• Economic and Environmental Geology
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• v.39 no.3 s.178
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• pp.255-268
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• 2006

Recent 22-year (1981-2002) meteorological data of 58 Korea Meteorological Adminstration (KMA) station were analyzed to investigate spatial and temporal variation of surface air temperature (SAT) and ground surface temperature (GST) in Korea. Based on the KMA data, multiple linear regression (MLR) models, having two regression variables of latitude and altitude, were presented to predict mean surface air temperature (MSAT) and mean ground surface temperature (MGST). Both models showed a high accuracy of prediction with $R^2$ values of 0.92 and 0.94, respectively. The prediction of MGST is particularly important in the areas of geothermal energy utilization, since it is a critical parameter of input for designing the ground source heat pump system. Thus, due to a good performance of the MGST regression model, it is expected that the model can be a useful tool for preliminary evaluation of MGST in the area of interest with no reliable data. By a simple linear regression, temporal variation of SAT was analyzed to examine long-term increase of SAT due to the global warming and the urbanization effect. All of the KMA stations except one showed an increasing trend of SAT with a range between 0.005 and $0.088^{\circ}C/yr$ and a mean of $0.043^{\circ}C/yr$. In terms of meteorological factors controlling variation of GST, the effects of solar radiation, terrestrial radiation, precipitation, and snow cover were also discussed based on quantitative and qualitative analysis of the meteorological data.

• Analytical Science and Technology
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• v.24 no.6
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• pp.544-555
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• 2011

The acute toxicity in the rainbow trout (Oncorhynchus mykiss) was analyzed and predicted using quantitative structure-activity relationships (QSAR). The aquatic toxicity, 96h $LC_{50}$ (median lethal concentration) of 275 organic pesticides, was obtained from EU-funded project DEMETRA. Prediction models were derived from 558 2D molecular descriptors, calculated in PreADMET. The linear (multiple linear regression) and nonlinear (support vector machine and artificial neural network) learning methods were optimized by taking into account the statistical parameters between the experimental and predicted p$LC_{50}$. After preprocessing, population based forward selection were used to select the best subsets of descriptors in the learning methods including 5-fold cross-validation procedure. The support vector machine model was used as the best model ($R^2_{CV}$=0.677, RMSECV=0.887, MSECV=0.674) and also correctly classified 87% for the training set according to EU regulation criteria. The MLR model could describe the structural characteristics of toxic chemicals and interaction with lipid membrane of fish. All the developed models were validated by 5 fold cross-validation and Y-scrambling test.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.260-266
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• 2009

Non-revenue water reduction(NRW) technologies are implemented to evaluate and manage leakages scientifically in water distribution systems under local governments. A development of quantitative leakage indicator by measuring minimum night flow, pressure control policy by installation of PRV(pressure reducing valve) and the establishment of leakage prevention schemes by residual life modeling of deteriorated water pipes are reviewed and studied. Estimation models of allowable leakage are developed by measuring and analyzing minimum night flow at residential and commercial area in Nonsan city, which is suggested from UK water industry and can improve an existing leakage indicator for the evaluation of non-revenue water. Also, pressure control method is applied and analyzed to Uti distribution area in Sacheon city in the operation aspect. As results, $466\;m^3/day$ of leakage can be reduced and it is expected that 113million won of annual cost can be saved. In the part of corrosion velocity and residual life assessment, non-linear prediction models of residual thickness are proposed by assessment of corrosion velocity based on exposure years, soil and water quality etc., since the deteriorated water pipe play a major role to increase leakage. It is expected that collection data and analyzing results can be applied effectively and positively to reduce non-revenue water by accumulating surveying data and verifying the results in the business field of water distribution systems under local governments.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1247-1247
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• 2001

