.1%, respectively. In general, the calibrated model equations showed a little lower performance in calculating GY, PC, and SND in the validation dataset(data from 2005) but REP ranging from 3.3% for PC and 13.9% for SND accumulated from PIS to harvest was acceptable. Nitrogen rate prescription treatment(PRT) for the target PC of 6.8% reduced the coefficient of variation in PC from 4.6% in the fixed rate treatment(FRT, 3.6g N $m^{-2}$) to 2.4% in PRT and the average PC of PRT was 6.78%, being very close to the target PC of 6.8%. In addition, PRT increased GY by 42.1 $gm^{-2}$ while Npi increased by 0.63 $gm^{-2}$ compared to the FRT, resulting in high agronomic N-use efficiency of 68.8 kg grain from additional kg N. The high agronomic N-use efficiency might have resulted from the higher response of grain yield to the applied N in the prescribed N rate treatment because N rate was prescribed based on the crop growth and N status of each plot.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1620-1620
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• 2001

Forages, both grazed and conserved, provide the basis of ruminant production systems throughout the world. More than 90 per cent of the feed energy consumed by herbivorous animals world - wide were provided by forages. With such world - wide dependence on forages, the economic and nutritional necessity of been able to characterize them in a meaningful way is vital. The characterization of forages for productive animals is becoming important for several reasons. Relative to conventional laboratory procedures, Near Infrared Reflectance Spectroscopy (NIRS) offers advantages of simplicity, speed, reduced chemical waste, and more cost-effective prediction of product functionality. NIR spectroscopy represents a radical departure from conventional analytical methods, in that entire sample of forage is characterized in terms of its absorption properties in the near infrared region, rather than separate subsamples being treated with various chemicals to isolate specific components. This forces the analyst to abandon his/her traditional narrow focus on the sample (one analyte at a time) and to take a broader view of the relationship between components within the sample and between the sample and the population from which it comes. forage is usually analysed by NIRS in dry and ground presentation. Initial success of NIRS analysis of coarse forages suggest a need to better understand the potential for analysis of minimally processed samples. Preparation costs and possible compositional alterations could be reduced by samples presented to the instrument in undried and unground conditions. NIRS has gained widespread acceptance for the analysis of forage quality constituents on dry material, however little attention has been given to the use of NIRS for chemical determinations on undried and unground forages. Relatively few works reported the use of NIRS to determine quality parameters on undried materials, most of them on both grass and corn silage. Only two works have been found on the determination of quality parameters on fresh forages. The objectives of this paper were (1) to evaluate the use of NIRS for determination of nitrogen and moisture on undried and unground forage samples and (2) to explore two mathematical treatments and two NIR regions to predict chemical parameters on fresh forage. Four hundred forage samples (n: 400) were analysed in a NIRS 6500 instrument (NIR Systems, PA, USA) in reflectance mode. Two mathematical treatments were applied: 1,4,4,1 and 2,5,5,2. Predictive equations were developed using modified partial least squares (MPLS) with internal cross - validation. Coefficient of determination in calibration (${R^2}_{CAL}$) and standard error in cross-validation (SECV) for moisture were 0.92 (12.4) and 0.92 (12.4) for 1,4,4,1 and 2,5,5,2 respectively, on g $kg^{-1}$ dry weight. For crude protein NIRS calibration statistics yield a (${R^2}_{CAL}$) and (SECV) of 0.85 (19.8) and 0.85 (19.6) for 1,4,4,1 and 2,5,5,2 respectively, on a dry weight. It was concluded that NIRS is a suitable method to predict moisture and nitrogen on fresh forage without samples preparation.

