• Title/Summary/Keyword: Coefficient of Determination

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Studies on Development of Microplate-EIA for the Determination of Serum Progesterone (혈청 Progesterone 측정을 위한 효소면역분석법 개발에 관한 연구)

  • 김정우;이욱연
    • Korean Journal of Animal Reproduction
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    • v.17 no.4
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    • pp.347-356
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    • 1994
  • A simpled and sensitive microplate enzyme immunoassay(EIA) was developed for the determination of progesterone concentration in serum, based on progesterone monoclonal antibody as anti-progesterone, horseradish peroxidase(HRP) as enzyme-label and tetramethylbenzidine(TMB) as substrate. The assay has a sensitivity of 5 pg-120pg/well and intra- and inter-assay coefficients of variation for progesterone standard curve (1.0ng~10.0ng/ml) were ranged 2.5~9.9% and 1.7.8.0%, respectively, determination coefficient of the regressio equation of our standard curve(R2=0.990$\pm$0.007) were high, and this is the same level as that of commercial kit(Hormonost Bio-Lab, Germany, R2=0.98~0.99). The progesterone concentration of serum determined by both kits (Work & Bio-Lab) were significantly correlated (r=0.95, P<0.01) although a little higher value were resulted in our kit than that of commercial kit. It generally is these results indicated that the microplate-EIA can be cused for the determination of progesterone in serum, as well as, for the determination of the early pregnancy diagnosis.

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Comments on the regression coefficients (다중회귀에서 회귀계수 추정량의 특성)

  • Kahng, Myung-Wook
    • The Korean Journal of Applied Statistics
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    • v.34 no.4
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    • pp.589-597
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    • 2021
  • In simple and multiple regression, there is a difference in the meaning of regression coefficients, and not only are the estimates of regression coefficients different, but they also have different signs. Understanding the relative contribution of explanatory variables in a regression model is an important part of regression analysis. In a standardized regression model, the regression coefficient can be interpreted as the change in the response variable with respect to the standard deviation when the explanatory variable increases by the standard deviation in a situation where the values of the explanatory variables other than the corresponding explanatory variable are fixed. However, the size of the standardized regression coefficient is not a proper measure of the relative importance of each explanatory variable. In this paper, the estimator of the regression coefficient in multiple regression is expressed as a function of the correlation coefficient and the coefficient of determination. Furthermore, it is considered in terms of the effect of an additional explanatory variable and additional increase in the coefficient of determination. We also explore the relationship between estimates of regression coefficients and correlation coefficients in various plots. These results are specifically applied when there are two explanatory variables.

An Assessment on Cu-Equivalent Image of Digital Intraoral Radiography (디지털구내방사선사진의 구리당량화상에 대한 평가)

  • KIM JAE-DUK
    • Journal of Korean Academy of Oral and Maxillofacial Radiology
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    • v.29 no.1
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    • pp.33-42
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    • 1999
  • Geometrically standardized dental radiographs were taken. We prepared Digital Cu-Equivalent Image Analyzing System for quantitative assessment of mandible bone. Images of radiographs were digitized by means of Quick scanner and personal Mcquintosh computer. NIH image as software was used for analyzing images. A stepwedge composed of 10 steps of 0.1mm copper foil in thickness was used for reference material. This study evaluated the effects of step numbers of copper wedge adopted for calculating equation. kVp and exposure time on the coefficient of determination(r²)of the equation for conversion to Cu-equivalent image and the coefficient of variation and Cu-Eq value(mm) measured at each copper step and alveolar bone of the mandible. The results were as follows: 1. The coefficients of determination(r²) of 10 conversion equations ranged from 0.9996 to 0.9973(mean=0.9988) under 70kVp and 0.16 sec. exposure. The equation showed the highest r was Y=4.75614612-0.06300524x +0.00032367x² -0.00000060x³. 2. The value of r² became lower when the equation was calculated from the copper stepwedge including 1.0mm step. In case of including 0mm step for calculation. the value of r showed variability. 3. The coefficient of variation showed 0.11, 0.20 respectively at each copper step of 0.2, 0.1mm in thickness. Those of the other steps to 0.9 mm ranged from 0.06 to 0.09 in mean value. 4. The mean Cu-Eq value of alveolar bone was 0.14±0.02mm under optimal exposure. The values were lower than the mean under the exposures over 0.20sec. in 60kVp and over 0.16sec. in 70kVp. 5. Under the exposure condition of 60kVp 0.16sec.. the coefficient of variation showed 0.03. 0.05 respectively at each copper-step of 0.3, 0.2mm in thickness. The value of r² showed over 0.9991 from both 9 and 10 steps of copper. The Cu-Eq value and the coefficient of variation was 0.14±0.01mm and 0.07 at alveolar bone respectively. In summary. A clinical application of this system seemed to be useful for assessment of quantitative assessment of alveolar provided high coefficient of determination is obtained by the modified adoption of copper step numbers and the low coefficient of variation for the range of Cu-Equivalent value of alveolar bone from optimal kVp and exposure time for each x-ray machine.