Constituents of animal biofluids such as milk, blood and urine contain information specifically related to metabolic and health status of the ruminant animals. Some changes in composition of biofluids can be attributed to disease response of the animals. Mastitis is a major problem for the global dairy industry and causes substantial economic losses from decreasing milk production and reducing milk quality. The purpose of this study was to investigate potential of NIRS combined with multivariate analysis for cow's mastitis diagnosis based on NIR spectra of milk, blood and urine. A total of 112 bulk milk, urine and blood samples from 4 Holstein cows were analyzed. The milk samples were collected from morning milking. The urine samples were collected before morning milking and stored at -35$^{\circ}C$ until spectral analysis. The blood samples were collected before morning milking using a catheter inserted into the carotid vein. Heparin was added to blood samples to prevent coagulation. All milk samples were analyzed for somatic cell count (SCC). The SCC content in milk was used as indicator of mastitis and as quantitative parameter for respective urine and blood samples collected at same time. NIR spectra of blood and milk samples were obtained by InfraAlyzer 500 spectrophotometer, using a transflectance mode. NIR spectra of urine samples were obtained by NIR System 6500 spectrophotometer, using 1 mm sample thickness. All samples were divided into calibration set and test set. Class variable was assigned for each sample as follow: healthy (class 1) and mastitic (class 2), based on milk SCC content. SIMCA was implemented to create models of the respective classes based on NIR spectra of milk, blood or urine. For the calibration set of samples, SIMCA models (model for samples from healthy cows and model for samples from mastitic cows), correctly classified from 97.33 to 98.67% of milk samples, from 97.33 to 98.61% of urine samples and from 96.00 to 94.67% of blood samples. From samples in the test set, the percent of correctly classified samples varied from 70.27 to 89.19, depending mainly on spectral data pretreatment. The best results for all data sets were obtained when first derivative spectral data pretreatment was used. The incorrect classified samples were 5 from milk samples,5 and 4 from urine and blood samples, respectively. The analysis of changes in the loading of first PC factor for group of samples from healthy cows and group of samples from mastitic cows showed, that separation between classes was indirect and based on influence of mastitis on the milk, blood and urine components. Results from the present investigation showed that the changes that occur when a cow gets mastitis influence her milk, urine and blood spectra in a specific way. SIMCA allowed extraction of available spectral information from the milk, urine and blood spectra connected with mastitis. The obtained results could be used for development of a new method for mastitis detection.

• Journal of Applied Biological Chemistry
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• v.53 no.2
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• pp.99-104
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• 2010

The influences on antioxidant activities of the substituents ($R_1-R_4$) on benzo ring in 4-Methyl-2H-benzopyran-2-one analogues (1-23) were discussed quantitatively using three dimensional quantitative structure-activity relationships (3D-QSARs: Comparative molecular field analyses (CoMFA) and Comparative molecular similarity indice analyses (CoMSIA)) methods. The statistical qualities of CoMSIA models were better than those of CoMFA models and the CoMSIA 2 model was optimized model ($q^2$=0.700 & $r^2$=0.979). Also, the contribution ratios (%) of the optimized CoMSIA 2 model were H-bond donor field 43.5%, electrostatic field 41.8% and steric field 14.7% so that the antioxidant activity exhibited a strong correlation with H-bond donor and electrostatic factor of molecules. From the analytical results of the CoMSIA contour maps, if the positive charge favor group and H-bond donor disfavor group were placed in the $R_1-R_4$ positions on the benzo ring, it was predicted that the groups would raised the antioxidant activity.

• Journal of Korean Society of Steel Construction
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• v.20 no.3
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• pp.421-435
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• 2008

This paper presents an investigation on the ultimate behavior of a transmission tower using nonlinear analyses inconsideration of residual stress and initial imperfection. Main members, such as main post, horizontal member and diagonal member of the transmission tower were modeled using beam element. Moreover, submembers of the transmission tower were modeled using truss element. ABAQUS (2004) program was used to perform finite element analyses. Initial condition options of the ABAQUS program considering initial stress and imperfection were used in this study. Before performing the analysis of the total transmission tower, simple angle section models using beam or plate/shell element w ere investigated to verify the appropriateness of ABAQUS analysis models and options. According to the verification results, the beam element was used for nonlinear analyses of the transmission tower. From nonlinear analyses results, buckling failure was in the main member of the leg part because of ${P-{\triangle}}$ effect at that point. Also, this paper includes significant results to define real structural failure modes and quantitative values. This study should be used in the development of a reasonable and economic design method for transmission towers.