• Journal of Korean Society of Environmental Engineers
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• v.39 no.10
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• pp.568-574
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• 2017

The purpose of this study was to optimize experimental conditions (time ($X_1$) (ranging of 26.36 - 93.64 min), concentration of sulfuric acid ($X_2$) (ranging of 0-2.5%) and temperature ($X_3$) (ranging of $136.4-203.6^{\circ}C$) for an organosolv pretreatment process to extract lignin from waste wood. The resulting quadratic model equation using RSM (response surface methodology) represented y (lignin yield) = $-79.89+0.91X_1+9.8X_2-2.54{\times}10^{-3}X_1{^2}-2.11X_2{^2}$. The $R^2$ (coefficient of determination) value of 0.8531 for a model indicates this model has statistically significant predictors at the 10% levels. The predictive results optimized by quadratic model produced a lignin yield of 12.46 g/100 g of dry wood under conditions of $178.2^{\circ}C$ and 2.32% $H_2SO_4$. The lignin yield was more affected by the acid catalyst concentrations than the reaction temperature, but the reaction time was not an influential factor for improving lignin extraction from waste wood in this organosolv pretreatment. According to ANOVA (analysis of variance), the significance probability (p-value) of model was smaller than 0.001 and simulation of obtained model equations showed a good reproducibility based on actual organosolv tests under optimal conditions.

• Korean Journal of Applied Biomechanics
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• v.18 no.4
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• pp.109-114
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• 2008

The purpose of this study was to estimate the energy expenditure simply and practically during physical activities. The physical activity is quantified by the integration of the accelerometer signals obtained from the triaxial accelerometer attached at the waist level of the human body. To find a relationship between energy expenditure and accelerometer data, 6 male and 5 female subjects walked and ran on the treadmill with speeds of 1.5, 3.0, 4.5, 6.0, 6.5, 7.0, and 8.5 km/hr. Each subject performed walking at the speed lower than 6.0 km/hr and running at the speed higher than 6.5 km/hr. Actual energy expenditure was determined by a continuous direct gas analyzer. Two predictive equations of walking and running mode for energy expenditure which includes gender, body mass index(BMI) and data from accelerometer were developed using multiple regression analysis. The correlation coefficients and coefficients of determination between the estimated and measured energy expenditure were R=0.936, R2=0.876 and R=0.881, R2=0.776 in walking and running mode, respectively. For further study, experiments on a larger scale of test subjects are essential for acquiring more reliable results.

• Journal of Korea Soil Environment Society
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• v.1 no.2
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• pp.91-101
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• 1996

In recent years, phytoremediation, the use of plants to detoxify hydrocarbons, has been a promising new area of research, particularly in situ cleanup of large volumes of slightly contaminated soils. There is increasing need for a mathematical model that can be used as a predictive tool prior to actual field implementation of such a relatively new technique. Although a number of models exist for solute-plant interaction in the vegetated zone of soil, most of them have focused on ionic nutrients and some metals. In this study, we developed a mathematical model for simulation of bioremediation of hydrocarbons in soil, associated with plant root systems. The proposed model includes root interactions with soil-water and hydrocarbons in time and space, as well as advective and dispersive transport in unsaturated soil. The developed model considers gas phase diffusion and liquid-gas mass exchanges. For simulation of temporal and spatial changes in root behavior on soil-water and with hydrocarbons, time-specific distribution of root quantity through soil was incorporated into the simulation model. Hydrocarbon absorption and subsequent uptake into roots with water were simulated with empirical equations. In addition, microbial activity in the rhizosphere, a zone of unique interaction between roots and soil microorganisms, was modeled using a biofilm theory. This mathematical model for understanding and predicting fate and transport of compound in plant-aided remediation will assist effective application of plant-aided remediation to field contamination.

• Asian-Australasian Journal of Animal Sciences
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• v.31 no.8
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• pp.1238-1243
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• 2018

