• Journal of Nutrition and Health
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• v.22 no.1
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• pp.23-31
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• 1989

The purpose of this study was to evaluate the validity of various dietary methods. Dietary intake of 24 patients on regular diet was investigated by three methods. One method was a precise weighing method, the others were 24-hour dietary recall method and convenient dietary questionnaries. The results obtained are summarized as followes ; 1) There were no significant differences in mean nutrient intake of subjects among three dietary survey methods. 2) The validity coefficient between the precise weighing method and 24-hour recall method, ranging from 0.26(fat) to 0.59(carbohydrate) showed significant correlation for carbohydrate, vitamin A, thiamin, riboflavin and ascorbic and intakes. 3) The validity coefficient between precise weighting method and covenient dietary questionnaires, ranging from 0.14(fat) to 0.80(vitamin A), showed a significant correlation for most nutrients. 4) Female showed higher correlation between the precise weighing method and 24-hour recall method than male subjects for most nutrients. However, there was no significant sexual difference of correlation between weighing method and convenient method. 5) The correlation coefficient between the precise weighing method and the other two methods by age group showed younger sujbects have a higher significant correlation than older subjects for most nutrients.

• The Bulletin of The Korean Astronomical Society
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• v.39 no.2
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• pp.107.2-107.2
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• 2014

The study on non-linear correlation between auxiliary channels in LIGO data has been performed by using mutual information coefficient, generating a correlation map.

• International Journal of Naval Architecture and Ocean Engineering
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• v.10 no.3
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• pp.413-420
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• 2018

This paper documents the result of a preliminary analysis on the influence of hull-ice friction coefficient on model resistance and power predictions and their correlation to full-scale measurements. The study is based on previous model-scale/full-scale correlations performed on the National Research Council - Ocean, Coastal, and River Engineering Research Center's (NRC/OCRE-RC) model test data. There are two objectives for the current study: (1) to validate NRC/OCRE-RC's modeling standards in regarding to its practice of specifying a CFC (Correlation Friction Coefficient) of 0.05 for all its ship models; and (2) to develop a correction methodology for its resistance and propulsion predictions when the model is prepared with an ice friction coefficient slightly deviated from the CFC of 0.05. The mean CFC of 0.056 and 0.050 for perfect correlation as computed from the resistance and power analysis, respectively, have justified NRC/OCRE-RC's selection of 0.05 for the CFC of all its models. Furthermore, a procedure for minor friction corrections is developed.

• Journal of the Korean Statistical Society
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• v.29 no.3
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• pp.285-294
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• 2000

In analyzing bivariate date the sample correlation coefficient is often used, and it is quite sensitive to one or few isolated cases. In this article we derive a formula for the effect of $textsc{k}$ observations on the samples correlation coefficient by the deletion method. To give a reference value for the isolated cases the asymptotic distribution fo the formula is derived. Also, we give some interpretations on several types of isolated cases and an example based on a real data set.

• Journal of the Korean Data and Information Science Society
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• v.22 no.5
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• pp.1007-1016
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• 2011

This article deals with the problem of testing for the correlation coefficient in the bivariate normal distribution. We propose Bayesian hypothesis testing procedures for the bivariate normal correlation coefficient under the noninformative prior. The noninformative priors are usually improper which yields a calibration problem that makes the Bayes factor to be defined up to a multiplicative constant. So we propose the default Bayesian hypothesis testing procedures based on the fractional Bayes factor and the intrinsic Bayes factors under the reference priors. A simulation study and an example are provided.

• Journal of Information Processing Systems
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• v.14 no.5
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• pp.1215-1224
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• 2018

Interval-valued neutrosophic hesitant fuzzy set (IVNHFS) is an extension of neutrosophic set (NS) and hesitant fuzzy set (HFS), each element of which has truth membership hesitant function, indeterminacy membership hesitant function and falsity membership hesitant function and the values of these functions lie in several possible closed intervals in the real unit interval [0,1]. In contrast with NS and HFS, IVNHFS can be more flexibly used to deal with uncertain, incomplete, indeterminate, inconsistent and hesitant information. In this study, I propose the novel correlation coefficient of IVNHFSs and my paper discusses its properties. Then, based on the novel correlation coefficient, I develop an approach to deal with multi-attribute decision-making problems within the framework of IVNHFS. In the end, a practical example is used to show that the approach is reasonable and effective in dealing with decision-making problems.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.32 no.5
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• pp.374-381
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• 2008

The correlation coefficient method, which was proposed by our research group, is applied to digital particle holography to locate the focal plane of particles. It uses the fact that the correlation coefficient is maximum at the focal plane. The factors influencing this method are discussed with a numerical simulation of holograms. For real holograms, the Wiener filter was proposed to process both recorded holograms and reconstructed images. The application results using the dot array target showed that the Wiener filter is a very effective tool for processing holography-related images. The effects of the dot size and the object distance on the errors in the determination of the focal plane by the correlation coefficient method were investigated by using the calibration target.

• IE interfaces
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• v.14 no.1
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• pp.79-83
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• 2001

In this paper, we propose a simple method to reduce categorical variables into smaller, but significant numbers, and also demonstrate how the proposed method can be applied to the problem of reduction that empirical research often faces in the course of data processing. For the purpose, we introduce a concept of pseudo-correlation coefficient to make it possible to use factor analysis (FA) as a tool for reducing variables. The main idea of the concept is to deal with the measures of association of categorical variables in the sense of the concept of Pearson's correlation coefficient in order to meet the input requirement of FA. Upon examination of existing measures that could play as pseudo-correlation coefficients, Cramer's V coefficient is selected for the best result among them. To show the detailed procedure of the proposed method, a specific demonstration with the data from 329 R&D projects conducted in 18 private laboratories in electric and electronics industry is presented.

• Journal of Korean Society for Quality Management
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• v.26 no.1
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• pp.108-125
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• 1998

The EWMA(Exponentially Weighted Moving Average) has recently received a great deal of attention in the quality control literature as a process monitoring tool on the shop floor of manufacturing industires, since it is easy to plot, to interpret, and its control limits are easy to obtain. Most a, pp.ications of the EWMA for process monitoring have concentrated on the problem of detecting shifts of a process mean and a process standard deviation with ARL(Average Run Length) properties. But there may be the necessity of controlling linearity on product quality such as the correlation coefficient to the process operator. Control managers may want to protect the increase of a process correlation coefficient value, such as 0, between two variables of interest. However, there are few studies concerned on this part. Therefore, we propose EWMA models for a process correlation coefficient using two transformed statistics, T-statistic and (Fisher's) Z-statistic. We also present some results of simulation by SAS/IML and compare two models.

• The Korean Journal of Zoology
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• v.24 no.2
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• pp.91-98
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• 1981

It has been confirmed that two dendrograms resulted from two similarity matrices, average taxonomic distance and correlation coefficient matrices, are different with each other when cluster analyses were performed with 571 adults of deer mice, Peromyscus maniculatus using 30 morphometric characters. To choose one of two similarity matrices mentioned above in order to construct a dendrogram representing phenetic relationships among taxa, an objective method using the result from principal component analysis as a standard result to compare with two matrices has been suggested.