• Journal of Korean Society on Water Environment
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• v.25 no.4
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• pp.580-588
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• 2009

In this study daily flow rates and delivered pollutant loads of Nakdong river basin are simulated with modified TANK model and minimum variance unbiased estimator. Based on the simulation results, flow duration curves, load duration curves, and delivery ratio duration curves have been established. Then GIS analysis is performed to obtain several hydrological geomorphic characteristics such as watershed area, stream length, watershed slope and runoff curve number. Finally, multiple regression analysis is carried out to estimate empirical equations for pollutants delivery ratio. The results show that there is positive relation between the flow rates and delivery ratios, and the proposed empirical formulas for delivery ratio can predict well river pollutant loads.

• Journal of Forest and Environmental Science
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• v.27 no.1
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• pp.47-54
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• 2011

Allometry and basal area equations were developed with various tree measurement variables for the major species; Quercus variabilis, Quercus mongolica, Pinus koraiensis and Larix leptolepis in Korea. For allometry models, the relationships between total height-DBH, crown width-DBH, height to the widest portion of the crown-total height, and height to base of crown-total height were investigated. Multiple regression methods were used to relate annual basal area growth to tree variables of initial size (DBH, total height, and crown width), relative size (relative diameter and relative height) as well as competition measures (competition index, crown class, and live crown ratio).

• Journal of Embryo Transfer
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• v.18 no.3
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• pp.215-225
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• 2003

This study was carried out to investigate the change of blood compositions by age in Hanwoo, and a total of 866 of Hanwoo, which consisted with 638 of steer and 228 of bulls, were used to measure serum concentrations. A multiple regression equation was estimated with collection age and blood composition as independent and dependent variables, respectively. Complicated regression equations for blood compositions in steer and bulls were IGF-I(cubic), calcium (linear), and IP(linear). Linear and cubic equations were fitted to testosterone in steer and creatinine in bulls, respectively. A cubic equation in steer and linear equation in bulls were fitted to HDLC. Equations of quadratic in steer and cubic in bulls were fitted to concentration of triglyceride, globulin, and A/G ratio. BUN was fitted by equations of cubic in steer and quadratic in bulls. TP and albumin were fitted by equations of quadratic in steer and linear in bulls. A cubic regression equation did not explain the change of cortisol by age in steer and bulls. A cubic regression equation did explain the change of glucose by age in steer, but not in bulls. Higher R-square values (R-SQUARE>0.1) were estimated to IGF-1, albumin, creatinine, Inorganic phosphorous(IP) and HDLC in steer, and testosterone, IGF-I, TP, albumin, glucose, creatinine, IP, and HDLC in bulls for the fitted regression equations of blood compositions. Therefore, IGF-I, albumin, creatinine, IP, and HDLC were regarded as comparatively large variation by age in steer and bulls.

• Magazine of the Korean Society of Agricultural Engineers
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• v.26 no.2
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• pp.106-124
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• 1984

Monthly streanflow of watersheds is one of the most important elements for the planning, design, and management of water resources development projects, e.g., determination of storage requirement of reservoirs and control of release-water in lowflow rivers. Modeling of longterm runoff is theoretically based on water-balance analysis for a certain time interval. The effect of the casual factors of rainfall, evaporation, and soil-moisture storage on streamflow might be explained by multiple regression analysis. Using the basic concepts of water-balance and regression analysis, it was possible to develop a generalized model called the Regionalized Regression Model for Monthly Streamflow in Korean Watersheds. Based on model verification, it is felt that the model can be reliably applied to any proposed station in Korean watersheds to estimate monthly streamflow for the planning, design, and management of water resources development projects, especially those involving irrigation. Modeling processes and properties are summarized as follows; 1. From a simplified equation of water-balance on a watershed a regression model for monthly streamflow using the variables of rainfall, pan evaporation, and previous-month streamflow was formulated. 2. The hydrologic response of a watershed was represented lumpedly, qualitatively, and deductively using the regression coefficients of the water-balance regression model. 3. Regionalization was carried out to classify 33 watersheds on the basis of similarity through cluster analysis and resulted in 4 regional groups. 4. Prediction equations for the regional coefficients were derived from the stepwise regression analysis of watershed characteristics. It was also possible to explain geographic influences on streamflow through those prediction equations. 5. A model requiring the simple input of the data for rainfall, pan evaporation, and geographic factors was developed to estimate monthly streamflow at ungaged stations. The results of evaluating the performance of the model generally satisfactory.

• Journal of Dental Rehabilitation and Applied Science
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• v.16 no.1
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• pp.61-67
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• 2000

It was the aim of present study to grope the relationship of the maxillary first molar width to the various transverse skeletal measurements in frontal headfilm, and to formulate the predictive equations of the maxillary intermolar width (U6-U6) from each of the variables. Frontal cephalograms of 17 males from 18 to 26 YO and 13 females from 17 to 25 YO who manifested balanced skeletal profiles, normal occlusion, and no history of orthodontic and prosthodontic treatment were employed as subjects. Nine transverse measurements were scrutinized with Pearson's correlation analysis, simple and stepwise multiple regression analysis in specific regards to the intermolar width of maxillary first molar. Statistical output demonstrated that there were intimate relationships within the various transverse skeletal measurements each other, and among the others, high correlation was found between facial width and maxillary first intermolar width. Regression analyses provided the reliable and clinically applicable predictive equations to set the ideal maxillary first intermolar width(U6-U6) from the given skeletal framework.

