• Journal of the Korean Data and Information Science Society
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• v.24 no.4
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• pp.877-883
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• 2013

The quadratic inference functions (QIF) method proposed by Qu et al. (2000) and the generalized method of moments (GMM) for marginal regression analysis of longitudinal data with time-dependent covariates proposed by Lai and Small (2007) both are the methods based on generalized method of moment (GMM) introduced by Hansen (1982) and both use generalized estimating equations (GEE). Lai and Small (2007) divided time-dependent covariates into three types such as: Type I, Type II and Type III. In this paper, we compared these methods in the case of Type II and Type III in which full covariates conditional mean assumption (FCCM) is violated and interested in whether they can improve the results of GEE with independence working correlation. We show that in the marginal regression model with Type II time-dependent covariates, GMM Type II of Lai and Small (2007) provides more ecient result than QIF and for the Type III time-dependent covariates, QIF with independence working correlation and GMM Type III methods provide the same results. Our simulation study showed the same results.

• Korean Journal of Soil Science and Fertilizer
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• v.50 no.5
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• pp.409-421
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• 2017

Recently Unmanned Aerial Vehicle (UAV) technology offers new opportunities for assessing crop growth condition using UAV imagery. The objective of this study was to select optimal vegetation indices and regression model for estimating of rice growth using UAV images. This study was conducted using a fixed-wing UAV (Model : Ebee) with Cannon S110 and Cannon IXUS camera during farming season in 2016 on the experiment field of National Institute of Crop Science. Before heading stage of rice, there were strong relationships between rice growth parameters (plant height, dry weight and LAI (Leaf Area Index)) and NDVI (Normalized Difference Vegetation Index) using natural exponential function ($R{\geq}0.97$). After heading stage, there were strong relationships between rice dry weight and NDVI, gNDVI (green NDVI), RVI (Ratio Vegetation Index), CI-G (Chlorophyll Index-Green) using quadratic function ($R{\leq}-0.98$). There were no apparent relationships between rice growth parameters and vegetation indices using only Red-Green-Blue band images.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.2
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• pp.40-46
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• 2015

The modular assembly system can make it possible for the variety of products to be assembled in a short lead time. In this system, necessary components are assembled to optional components tailor to customers' orders. Budget for inventory investments composed of inventory and purchasing costs are practically limited and the purchasing cost is often paid when an order is arrived. Service cost is assumed to be proportional to service level and it is included in budget constraint. We develop a heuristic procedure to find a good solution for a continuous review inventory system of the modular assembly system with a budget constraint. A regression analysis using a quadratic function based on the exponential function is applied to the cumulative density function of a normal distribution. With the regression result, an efficient heuristics is proposed by using an approximation for some complex functions that are composed of exponential functions only. A simple problem is introduced to illustrate the proposed heuristics.

• Environmental Engineering Research
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• v.24 no.3
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• pp.484-494
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• 2019

This paper presents a preliminary investigation of the optimum nutrients combination required for bioremediation of spent-engine oil contaminated soil using Box-Behnken-Design. Three levels of cow-manure, poultry-manure and inorganic nitrogen-phosphorus-potassium (NPK) fertilizer were used as independent biostimulants variables; while reduction in total petroleum hydrocarbon (TPH) and total soil porosity (TSP) response as dependent variables were monitored under 6-week incubation. Ex-situ data generated in assessing the degree of biodegradation in the soil were used to develop second-order quadratic regression models for both TPH and TSP. The two models were found to be highly significant and good predictors of the response fate of TPH-removal and TSP-improvement, as indicated by their coefficients of determination: $R^2=0.9982$ and $R^2=1.000$ at $p{\leq}0.05$, respectively. Validation of the models showed that there was no significant difference between the predicted and observed values of TPH-removal and TSP-improvement. Using numerical technique, the optimum values of the biostimulants required to achieve a predicted maximum TPH-removal and TSP-improvement of 67.20 and 53.42%-dry-weight per kg of the contaminated soil were as follows: cow-manure - 125.0 g, poultry-manure - 100.0 g and NPK-fertilizer - 10.5 g. The observed values at this optimum point were 66.92 and 52.65%-dry-weight as TPH-removal and TSP-improvement, respectively.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.479-487
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• 2013

