• International journal of advanced smart convergence
• /
• v.9 no.4
• /
• pp.42-51
• /
• 2020

In this paper, the authors propose the pseudo complex correlation coefficient (PCCC) of the two complex random variables (RV), because the four real correlation coefficients (RCC) of the corresponding four real RVs cannot be obtained only from the complex correlation coefficient (CCC) of given two complex RV. Such observation is motivated by the general statement; "The complex jointly-Gaussian random M-vector cannot be completely described by the complex covariance matrix, even though the real Gaussian random 2M-vector can be completely descried by the real covariance matrix. Therefore, in order to describe completely the complex jointly-Gaussian random M-vector, we need an additional matrix, namely the complex pseudo-covariance matrix, along with the complex covariance matrix." Then, we apply PCCC to correlated information sources (CIS) for non-orthogonal multiple access (NOMA) in 5G system, and investigate impact of the proposed PCCC on the achievable data rate of the stronger channel user in the conventional successive interference cancellation (SIC) NOMA with CIS. It is shown that for the given same CCC, the achievable data rates with the different PCCC are different, because the corresponding RCC are different. We also show that as the absolute value of the same CCC increases, the impact of the different PCCC becomes more significant.

• Transactions of the Korean Society of Mechanical Engineers
• /
• v.17 no.5
• /
• pp.1106-1114
• /
• 1993

A composite material is composed of a reinforcement and a matrix, which determine mechanical characteristics of the molded part. There is no doubt that the properties of a composite material depend not only on the characteristics of the matrix but also on the structure of glass fiber mat and a fiber type of reinforcement. Therefore it is very important to study the composites of reinforcement and the matrix, and to control the fiber type in the process of molding of composite materials. In this study, the specimen was made of a glass fiber mat of 6-7mm thickness by scattering it in the air after cutting the glass fiber mat with needle punching makes change according to the type of needle and the number of times of stretching. First the sheet was made by means of a hot-press after accumulating a matrix and a glass fiber according to each mat structure of glass fiber. It was heated the manufactured sheet with the dry oven and molded it a secondary high temperature compression by a 30 ton oilhydraulic press. A definition of a correlation coefficient is showed up during this period and find it out with the relation of the fiber-matrix separation and the fiber orientation. We studied effects of the glass fiber mat structures on the correlation coefficient.

• Communications for Statistical Applications and Methods
• /
• v.22 no.6
• /
• pp.665-674
• /
• 2015

Lack of a general matrix formula hampers implementation of the semi-partial correlation, also known as part correlation, to the higher-order coefficient. This is because the higher-order semi-partial correlation calculation using a recursive formula requires an enormous number of recursive calculations to obtain the correlation coefficients. To resolve this difficulty, we derive a general matrix formula of the semi-partial correlation for fast computation. The semi-partial correlations are then implemented on an R package ppcor along with the partial correlation. Owing to the general matrix formulas, users can readily calculate the coefficients of both partial and semi-partial correlations without computational burden. The package ppcor further provides users with the level of the statistical significance with its test statistic.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2002.05a
• /
• pp.253-259
• /
• 2002

The rigid body characteristics (value of mass, Position of center of mass, moments and products of inertia) of mechanical systems can be identified from FRF data or vibration spectra of rigid body motion. Therefore the accuracy of rigid body characteristics is connected directly with the accuracy of measured data for rigid body motions. In this paper, a method of improving accuracy of measurement of rigid body motion is presented. Applying rigid body theory, ail translational and rotational displacements at a tentative point on the rigid body are calculated using the measured translational displacements for several points and transfer matrix. Then the estimated displacements for the identical points are calculated using the 6 displacements of the tentative Point and transfer matrix. By using correlation coefficient between measured and estimated displacements, we can detect the existence of errors that are contained in a certain measured displacement. Consequently, the improved rigid body motion with respect to a tentative point can be obtained by eliminating the contaminated data.

• Journal of the Korean Data and Information Science Society
• /
• v.23 no.5
• /
• pp.1037-1044
• /
• 2012

Multivariate control charts for effectively monitoring every component in the dispersion matrix of multivariate normal process are considered. Through the numerical results, we noticed that the multivariate control charts based on sample statistic $V_i$ by Hotelling or $W_i$ by Alt do not work effectively when the correlation coefficient components in dispersion matrix are increased. We propose a combined procedure monitoring every component of dispersion matrix, which operates simultaneously both control charts, a chart controlling variance components and a chart controlling correlation coefficients. Our numerical results show that the proposed combined procedure is efficient for detecting changes in both variances and correlation coefficients of dispersion matrix.

