• Title, Summary, Keyword: Coefficient of Multiple Determination

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Evaluation of Sigumjang Aroma by Stepwise Multiple Regression Analysis of Gas Chromatographic Profiles

  • Choi, Ung-Kyu;Kwon, O-Jun;Lee, Eun-Jeong;Son, Dong-Hwa;Cho, Young-Je;Im, Moo-Hyeog;Chung, Yung-Gun
    • Journal of Microbiology and Biotechnology
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    • v.10 no.4
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    • pp.476-481
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    • 2000
  • A linear correlation, by the stepwise multiple regression analysis, was found between the sensory test of Sigumjang aroma and the gas chromatographic data which were transformed with logarithm. GC data is the most objective method to evaluate Sigumjang aroma. A multiple correlation coefficient and a determination coefficient of more than 0.9 were obtained at the 9th and 13th steps, respectively. At step 31, the coefficient of determination level of 0.95 was attained. The accuracy of its estimation became higher as the number of the variables entered into the regression model increased. Over 90% of the Sigumjang aroma was explained by 13 compounds indentified on GC. The contributing proportion of the peak 26 was the highest followed by peaks 57 (9.27%), 29 (7.51%), 54 (6.01%), 8 (5.99%), 49 (4.97%), and 13 (4.11%).

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Assessment of the Measurement Method of the Bone Mineral Density on Cu-Equivalent Image (구리당량 영상작성에 의한 골밀도계측방법의 평가)

  • Kim Jae-Duk
    • Imaging Science in Dentistry
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    • v.30 no.2
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    • pp.101-108
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    • 2000
  • Purpose : The effects of step numbers of copper wedge and exposure on the coefficient of determination (r²) of the conversion equation to Cu-equivalent image and on the Cu-equivalent value (mmCu) and it's coefficient of variation measured at each copper step and the mandibular premolar area were evaluated. Method: Digital image analyzing system consisted of scanner, personal computer, and a stepwedge with 10 steps of 0.03 mm copper in thickness as reference material was prepared for quantitative assessment of the bone mineral density. NIH image program was used for analyzing images. Results : The film having moderately high film density showed the discrepancy between the real thickness and the measured Cu-equivalent value of each copper step. The Cu-equivalent image was dependent on the determinational coefficient of the conversion equation than the coefficient of variance of the measured value. Conclusion : Obtaining conversion equation with high coefficient of determination and proper film exposure are supposed to be neccessary for quantitative assessment of bone density. Multiple steps in the range of the corresponding copper thickness to the bone density of the area to be measured should be prepared.

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The Development of the DEA-AR Model using Multiple Regression Analysis and Efficiency Evaluation of Regional Corporation in Korea (다중회귀분석을 이용한 DEA-AR 모형 개발 및 국내 지방공사의 효율성 평가)

  • Sim, Gwang-Sic;Kim, Jae-Yun
    • Journal of the Korean Operations Research and Management Science Society
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    • v.37 no.1
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    • pp.29-43
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    • 2012
  • We design a DEA-AR model using multiple regression analysis with new methods which limit weights. When there are multiple input and single output variables, our model can be used, and the weights of input variables use the regression coefficient and coefficient of determination. To verify the effectiveness of the new model, we evaluate the efficiency of the Regional Corporations in Korea. Accordance with statistical analysis, it proved that there is no difference between the efficiency value of the DEA-AR using AHP and our DEA-AR model. Our model can be applied to a lot of research by substituting DEA-AR model relying on AHP in the future.

A Study on Stochastic Estimation of Monthly Runoff by Multiple Regression Analysis (다중회귀분석에 의한 하천 월 유출량의 추계학적 추정에 관한 연구)

