• Title/Summary/Keyword: Correlation model

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Genetic Relationship of Gestation Length with Birth and Weaning Weight in Hanwoo (Bos Taurus Coreanae)

  • Hwang, J.M.;Choi, J.G.;Kim, H.C.;Choy, Y.H.;Kim, S.;Lee, C.;Kim, J.B.
    • Asian-Australasian Journal of Animal Sciences
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    • v.21 no.5
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    • pp.633-639
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    • 2008
  • The genetic relationship of gestation length (GL) with birth and weaning weight (BW, WW) was investigated using data collected from the Hanwoo Experiment Station, National Institute of Animal Science, RDA, Republic of Korea. Analytical mixed models including birth year‐season, sex of calf, linear and quadratic covariates of age of dam (days) and linear covariate of age at weaning (days) as fixed effects were used. Corresponding restricted maximum likelihood (REML) and Bayesian estimates of variance components and heritability were obtained with two models; Model 1 included only direct genetic effect and Model 2 included direct genetic, maternal genetic and permanent environmental effect. All the genetic parameter estimates from REML were corresponding to the Bayesian estimates. Direct heritability estimates for GL, BW, and WW were 0.48, 0.33 and 0.25 by Model 1. From Model 2, direct and maternal heritability estimates were 0.38 and 0.03 for GL, 0.14 and 0.05 for BW, and 0.08 and 0.05 for WW. Genetic correlation estimates between direct and maternal effects were 0.05 for GL, 0.59 for BW, and 0.52 for WW. Estimates of direct genetic correlation between GL and BW (WW) were 0.44 (0.21). Positive genetic correlation of GL with BW and WW imply that selection for greater BW or WW would lead to prolonged gestation length.

Evaluating analytical and statistical models in order to estimate effective grouting pressure

  • Amnieh, Hassan Bakhshandeh;Masoudi, Majid;Karbala, Mohammdamin
    • Computers and Concrete
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    • v.20 no.3
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    • pp.275-282
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    • 2017
  • Grouting is an operation often carried out to consolidate and seal the rock mass in dam sites and tunnels. One of the important parameters in this operation is grouting pressure. In this paper, analytical models used to estimate pressure are investigated. To validate these models, grouting data obtained from Seymareh and Aghbolagh dams were used. Calculations showed that P-3 model from Groundy and P-25 model obtained from the results of grouting in Iran yield the most accurate predictions of the pressure and measurement errors compared to the real values in P-25 model in this dams are 12 and 14.33 Percent and in p-3 model are 12.25 and 16.66 respectively. Also, SPSS software was applied to define the optimum relation for pressure estimation. The results showed a high correlation between the pressure with the depth of the section, the amount of water take, rock quality degree and grout volume, so that the square of the multiple correlation coefficient among the parameters in this dams were 0.932 and 0.864, respectively. This indicates that regression results can be used to predict the amount of pressure. Eventually, the relationship between the parameters was obtained with the correlation coefficient equal to 0.916 based on the data from both dams generally and shows that there is a desirable correlation between the parameters. The outputs of the program led to the multiple linear regression equation of P=0.403 Depth+0.013 RQD+0.011 LU-0.109 V+0.31 that can be used in estimating the pressure.

Prediction model of hypercholesterolemia using body fat mass based on machine learning (머신러닝 기반 체지방 측정정보를 이용한 고콜레스테롤혈증 예측모델)

  • Lee, Bum Ju
    • The Journal of the Convergence on Culture Technology
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    • v.5 no.4
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    • pp.413-420
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    • 2019
  • The purpose of the present study is to develop a model for predicting hypercholesterolemia using an integrated set of body fat mass variables based on machine learning techniques, beyond the study of the association between body fat mass and hypercholesterolemia. For this study, a total of six models were created using two variable subset selection methods and machine learning algorithms based on the Korea National Health and Nutrition Examination Survey (KNHANES) data. Among the various body fat mass variables, we found that trunk fat mass was the best variable for predicting hypercholesterolemia. Furthermore, we obtained the area under the receiver operating characteristic curve value of 0.739 and the Matthews correlation coefficient value of 0.36 in the model using the correlation-based feature subset selection and naive Bayes algorithm. Our findings are expected to be used as important information in the field of disease prediction in large-scale screening and public health research.

Design of customized product recommendation model on correlation analysis when using electronic commerce (전자상거래 이용시 연관성 분석을 통한 맞춤형 상품추천 모델 설계)

  • Yang, MingFei;Park, Kiyong;Choi, Sang-Hyun
    • Journal of the Korea Convergence Society
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    • v.13 no.3
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    • pp.203-216
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    • 2022
  • In the recent business environment, purchase patterns are changing around the influence of COVID-19 and the online market. This study analyzed cluster and correlation analysis based on purchase and product information. The cluster analysis of new methods was attempted by creating customer, product, and cross-bonding clusters. The cross-bonding cluster analysis was performed based on the results of each cluster analysis. As a result of the correlation analysis, it was analyzed that more association rules were derived from a cross-bonding cluster, and the overlap rate was less. The cross-bonding cluster was found to be highly efficient. The cross-bonding cluster is the most suitable model for recommending products according to customer needs. The cross-bonding cluster model can save time and provide useful information to consumers. It is expected to bring positive effects such as increasing sales for the company.