State Highway Agencies (SHAs) have started utilizing cost-plus-time bidding (A+B bidding) since Federal Highway Agency (FHWA) declared it operational on May 4, 1995. Although this technique has successfully accelerated many projects by incorporating construction time in the bidding competition, a framework to illustrate the interactions of incentive/disincentive (I/D) rates on the competitiveness of contractors participating in the bid competition is yet to be developed. In a previous research, authors indicated that for each bid competition there is an efficient cap for I/D rates which are dictated by the capabilities of contractors in project acceleration. However, the results of previous study were based on the assumption that there is a statistically significant relationship between cost and time. In this study, the entire cost-plus-time projects implemented by the Oklahoma Department of Transportation (ODOT) were investigated. Then the significance of relationship between cost and time were analyzed for each contractor utilizing Analysis of Variance (ANOVA) technique, and the price-time function of each contractor was determined by regression analysis. The results of the analysis indicate that there is a significant relationship between cost and time for the majority of contractors. However, a quadratic relationship is not always significant and for some contractors a linear price-time relationship is significant. The results of this project can be used not only by ODOT to optimize the incentive/disincentive rates but also by contractors to determine the most competitive strategies of other bid participants.

• Journal of Medicine and Life Science
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• v.20 no.3
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• pp.107-114
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• 2023

Epidemiological control of coronavirus disease 2019 (COVID-19) is needed to estimate the infection period of confirmed cases and identify potential cases. The present study, targeting confirmed cases for which the time of COVID-19 symptom onset was disclosed, aimed to investigate the relationship between intervals (day) from symptom onset to testing the cycle threshold (CT) values of real-time reverse transcription-polymerase chain reaction. Of the COVID-19 confirmed cases, those for which the date of suspected symptom onset in the epidemiological investigation was specifically disclosed were included in this study. Interval was defined as the number of days from symptom onset (as disclosed by the patient) to specimen collection for testing. A locally weighted regression smoothing (LOWESS) curve was applied, with intervals as explanatory variables and CT values (CTR for RdRp gene and CTE for E gene) as outcome variables. After finding its non-linear relationship, a polynomial regression model was applied to estimate the 95% confidence interval values of CTR and CTE by interval. The application of LOWESS in 331 patients identified a U-shaped curve relationship between the CTR and CTE values according to the number of interval days, and both CTR and CTE satisfied the quadratic model for interval days. Active application of these results to epidemiological investigations would minimize the chance of failing to identify individuals who are in contact with COVID-19 confirmed cases, thereby reducing the potential transmission of the virus to local communities.

• Korean Journal of Radiology
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• v.22 no.7
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• pp.1194-1202
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• 2021

Objective: To investigate the age-dependent changes in regional cerebral blood flow (CBF) in healthy adults by fitting mathematical models to imaging data. Materials and Methods: In this prospective study, 90 healthy adults underwent pseudo-continuous arterial spin labeling imaging of the brain. Regional CBF values were extracted from the arterial spin labeling images of each subject. Multivariable regression with the Akaike information criterion, link test, and F test (Ramsey's regression equation specification error test) was performed for 7 models in every brain region to determine the best mathematical model for fitting the relationship between CBF and age. Results: Of all 87 brain regions, 68 brain regions were best fitted by cubic models, 9 brain regions were best fitted by quadratic models, and 10 brain regions were best fitted by linear models. In most brain regions (global gray matter and the other 65 brain regions), CBF decreased nonlinearly with aging, and the rate of CBF reduction decreased with aging, gradually approaching 0 after approximately 60. CBF in some regions of the frontal, parietal, and occipital lobes increased nonlinearly with aging before age 30, approximately, and decreased nonlinearly with aging for the rest of life. Conclusion: In adults, the age-related perfusion patterns in most brain regions were best fitted by the cubic models, and age-dependent CBF changes were nonlinear.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.42 no.1
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• pp.22-32
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• 1997