  • 김태철;정하우
    • Magazine of the Korean Society of Agricultural Engineers
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    • v.22 no.3
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    • pp.75-87
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    • 1980
  • Most hydro]ogic phenomena are the complex and organic products of multiple causations like climatic and hydro-geological factors. A certain significant correlation on the run-off in river basin would be expected and foreseen in advance, and the effect of each these causual and associated factors (independant variables; present-month rainfall, previous-month run-off, evapotranspiration and relative humidity etc.) upon present-month run-off(dependent variable) may be determined by multiple regression analysis. Functions between independant and dependant variables should be treated repeatedly until satisfactory and optimal combination of independant variables can be obtained. Reliability of the estimated function should be tested according to the result of statistical criterion such as analysis of variance, coefficient of determination and significance-test of regression coefficients before first estimated multiple regression model in historical sequence is determined. But some error between observed and estimated run-off is still there. The error arises because the model used is an inadequate description of the system and because the data constituting the record represent only a sample from a population of monthly discharge observation, so that estimates of model parameter will be subject to sampling errors. Since this error which is a deviation from multiple regression plane cannot be explained by first estimated multiple regression equation, it can be considered as a random error governed by law of chance in nature. This unexplained variance by multiple regression equation can be solved by stochastic approach, that is, random error can be stochastically simulated by multiplying random normal variate to standard error of estimate. Finally hybrid model on estimation of monthly run-off in nonhistorical sequence can be determined by combining the determistic component of multiple regression equation and the stochastic component of random errors. Monthly run-off in Naju station in Yong-San river basin is estimated by multiple regression model and hybrid model. And some comparisons between observed and estimated run-off and between multiple regression model and already-existing estimation methods such as Gajiyama formula, tank model and Thomas-Fiering model are done. The results are as follows. (1) The optimal function to estimate monthly run-off in historical sequence is multiple linear regression equation in overall-month unit, that is; Qn=0.788Pn+0.130Qn-1-0.273En-0.1 About 85% of total variance of monthly runoff can be explained by multiple linear regression equation and its coefficient of determination (R2) is 0.843. This means we can estimate monthly runoff in historical sequence highly significantly with short data of observation by above mentioned equation. (2) The optimal function to estimate monthly runoff in nonhistorical sequence is hybrid model combined with multiple linear regression equation in overall-month unit and stochastic component, that is; Qn=0. 788Pn+0. l30Qn-1-0. 273En-0. 10+Sy.t The rest 15% of unexplained variance of monthly runoff can be explained by addition of stochastic process and a bit more reliable results of statistical characteristics of monthly runoff in non-historical sequence are derived. This estimated monthly runoff in non-historical sequence shows up the extraordinary value (maximum, minimum value) which is not appeared in the observed runoff as a random component. (3) "Frequency best fit coefficient" (R2f) of multiple linear regression equation is 0.847 which is the same value as Gaijyama's one. This implies that multiple linear regression equation and Gajiyama formula are theoretically rather reasonable functions.

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Estimate of Compressive Strength for Concrete using Ultrasonics by Multiple Regression Analysis Method (초음파를 이용한 중회귀분석법에 의한 콘크리트의 압축강도추정)

  • Park, I.G.;Han, E.K.;Kim, W.K.
    • Journal of the Korean Society for Nondestructive Testing
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    • v.11 no.2
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    • pp.22-31
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    • 1991
  • Various types of ultrasonic techniques have been used for the estimation of compressive strength of concrete structures. However, conventional ultrasonic velocity method using only longitudial wave cannot be determined the compressive strength of concrete structures with accuracy. In this paper, by using the introduction of multiple parameter, e. g. velocity of shear wave, velocity of longitudinal wave, attenuation coefficient of shear wave, attenuation coefficient of longitudinal wave, combination condition, age and preservation method, multiple regression analysis method was applied to the determination of compressive strength of concrete structures. The experimental results show that velocity of shear wave can be estimated compressive strength of concrete with more accuracy compared with the velocity of longitudinal wave, accuracy of estimated error range of compressive strength of concrete structures can be enhanced within the range of ${\pm}$10% approximately.

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A Study on the Fuel Economy based on the Driving Patterns for Passenger Car in the Metropolitan Area (승용차 도심 주행패턴에 의한 연비 성능 분석)

  • 정남훈;이우택;선우명호
    • Transactions of the Korean Society of Automotive Engineers
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    • v.11 no.1
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    • pp.25-31
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    • 2003
  • There are a lot of factors influencing on the automobile fuel economy such as average speed, average acceleration, acceleration sum per kilometer, and so on. In this study, various driving data were recorded during road tests. The accumulated road test mileage in Seoul metropolitan area is around 1,300 kilometers. The data were analyzed by multivariate statistical techniques including correlation analysis, principal component analysis, and multiple linear regression analysis. The analyzed results show that the average trip time per kilometer is one of the most important factors to fuel consumption and the increase of the average speed is desirable for reducing emissions and fuel consumption.