• The Korean Journal of Applied Statistics
• /
• v.35 no.1
• /
• pp.77-91
• /
• 2022

The optimal threshold estimation is considered in order to discriminate the mixture distribution in the fields of Biostatistics and credit evaluation. There exists well-known various accuracy measures that examine the discriminant power. Recently, Matthews correlation coefficient and the F1 statistic were studied to estimate optimal thresholds. In this study, we explore whether these accuracy measures are appropriate for the optimal threshold to discriminate the mixture distribution. It is found that some accuracy measures that depend on the sample size are not appropriate when two sample sizes are much different. Moreover, an alternative method for finding the optimal threshold is proposed using the correlation coefficient that defines the ratio of the confusion matrix, and the usefulness and utility of this method are also discusses.

• The Korean Journal of Applied Statistics
• /
• v.28 no.3
• /
• pp.385-392
• /
• 2015

Principal component analysis (PCA), a dimension-reduction technique, is usually implemented after the variables are standardized when the measurement unit of variables are different. To standardize a variable we divide it by its standard deviation. But there is another way to transform a variable to be independent of its measurement unit. It is to divide it by its mean rather than standard deviation. Implementing PCA on standardized variables is equivalent to implementing PCA with a correlation matrix of original variables. Similarly, implementing PCA on the transformed variables divided by their means is equivalent to implementing PCA with a matrix related to the coefficients of variation of the original variables. We explain why we need to implement PCA on the variables transformed by their means.

• Bulletin of the Korean Chemical Society
• /
• v.33 no.9
• /
• pp.2955-2960
• /
• 2012

Product ion yields in the in- and post-source decays of three peptide ions, $[Y_5X+H]^+$ (X = Y (tyrosine), K (lysine), and R (arginine)), generated by matrix-assisted laser desorption ionization (MALDI) were measured at six wavelengths, 307, 317, 327, 337, 347, and 357 nm, using ${\alpha}$-cyano-4-hydroxycinnamic acid (CHCA) and 2,5-dihydroxybenzoic acid (DHB) as the matrices. The temperatures of the early and late plumes generated by MALDI were estimated via kinetic analysis of the product ion yield data. For both matrices, the temperature drop (${\Delta}T$), i.e. the difference in the temperature between the early and late plumes, displayed negative correlation with the absorption coefficient. This was in agreement with the previous reasoning that deeper laser penetration and larger amount of material ablation arising from smaller absorption coefficient would result in larger extent of expansion cooling. The results support the postulation of the expansion cooling occurring in the plume presented previously.

• Journal of applied mathematics & informatics
• /
• v.26 no.3_4
• /
• pp.471-479
• /
• 2008

Let $R\;{\in}\;C^{m{\times}m}$ and $S\;{\in}\;C^{n{\times}n}$ be nontrivial unitary involutions, i.e., $R^*\;=\;R\;=\;R^{-1}\;{\neq}\;I_m$ and $S^*\;=\;S\;=\;S^{-1}\;{\neq}\;I_m$. We say that $G\;{\in}\;C^{m{\times}n}$ is a generalized reflexive matrix if RGS = G. The set of all m ${\times}$ n generalized reflexive matrices is denoted by $GRC^{m{\times}n}$. In this paper, an efficient method for the least squares solution $X\;{\in}\;GRC^{m{\times}n}$ of the matrix equation AXB = D with arbitrary coefficient matrices $A\;{\in}\;C^{p{\times}m}$, $B\;{\in}\;C^{n{\times}q}$and the right-hand side $D\;{\in}\;C^{p{\times}q}$ is developed based on the canonical correlation decomposition(CCD) and, an explicit formula for the general solution is presented.

• Journal of the Institute of Convergence Signal Processing
• /
• v.23 no.3
• /
• pp.143-149
• /
• 2022

This excerpt delineates a quantitative measure of relationship between a research title and its respective abstract extracted from different journal articles documented through a Korean Citation Index (KCI) database published through various journals. In this paper, we propose a machine learning-based similarity metric that does not assume normality on dataset, realizes the imbalanced dataset problem, and zero-variance problem that affects most of the rule-based algorithms. The advantage of using this algorithm is that, it eliminates the limitations experienced by Pearson correlation coefficient (r) and additionally, it solves imbalanced dataset problem. A total of 107 journal articles collected from the database were used to develop a corpus with authors, year of publication, title, and an abstract per each. Based on the experimental results, the proposed algorithm achieved high correlation coefficient values compared to others which are cosine similarity, euclidean, and pearson correlation coefficients by scoring a maximum correlation of 1, whereas others had obtained non-a-number value to some experiments. With these results, we found that an effective title must have high correlation coefficient with the respective abstract.