This experiment was conducted to obtain information for the cultivation of Korean valerian(Valeriana lauriei var. dasycarpa Hara) which will be useful for medicinal and aromatic resources. The effect of different temperature conditions, light intensities and soil water conditions on growth, yield and component of essential oil of V. fauriei were measured at the Dankook University, Cheonan, and a study on the shading treatment was at Umsung, Chungchongbukdo, and Jinbu, Kangwondo, in 1995. V. laudei was planted at five different temperature conditions, 10, 15, 20, 25 and 3$0^{\circ}C$, eight light intensity conditions, 1, 000, 2, 500, 5, 000, 20, 000, 30, 000, 40, 000, 50, 000 and 60, 000lux, six soil water contents, 30, 45, 55, 70, 80 and 90％ of the saturated soil, during growth stage. Shading treatment was three conditions, 0, 25 and 50％, during the daytime in field conditions. Photosynthesis had a highly significant relationship with temperature conditions in a quadratic regression model, from which the temperature for the plant growth was estimated to be 17.7$^{\circ}C$. A highly significant quadratic regression was noted between temperature and leaf width or root weight of V. fauriei. It was estimated from the regression equation that the optimum temperature for root growth was 20.3$^{\circ}C$. The content of essential oil and extract rate of root was the highest in the 15~2$0^{\circ}C$. Photosynthesis also was significantly affected by light intensity in a quadratic regression model, from which the optimum light intensity for the growth was estimated to be 40, 000lux. Root yield was more produced in Jinbu than that of in Umsung. The root yield was increased by the shading treatment in Umsung, whereas it was decreased by the shading treatment in Jinbu. The content of essential oil was not affected by the shading treatment of plants during the cultivation, while the compositions of components of essential oil were related to the growing locations. As soil water content was higher, the growth and content of root extract were increased. The optimum soil moisture for the growth of V. fauriei was 80~90％ of the saturated soil. In summary, the results indicated that the growth, yield and component of essential oil in V. fauriei were affected by environmental factors as well as soil moisture.

• Journal of Korea Water Resources Association
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• v.51 no.3
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• pp.263-272
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• 2018

For the design of hydraulic structures, the design flood discharge corresponding to a specific frequency is generally used by using the design storm calculated according to the rainfall-runoff relationship. In the past, empirical equations such as rational equations were used to calculate the peak flow rate. However, as the duration of rainfall is prolonged, the outflow patterns are different from the actual events, so the accuracy of the temporal distribution of the probability rainfall becomes important. In the present work, Huff's quartile method is used for the temporal distribution of rainfall, and the third quartile is generally used. The regression equation for Huff's quadratic curve applies a sixth order polynomial equation because of its high accuracy throughout the duration of rainfall. However, in statistical modeling, the regression equation needs to be concise in accordance with the principle of simplicity, and it is necessary to determine the regression coefficient based on the statistical significance level. Therefore, in this study, the statistical significance test for regression equation for temporal distribution of the Huff's quartile method, which is used as the temporal distribution method of design rainfall, is conducted for 69 rainfall observation stations under the jurisdiction of the Korea Meteorological Administration. It is statistically significant that the regression equation of the Huff's quartile method can be considered only up to the 4th order polynomial equation, as the regression coefficient is significant in most of the 69 rainfall observation stations.

• Journal of Korean Society for Quality Management
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• v.32 no.3
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• pp.109-125
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• 2004

This paper deals with an optimal process control problem in production of hull structural steel plate with high defective rate. The main quality characteristic(dependent variable) is the internal quality(defect) of plates and is dependent on process parameters(independent variables). The dependent variable(quality characteristics) has three categorical ordinal data and there are 35 independent variables(29 continuous variables and 6 categorical variables). In this paper, we determine the main factors and to develop the mathematical model between internal quality predicted probabilities and the main factors. Secondly, we find out the optimal process condition of main factors through analysis of variance(ANOVA) using simulation. We consider three models to obtain the main factors and the optimal process condition: linear, quadratic, error models.