Evaluation of Barley Bran Sauce Aroma by Multiple Regression Analysis

  • Choi, Ung-Kyu
    • Food Science and Biotechnology
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    • v.14 no.5
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    • pp.656-660
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    • 2005
  • The relationship between the gas chromatographic (GC) patterns of sauce made of barley bran and ranked order in sensory analysis was investigated by multiple regression analysis (MRA). Most of the 42 barley bran sauce samples comprised about 34 peaks, in which the content of 9, 12-octadecanoic acid methyl ester was the highest, followed by those of 2-furanmethanol and 2-furancarboxaldehyde. It is difficult to estimate the aroma quality of barley bran sauce samples on the basis of only one peak. The 34 aroma compounds of the 42 samples were analyzed by an MRA model featuring six transformations. The most precise fit was calculated from the absolute value transformed with the root square of each peak, and the multiple determination coefficient showed that 91.6% of the variation in the sensory score could be explained on the basis of GC data.

A Study on the Determination of Grain Size of Heat-treated Stainless Steel Using Digital Ultrasonic Signal Processing Techniques. (디지털 초음파 신호처리 기법을 이용한 열처리된 스테인레스 스틸의 그레인 크기 결정에 관한 연구)

  • 임내묵;이영석;김성환
    • The Journal of the Acoustical Society of Korea
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    • v.18 no.8
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    • pp.84-93
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    • 1999
  • Determination of grain size of heat-treated stainless steel based fm digital ultrasonic signal processing technique is presented. This techniques consist in evidence accumulation with multiple feature parameters, difference absolute mean value(DAMV), variance(VAR), mean frequency (MEANF), auto regressive model coefficient(ARC) and linear cepstrum coefficient(LCC). Feature parameters were extracted from ultrasonic echo signal of heat-treated metals. It was found that a few parameters might not be sufficient to exactly evaluate the grain size of heat-treated metals. The determination of grain size of heat-treated metals was carried out through the evidence accumulation procedure using the distances measured with reference parameters. A fuzzy mapping function is designed to transform the distances for the application of the evidence accumulation method. In the work presented, heat-treated stainless steel samples with various grain sizes are examined. The processed experimental results supports the feasibility of the grain size determination technique presented.

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Precision Measurement of Water Content in Soil Using Dual RF Impedance Changes (고주파의 2개 주파수 임피던스 변화를 이용한 토양내 수분함량 정밀측정)

  • 김기복;김상천;주대성;윤동진
    • Journal of Biosystems Engineering
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    • v.28 no.4
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    • pp.369-376
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    • 2003
  • This study was conducted to develop a precision measurement method of water content in soil (find sand and silty sand) using dual RF impedance changes. The electrically stable perpendicular plate capacitive sensor was fabricated and utilized to sense the water content in soil. Crystal oscillators of 5 and 20 MHz and related circuits were designed to detect the capacitance changes of a perpendicular plate capacitive sensor with soil samples at various volumetric water contents. A multiple regression model for volumetric water content having dual oscillation frequency changes at 5 and 20 MHz as independent variables resulted in coefficient of determination of 0.963 and standard error calibration of 0.030 cm$^3$/cm$^3$ for calibration and coefficient of determination of 0.966, standard error of prediction of 0.027 cm$^3$/cm$^3$ and bias of 0.001 cm$^3$/cm$^3$ for prediction.

Drying Equations of Sarcodon Aspratus (능이버섯의 건조 방정식)

  • Keum, D.H.;Ro, J.G.;Jung, T.Y.;Hong, S.R.;Park, K.M.;Kim, H.;Han, J.W.
    • Journal of Biosystems Engineering
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    • v.29 no.1
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    • pp.59-64
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    • 2004
  • This study was performed to determine drying equations of sarcodon aspratus. Drying tests for sarcodon aspratus were conducted in an experimental dryer equiped with an air conditioning unit. The drying tests were performed at three air temperatures of 30$^{\circ}C$, 40$^{\circ}C$ and 50$^{\circ}C$, and two relative humidities of 30% and 50%. Measured moisture ratio data were fitted with the selected four drying models(Page, Thompson, Lewis and simplified diffusion models) using stepwise multiple regression analysis. When the coefficients of determination and root mean square errors of moisture ratio were evaluated for four drying models, the Page model was found to fit adequately to all the drying test data with coefficient of determination of 0.9996 and RMSE of 0.00523.