Objective: Two experiments were conducted to determine the effects of feeding level on nutrient digestibility and enteric methane ($CH_4$) emissions in growing goats and Sika deer. Methods: Three growing male goats (initial body weight [BW] of $22.4{\pm}0.9kg$) and three growing male deer (initial BW of $20.2{\pm}4.8kg$) were each allotted to a respiration-metabolism chamber for an adaptation period of 7 d and a data collection period of 3 d. An experimental diet was offered to each animal at one of three feeding levels (1.5%, 2.0%, and 2.5% of BW) in a $3{\times}3$ Latin square design. The chambers were used for measuring enteric $CH_4$ emission. Results: Nutrient digestibility decreased linearly in goats as feeding level increased, whereas Sika deer digestibility was not affected by feeding level. The enteric production of $CH_4$ expressed as g/kg dry matter intake (DMI), g/kg organic matter intake, and % of gross energy intake decreased linearly with increased feeding level in goats; however, that of Sika deer was not affected by feeding level. Six equations were estimated for predicting the enteric $CH_4$ emission from goats and Sika deer. For goat, equation 1 was found to be of the highest accuracy: $CH_4(g/d)=6.2({\pm}14.1)+10.2({\pm}7.01){\times}DMI(kg/d)+0.0048({\pm}0.0275){\times}dry$ matter digestibility (DMD, g/kg)-0.0070 (${\pm}0.0187$)${\times}$neutral detergent fiber digestibility (NDFD; g/kg). For Sika deer, equation 4 was found to be of the highest accuracy: $CH_4(g/d)=-13.0({\pm}30.8)+29.4({\pm}3.93){\times}DMI(kg/d)+0.046(0.094){\times}DMD(g/kg)-0.0363({\pm}0.0636){\times}NDFD(g/kg)$. Conclusion: Increasing the feeding level increased $CH_4$ production in both goats and Sika deer, and predictive models of enteric $CH_4$ production by goats and Sika deer were estimated.

• Animal Bioscience
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• v.37 no.8
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• pp.1474-1482
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• 2024

Objective: The experiment aimed to determine the standardized ileal digestibility (SID) of crude protein (CP) and amino acids (AA) in 10 brown rice samples fed to pigs, and to construct predictive models for SID of CP and AA based on the physical characteristics and chemical composition of brown rice. Methods: Twenty-two cannulated pigs (initial body weight: 42.0±1.2 kg) were assigned to a replicated 11×3 incomplete Latin square design, including an N-free diet and 10 brown rice diets. Each period included 5 d adaptation and 2 d ileal digesta collection. Chromic oxide was added at 0.3% to all the diets as an indigestible marker for calculating the ileal CP and AA digestibility. Results: The coefficients of variation of all detected indices for physical characteristics and chemical composition, except for bulk weight, dry matter (DM) and gross energy, in 10 brown rice samples were greater than 10%. The SID of CP, lysine (Lys), methionine, threonine (Thr), and tryptophan (Trp) in brown rice was 77.2% (62.6% to 85.5%), 87.5% (80.3% to 94.3%), 89.2% (78.9% to 98.9%), 55.4% (46.1% to 67.6%) and 92.5% (86.3% to 96.3%), respectively. The best prediction equations for the SID of CP, Lys, Thr, and Trp were as following, SID_CP = -664.181+8.484×DM (R² = 0.40), SID_Lys = 53.126+6.031×ether extract (EE)+0.893×thousand-kernel volume (R² = 0.66), SID_Thr = 39.916+7.843×EE (R² = 0.41), and SID_Trp = -361.588+4.891×DM+0.387×total starch (R² = 0.85). Conclusion: Overall, a great variation exists among 10 sources of brown rice, and the thousand-grain volume, DM, EE, and total starch can be used as the key predictors for SID of CP and AA.

• Journal of the Korea Concrete Institute
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• v.19 no.1
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• pp.121-130
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• 2007

To investigate the enhancement in strength and deformation capacities of concrete confined by FRP composites, tests under axial loads were carried out on three groups of thirty six short columns in circular section with diverse GFRP confining reinforcement. The major test variables considered include fiber content or orientation, wrap or tube type by varying the end loading condition, and continuous or discontinuous confinement depending on the presence of vortical spices between its two halves. The circumferential FRP strains at failure for different types of confinements were also investigated with emphasis. Various analytical models capable of predicting the ultimate strength and strain of the confined concrete were examined by comparing to observed results. Tests results showed that FRP wraps or tubes provide the substantial increase in strength and deformation, while partial wraps comprising the vertical discontinuities fail in an explosive manner with less increase in strength, particularly in deformation. A bilinear stress-strain response was observed throughout all tests with some variations of strain hardening. The failure hoop strains measured on the FRP surface were less than those obtained from the tensile coupons in all tests with a high degree of variation. In overall, existing predictive equations overestimated ultimate strengths and strains observed in present tests, with a much larger scatter related to the latter. For more accuracy, two simple design- oriented equations correlated with present tests are proposed. The strength equation was derived using the Mohr-Coulomb failure criterion, whereas the strain equation was based on entirely fitting of test data including the unconfined concrete strength as one of governing factors.

• 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.