• Journal of Aerospace System Engineering
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• v.10 no.3
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• pp.9-14
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• 2016

Using a multiple regression analysis, a total of 78 low-Reynolds-number airfoils are examined in this paper to clarify the systematic relationships between the geometrical parameters of the airfoils and experimentally-determined aerodynamic coefficients. The results show that the effects of the maximum camber and the maximum thickness regarding the maximum lift and the stalling angle of attack, respectively, are major. The lower-surface flatness of the airfoil is also a crucial geometrical parameter for aerodynamic performance. It is proven here that, generally, the application of the regression equations for an assessment of the aerodynamic performance is relatively acceptable, along with an expectation that the lift-curve slope violates the normality assumption.

• The Korean Journal of Applied Statistics
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• v.26 no.5
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• pp.697-712
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• 2013

When analyzing repeated binary data, the generalized estimating equations(GEE) approach produces consistent estimates for regression parameters even if an incorrect working correlation matrix is used. However, time-varying covariates experience larger changes in coefficients than time-invariant covariates across various working correlation structures for finite samples. In addition, the GEE approach may give biased estimates under missing at random(MAR). Weighted estimating equations and multiple imputation methods have been proposed to reduce biases in parameter estimates under MAR. This article studies if the two methods produce robust estimates across various working correlation structures for longitudinal binary data with time-varying covariates under different missing mechanisms. Through simulation, we observe that time-varying covariates have greater differences in parameter estimates across different working correlation structures than time-invariant covariates. The multiple imputation method produces more robust estimates under any working correlation structure and smaller biases compared to the other two methods.

• Journal of the Korean Geotechnical Society
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• v.33 no.6
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• pp.27-36
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• 2017

Gravel compaction pile method has been widely used to improve the soft ground on the land or sea as one of the soft ground improvement technique. The ultimate bearing capacity of the ground reinforced by gravel compaction piles is affected by the soil strength, the replacement ratio of pile, construction conditions, and so on, and various prediction equations have been proposed to predict this. However, the prediction of the ultimate bearing capacity using the existing models has a very large error and variation, and it is not suitable for practical design. In this study, multiple regression analysis was performed using field loading test results to predict the ultimate bearing capacity of ground reinforced by gravel compaction pile, and the most efficient input variables are selected through evaluation of error by leave one out cross validation, and a multiple regression equation for the prediction of ultimate bearing capacity was proposed. In addition, the prediction error was evaluated by applying artificial neural network using the selected input variables, and the results were compared with those of the existing model.

• Fashion & Textile Research Journal
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• v.10 no.1
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• pp.83-91
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• 2008

This study was designed to figure out the changes in elderly women's foot size and shape by aging, to propose size specification for elderly women's shoes, and to produce regression equations using representative measurements items to estimate other measurements usually hard to get. Subjects were 118 women of 30-59 years and the 227 elderly women over 60 years. Martin's anthropometry was done on the right foot of each subject for 25 items. And 11 indirect measurement items were measured on both foot printing sole outline and picture in profile taken by digital camera. For statistical analysis on the anthropometric measurements by SPSS program, analysis of variance, post-hoc test(SNK-test), crosstabulation, multiple correlation analysis, regression analysis were performed. The results of the study are as follows. Firstly, it was found that the foot figures of elderly women over 60 years were smaller in girth and width than those of below 60 years. In addition, it was revealed that a big toe and a little toe of elderly women showed a tendency concentrating to the central axis of feet. The foot index of elderly was smaller in width and girth. Secondly, foot size distribution table of elderly group showed wider size ranges and covered smaller sizes than the below the age of 60, meaning wide variation in foot size of elderly women. Thirdly, the multiple correlation analysis showed high correlation of foot length/girth to other measurements, suggesting these two items could be used as representative items for elderly women's shoe size specification as other age groups. Regression equations were produced using foot length/girth to estimate other measurements, suggesting such items could be estimated effectively and utilized in on/off-line shoe manufacturing shop as heel to big toe length, heel to little toe length, exterior malleouls width, instep girth, ankle girth, etc. These results imply prudent features of elderly women's foot as diversity of foot shape and wide size specification range should be applied for ergonomic shoe design for them.

• Journal of the Korean Society of Hazard Mitigation
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• v.9 no.5
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• pp.125-130
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• 2009

Storage function method which considers the non-linearity of the relationship between rainfall and runoff has been frequently used to predict runoff in a basin and a flood pattern. However, it is time-consuming to estimate appropriate parameters of every basin and rainfall event, which requires the empirical parameter equation applicable in Korea. In this study, multiple regression analysis is used to develop empirical equations to estimate parameters of Storage Function method using basin characteristics. The basin area, maximum stream length, and stream slope are considered as the basin characteristics as the result of the regression analysis. Collinearity is removed and trial-and-error method is used to choose the most descriptive parameters to the dependent variables in Han River basin which is divided into 30 subbasins. The developed equations are validated using the rainfall events in MunMak gauging station and named as 'Han River equation'. The equation could provide the useful information about Storage Function method parameter to calculate runoff from a basin and predict river stage.