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Nondestructive Prediction of Fatty Acid Composition in Sesame Seeds by Near Infrared Reflectance Spectroscopy

  • Kim, Kwan-Su;Park, Si-Hyung;Choung, Myoung-Gun;Kim, Sun-Lim
    • KOREAN JOURNAL OF CROP SCIENCE
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    • v.51 no.spc1
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    • pp.304-309
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    • 2006
  • Near infrared reflectance spectroscopy (NIRS) was used to develop a rapid and nondestructive method for the determination of fatty acid composition in sesame (Sesamum indicum L.) seed oil. A total of ninety-three samples of intact seeds were scanned in the reflectance mode of a scanning monochromator, and reference values for fatty acid composition were measured by gas-liquid chromatography. Calibration equations were developed using modified partial least square regression with internal cross validation (n=63). The equations obtained had low standard errors of cross-validation and moderate $R^2$ (coefficient of determination in calibration). Prediction of an external validation set (n=30) showed significant correlation between reference values and NIRS estimated values based on the SEP (standard error of prediction), $r^2$ (coefficient of determination in prediction) and the ratio of standard deviation (SD) of reference data to SEP. The models developed in this study had relatively higher values (more than 2.0) of SD/SEP(C) for oleic and linoleic acid, having good correlation between reference and NIRS estimate. The results indicated that NIRS, a nondestructive screening method could be used to rapidly determine fatty acid composition in sesame seeds in the breeding programs for high quality sesame oil.

Comparison of carbon dioxide volume mixing ratios measured by GOSAT TANSO-FTS and TCCON over two sites in East Asia

  • Hong, Hyunkee;Lee, Hanlim;Jung, Yeonjin;Kim, Wookyung;Kim, Jhoon
    • Korean Journal of Remote Sensing
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    • v.29 no.6
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    • pp.657-662
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    • 2013
  • The comparison between $CO_2$ volume mixing ratios observed by GOSAT and TCCON from September 2009 through November 2012 was performed at Tsukuba and Saga, two downwind sites in East Asia. The temporal trends of $CO_2$ values obtained from GOSAT show good agreement with those observed by TCCON at these two by the TCCON, showing a coefficient of determination ($R^2$) of 0.65. The regression slop we obtained was 0.92, showing a small bias of GOSAT $CO_2$ values compared to those observed by TCCON. However, we found the higher correlation in fall and winter than that in spring and summer. The $CO_2$ volume mixing ratios observ sites. The $CO_2$ volume mixing ratios observed by GOSAT are also in good agreement with those measured ed by GOSAT are in good agreement with those measured by the TCCON at those two sites in fall and winter, showing a coefficient of determination ($R^2$) of 0.66 where as the correlation of determination obtained between GOSAT and TCCON was only 0.27 in spring and summer.

Estimation of Key Risk Management Factors for Construction Projects Based on Kano Model (Kano 모델 기반 건설프로젝트 핵심 리스크관리 요인 도출)

  • Cho, Jin-ho;Kim, Byung-Soo
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.42 no.2
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    • pp.239-248
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    • 2022
  • Risks in construction projects are increasing remarkably due to recent changes in the construction environment. Active risk management is required to recognize risks as opportunities. The purpose of this study is to propose a risk management model of the importance determination method through comparative analysis using Kano model, Timko CSC (Customer Satisfaction Coefficient), and ASC (Average Satisfaction Coefficient). Based on previous studies, the validity of risk management factor determination is reviewed through a questionnaire modified Kano model through interviews with working-level workers using the Delphi technique. Through this, a suitable risk management model is presented by selecting key risk management factors recognized by domestic construction project practitioners. As a result of the study, the Kano model developed to verify risk management of construction projects was evaluated to be effective in verifying the risk management of practitioners. It is expected that the Kano model presented in this study will be actively used to verify the importance of risk management for construction projects.