• Journal of Applied Biological Chemistry
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• v.53 no.4
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• pp.225-231
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• 2010

To understand the inhibitory activity with changing hydroxyl substituents ($R_l-R_9$) of polyhydroxy substituted 2-phenyl-l,4-benzopyrone analogues (1-25) against tyrosinase (PDB ID: oxy-form; 1WX2), molecular docking and the three dimensional quantitative structure-activity relationships (3D-QSARs: Comparative molecular field analysis (CoMFA) & Comparative molecular similarity indices analysis (CoMSIA)) were studied quantitatively. The statistically best models were CoMFA 1 and CoMSIA 1 model from the results. The optimized CoMSIA 1 model with the sensitivity of the perturbation and the prediction produced ($dq^2'/dr_{yy'}^2$=1.009 & $q^2$=0.51l) by a progressive scrambling analysis were not dependent on chance correlation. The inhibitory activities with optimized CoMSIA 1 model were dependent upon electrostatic factor (51.4%) of substrate molecules. Contour mapping the 3D-QSAR models to the active site of tyrosinase provides new insight into the interaction between tyrosinase as receptor and 2-phenyl-l,4-benzopyrone analogues as inhibitor. Therefore, the results will he able to apply to the optimization of a new potent tyrosinase inhibitors.

• The Journal of Society for e-Business Studies
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• v.23 no.1
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• pp.47-63
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• 2018

This study suggested quantitative models to calculate a royalty rate as an important input factor of the relief from royalty method which has the characteristics of income approach method and market approach method that are generally used in the valuation of intangible assets. This study built a royalty rate regression model by referring to the patent infringement damages cases based on royalties, i.e., by using the royalty rates as a dependent variable and the patent indexes of the corresponding patent right as independent variables. Then, a logistic regression model was constructed by referring to inter-partes review cases of patent rights, i.e. by using not-unpatentable results as a dependent variable and the patent indexes of the corresponding patent right as independent variables. A final royalty rate was calculated by matching the royalty rate from the royalty rate regression model with a not-unpatentable probability from the logistic regression model. The suggested royalty rate was compared with the royalty rate obtained by the traditional methods to check its reliability.

• The Korean Journal of Pesticide Science
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• v.11 no.1
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• pp.8-17
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• 2007

Three-dimensional quantitative structure-activity relationships (3D-QSARs) on the fungicidal activity against damping-off (Pythium ultimum) with N-phenylbenzenesulfonamide and N-phenyl-2-thienylsulfonamide analogues (1-34) were studied quantitatively using CoMFA (comparative molecular field analysis) and CoMSIA (comparative molecular similarity indeces analysis) methodologies. On the whole, the statistical qualities of CoMSIA models with field fit alignment (FF1-FF5) were slightly higher than that of atom based fit alignment (AF1-AF5) but, the deviations of statistical quality between two alignments in case of CoMFA models were slightly lower. The statistical results of CoMFA and CoMSIA model showed that the optimized CoMSIA model (FF1: $r_{cv.}^2\;(q^2)=0.674$ & $r_{ncv.}^2=0.964$) for damping-off is better predictability and fitness for fungicidal activities than CoMFA model (AF5: $r_{cv.}^2\;(q^2)=0.616$ & $r_{ncv.}^2=0.930$). The fungicidal activities according to the information of the CoMSIA (FF1) model were dependence upon the electrostatic and hydrophobic field of the N-phenylbenzene sulfonamide analogues. Therefore, from the results of graphical analyses on the contour maps with CoMSIA (FF3) model, it is expected that the characters of R4-substituent on the N-phenyl ring as hydrophobic and hydrogen bond acceptor will be contributed to the fungicidal activity against damping-off.

• Korean Journal of Food Science and Technology
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• v.30 no.3
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• pp.523-528
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• 1998

Response surface methodology (RSM) was used to monitor extraction characteristics of electron donating ability and organoleptic properties for ethanol extracts from Chrysanthemum petals, thereby determining optimum extraction conditions. A central composite design was applied to investigate effects of solvent per sample $(X_1)$, ethanol concentration $(X_2)$ and extraction time $(X_3)\;at\;60^{\circ}C$ on dependent variables such as electron donating ability $(Y_1)$, organoleptic color $(Y_2)$ and organoleptic aroma $(Y_3)$ of the extracts. Second-order models were employed to generate 4-dimensional response surfaces for qualitative and quantitative aspects of ethanol extracts. Coefficients of determination $(R_2)$ of the models for dependent variables were ranged from 0.8180 to 0.9696. Optimum extraction conditions for each variable were 50 mL/g, 61% and 16 hrs in electron donating ability, 88 mL/g, 21% and 16 hrs in organoleptic color, 55 mL/g, 73% and 19 hrs in organoleptic aroma, respectively. The optimum condition ranges for maximized characteristics of ethanol extracts were $65{\sim}78\;mL/g,\;90{\sim}100%\;and\;15{\sim}25\;hrs$. Predicted values at the optimum conditions were in good agreement with experimental values.