A Study of Aggressive Driver Detection Combining Machine Learning Model and Questionnaire Approaches (기계학습 모델과 설문결과를 융합한 공격적 성향 운전자 탐색 연구)

  • Park, Kwi Woo;Park, Chansik
    • Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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    • v.7 no.3
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    • pp.361-370
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    • 2017
  • In this paper, correlation analysis was performed between questionnaire and machine learning based aggressive tendency measurements. this study is part of a aggressive driver detection using machine learning and questionnaire. To collect two types tendency from questionnaire and measurements system, we constructed experiments environments and acquired the data from 30 drivers. In experiment, the machine learning based aggressive tendency measurements system was designed using a driver behavior detection model. And the model was constructed using accelerate and brake position data and hidden markov model method through supervised learning. We performed a correlation analysis between two types tendency using Pearson method. The result was represented to high correlation. The results will be utilize for fusing questionnaire and machine learning. Furthermore, It is verified that the machine learning based aggressive tendency is unique to each driver. The aggressive tendency of driver will be utilized as measurements for advanced driver assistance system such as attention assist, driver identification and anti-theft system.

Characteristics of Raman scattering spectroscopy for $ZnS_{1-x}Te_x$ alloy semi- conductor ($ZnS_{1-x}Te_x$ 삼원 화합물 반도체의 라만 산란 특성)

    • Journal of the Korean Crystal Growth and Crystal Technology
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    • v.12 no.5
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    • pp.223-228
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    • 2002
  • We have studied the characteristics of Raman scattering spectroscopy from $_ZnS{1-x}Te_x$ alloys in the whole range of Te composition x. The Raman spectra showed two-mode behaviors for those alloys. The Raman line shape showed the changes of an asymmetry and broadening of that with Te composition x. The asymmetric broadening of the line shape could be explained with a spatial correlation model.

An Empirical Study on the Integrated Organization Abilities in Third Party Logistics Korean Company for Reduction of Export Expense (수출비용절감을 위한 3PL업체의 통합조직능력에 관한 실증연구)

  • Lee, Sang-Ok;Lee, Moon-Kyu;Bang, Hyo-Sik
    • THE INTERNATIONAL COMMERCE & LAW REVIEW
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    • v.50
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    • pp.187-212
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    • 2011
  • Third party logistics research is searching for increasing its logistics efficiency of organization. Perspective of resource-based theory, this study is to reveal the exploratory relation between integrated capabilities, organzaiton knowledge, and service performance. To develop the relational model, this study conducted a theoretical survey on Shang(2009)'s 3PL service providers research model and Synder & Cumming(1998)'s learning of organization knowledge. According to the result of correlation analysis, Integrated organization knowledge is positively correlated with service diversity advantage (correlation coefficient= .670, p-value= .000) and service quality advantage (correlation coefficient= .575, p-value= .000). The thesis argued that Korean companies try to apply integrated organization abilities and service performance for cutting their export expense.

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Reduction of Nominal Variables Using Factor Analysis Model (명목척도를 갖는 변수의 축약방법에 관한 연구)

  • 홍순욱;조근태;권철신
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 1998.10a
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    • pp.122-125
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    • 1998
  • In this article, a reduction method for nominal variables is presented and its use illustrated. Factor analysis model (FAM) generally enables us to reduce variables having interval or ratio scale based on their correlation coefficients. We developed an extensive method that makes FAM applicative to the case of nominal variables which does not give correlation coefficients, but only the degree of association. Cramer's V coefficient is a well-established measure that provides the strength of association for nominal variables with a range of [0,1]. When Cramer's V coefficient can logically substitute for correlation coefficient, FAM would be extensively used for reduction of nominal variables.

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Kernel Regression with Correlation Coefficient Weighted Distance (상관계수 가중법을 이용한 커널회귀 방법)

  • Shin, Ho-Cheol;Park, Moon-Ghu;Lee, Jae-Yong;You, Skin
    • Proceedings of the KIEE Conference
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    • 2006.10c
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    • pp.588-590
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    • 2006
  • Recently, many on-line approaches to instrument channel surveillance (drift monitoring and fault detection) have been reported worldwide. On-line monitoring (OLM) method evaluates instrument channel performance by assessing its consistency with other plant indications through parametric or non-parametric models. The heart of an OLM system is the model giving an estimate of the true process parameter value against individual measurements. This model gives process parameter estimate calculated as a function of other plant measurements which can be used to identify small sensor drifts that would require the sensor to be manually calibrated or replaced. This paper describes an improvement of auto-associative kernel regression by introducing a correlation coefficient weighting on kernel distances. The prediction performance of the developed method is compared with conventional auto-associative kernel regression.

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Correlation of aerodynamic forces on an inclined circular cylinder

  • Cheng, Shaohong;Tanaka, Hiroshi
    • Wind and Structures
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    • v.8 no.2
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    • pp.135-146
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    • 2005
  • Divergent galloping-like motion of a dry inclined cable has been observed in a limited number of experimental studies, which, due to the uncertainties in its onset conditions, has induced serious concerns in the bridge stay cable design. A series of dynamic and static model wind tunnel tests have been carried out to confirm the existence of the phenomenon and clarify its excitation mechanism. The present paper focuses on exploring the spatial flow structure around an inclined cable. The pattern of resultant aerodynamic forces acting at different longitudinal locations of the model and the spatial correlation of the forces are examined. The results lead one step closer in revealing the physical nature of the phenomenon.