Surface roughness prediction with a full factorial design in turning (완전요인계획에 의한 선삭가공시 표면거칠기 예측)

  • Yang, Seung-Han;Lee, Young-Moon;Bae, Byong-Jung
    • Journal of the Korean Society of Manufacturing Process Engineers
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    • v.1 no.1
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    • pp.133-140
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    • 2002
  • The object of this paper is to predict the surface roughness using the experiment equation of surface roughness, which is developed with a full factorial design in turning. $3^3$ full factorial design has been used to study main and interaction effects of main cutting parameters such as cutting speed, feed rate, and depth of cut, on surface roughness. For prediction of surface roughness, the arithmetic average (Ra) is used, and stepwise regression has been used to check the significance of all effects of cutting parameters. Using the result of these, the experimental equation of surface roughness, which consists of significant effects of cutting parameters, has been developed. The coefficient of determination of this equation is 0.9908. And the prediction ability of this equation was verified by additional experiments. The result of that, the coefficient of determination is 0.9718.

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Analysis of Working Factors for Improvement of Surface Roughness on High Speed End-Milling (엔드밀 고속 가공시 표면정도 향상을 위한 가공인자의 영향 분석)

  • 배효준;박흥식
    • Journal of the Korean Society for Precision Engineering
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    • v.21 no.6
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    • pp.52-59
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    • 2004
  • Recently the high speed end-milling processing is demanded the high-precise technique with good surface roughness and rapid time in aircraft, automobile part and molding industry. The working factors of high speed end-milling has an effect on surface roughness of cutting surface. Therefore this study was carried out to analyze the working factors to get the optimum surface roughness by design of experiment. From this study, surface roughness have an much effect according to priority on distance of cut, feed rate, revolution of spindle and depth of cut. By design of experiment, it is effectively represented shape characteristics of surface roughness in high speed end-milling. And determination($R^2$) coefficient of regression equation had a satisfactory reliability of 76.3% and regression equation of surface roughness is made by regression analysis.

Case influence diagnostics for the significance of the linear regression model

  • Bae, Whasoo;Noh, Soyoung;Kim, Choongrak
    • Communications for Statistical Applications and Methods
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    • v.24 no.2
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    • pp.155-162
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    • 2017
  • In this paper we propose influence measures for two basic goodness-of-fit statistics, the coefficient of determination $R^2$ and test statistic F in the linear regression model using the deletion method. Some useful lemmas are provided. We also express the influence measures in terms of basic building blocks such as residual, leverage, and deviation that showed them as increasing function of residuals and a decreasing function of deviation. Further, the proposed measure reduces computational burden from O(n) to O(1). As illustrative examples, we applied the proposed measures to the stackloss data sets. We verified that deletion of one or few influential observations may result in big change in $R^2$ and F-statistic.

Determination of DEM Input Parameters for Dynamic Behavior Simulation of Aggregates (골재의 동적 거동 모사를 위한 DEM 입력변수의 결정 연구)

  • Yun, Tae Young;Yoo, Pyeong Jun;Kim, Yeon Bok
    • International Journal of Highway Engineering
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    • v.16 no.1
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    • pp.21-30
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    • 2014
  • PURPOSES : Evaluation of input parameters determination procedure for dynamic analysis of aggregates in DEM. METHODS : In this research, the aggregate slump test and angularity test were performed as fundamental laboratory tests to determine input parameters of spherical particles in DEM. The heights spreads, weights of the simple tests were measured and used to calibrate rolling and static friction coefficients of particles. RESULTS : The DEM simulations with calibrated parameters showed good agreement with the laboratory test results for given dynamic condition. CONCLUSIONS : It is concluded that the employed calibration method can be applicable to determine rolling friction coefficient of DEM simulation for given dynamic conditions. However, further research is necessary to connect the result to the behavior of aggregate in packing and mixing process and to refine static friction coefficient.