• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.8
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• pp.36-41
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• 2011

In multiple antenna systems, spatial facing correlation causes a significant degradation in performance. In this work, a method for reducing the sensitivity to spatial fading correlation through the bi-directional use of spatial resources is investigated. Firstly, the concept of bi-directional use of spatial resources is introduced. Then, the ability of this technique to reduce the sensitivity to spatial fading correlation is then shown through an analysis of the number of usable eigenmodes (UEMs). This system is found to efficiently reduce the sensitivity to spatial fading correlation.

• International Journal of Industrial Entomology and Biomaterials
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• v.5 no.1
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• pp.44-52
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• 2002

To understand the relationship among different quantitative traits, correlation studies were performed by utilizing eighty-eight inbred strains of silkworm, Bombyx mori L. on twelve economic characters. Analysis resulted in correlation of 5th instar period with total larval period (r ＝ 0.7882), cocoon weight with shell weight (r ＝ 0.8326), shell weight with shell ratio (r ＝ 0.5067), shell ratio with raw silk ％ (r ＝ 0.7570), raw silk ％ with filament length (r ＝ 0.3490), filament size (denier) with reelability (r ＝ 0.3193) and boil-off loss % (r ＝ 0.2792). Negative correlation was observed among filament length with filament size (r ＝ 0.7582) and reelability with boil-off loss % (r ＝ -0.3236). Correlation of different quantitative characters for quality silk production is discussed.

• Structural Engineering and Mechanics
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• v.32 no.6
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• pp.725-740
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• 2009

A new simple relation for the estimation of modal correlation coefficients is presented. It is obtained from the decomposition of covariances of modal responses into background and resonant contributions, as it is commonly done for the variances. Thanks to appropriate assumptions, the modal correlation coefficients are estimated as weighted sums of two limit values, corresponding to the background and resonant responses respectively. The weighting coefficients are expressed as functions of the background-to-resonant ratios, which makes the proposed formulation convenient and easily accessible. The simplicity of the mathematical formulation facilitates the physical interpretation. It is for example proved that modal correlation coefficients can be non negligable even in case of well separated natural frequencies, which is sometimes unclear in the litterature. The new relation is mainly efficient in case of large finite element models. It is applied and validated on a finite element buffeting analysis of the Viaduct of Millau, the highest bridge deck ever built so far.

• KCID journal
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• v.18 no.1
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• pp.25-32
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• 2011

In order to effectively manage the reservoir, reservoir water quality management should be based on physicochemical and configurational characteristics. In this research, correlation between factors affecting the reservoir water quality was examined. Chl-a and COD shows the highest positive correlation. Chl-a and T-P also has a high positive correlation, however Chl-a and T-N show lower correlation relatively. Even though T-N is an important factor for phytoplankton growth which increase Chl-a concentration, corelation of Ch1-a and T-N shows that enough nitrogen in the reservoir isn't no longer limiting factor. The age of reservoir can cause of increasing COD and SS. Embankment height and elevation of reservoirs shows strong negative correlation to water quality. That means reservoir which is higher embankment height and locate in higher elevations is less contaminated. Regression expression was derived with Chl-a and water quality parameters, and height of reservoir. Finally Chl-a was simulated using regression expression and it was a good approach to predict the Chl-a concentration.

• Communications for Statistical Applications and Methods
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• v.29 no.6
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• pp.655-664
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• 2022

On the motivation by an integrative study of multi-omics data, we are interested in estimating the structure of the sparse cross correlation matrix of two high-dimensional random vectors. We rewrite the problem as a multiple testing problem and propose a new method to estimate the sparse structure of the cross correlation matrix. To do so, we test the correlation coefficients simultaneously and threshold the correlation coefficients by controlling FRD at a predetermined level α. Further, we apply the proposed method and an alternative adaptive thresholding procedure by Cai and Liu (2016) to the integrative analysis of the protein expression data (X) and the mRNA expression data (Y) in TCGA breast cancer cohort. By varying the FDR level α, we show that the new procedure is consistently more efficient in estimating the sparse structure of cross correlation matrix than the alternative one.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.8
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• pp.845-852
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• 2018

Mayer-Schönberger and Cukier(2013) explain why big data is important for our life, while showing many cases in which analysis of big data has great significance for our life and raising intriguing issues on the analysis of big data. The two authors claim that correlation is in many ways practically far more efficient and versatile in the analysis of big data than causality. Moreover, they claim that causality could be abandoned since analysis and prediction founded on correlation must prevail. I critically examine the two authors' accounts of causality and correlation. First, I criticize that corelation is sufficient for our analysis of data and our prediction founded on the analysis. I point out their misunderstanding of the distinction between correlation and causality. I show that spurious correlation misleads our decision while analyzing Simpson paradox. Second, I criticize not only that causality is more inefficient in the analysis of big data than correlation, but also that there is no mathematical theory for causality. I introduce the mathematical theories of causality founded on structural equation theory, and show that causality has great significance for the analysis of big data.

• The Journal of the Korea Contents Association
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• v.16 no.1
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• pp.391-402
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• 2016

The purpose of this study is to use meta-analysis as a research method to investigate the correlation between early child teachers' teaching efficacy and their job satisfaction, and thereby look into the effect size of the two variables and their sub-variables. To achieve the purpose, this researcher chose a total of 37 theses for analysis and collected 289 data for analyzing the effect size. Based on the data, CMA(Comprehensive Meta Analysis) 2.0 was applied. According to the analysis, the correlation between early childhood teachers' teaching efficacy and their job satisfaction was higher than the medium effect size on the basis of Cohen(1992) research. In the sub-variables of teaching efficacy, the correlation of personal teaching efficacy with job satisfaction showed higher effect size than that of general teaching efficacy. In the sub-variables of job satisfaction, the correlation between the belief in job and teaching efficacy showed the highest effect size. In terms of thesis type as a moderating variable, Ph.D dissertations showed higher effect size than journals or M.A. theses. As the result of the meta-analysis on publishing year and the number of samples, there was no statistical significance. On the basis of the analysis results, discussions and limitations of this study were suggested.

• Journal of the Korea institute for structural maintenance and inspection
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• v.21 no.1
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• pp.23-29
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• 2017

In this study, a post-correlation analysis for shaking table test of square water storage tank is presented for the use of advances in earthquake-resistant design of liquid storage tank. For this purpose, the ANSYS CFX program is selected for the CFD analysis. Sensitivity analysis for resonant sloshing motion in terms of grid size and turbulence model suggested that (1) horizontal grid size as well as vertical grid size is a key variable in the sloshing analysis, and (2) the SST turbulence model is best for the sloshing analysis. Finally, correlation analyses for a non-resonant harmonic input and scaled earthquake excitation of the El Centro (1940) NS component are carried out using the grid and turbulence model established through the post-correlation analysis for the resonant motion. As a result, sloshing time histories by the CFD analysis agreed very well with the test results.

• Korean Journal of Food Science and Technology
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• v.50 no.2
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• pp.244-247
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• 2018

Quantitative analysis for non-host infection bacteriophage was conducted for their enumeration. Flow cytometry and epifluorescence microscopy (EPM) were selected as counting methods. Correlation analysis was performed based on the plaque assay method on the existing host infection and consisted of Pearson correlation statistical analysis, regression analysis, and difference analysis. Analyses of 12 samples with flow cytometry and plaque assay methods showed that there was a correlation of 96.7% with Pearson correlation value r=0.967, $R^2$ 0.9352, and difference value of 1.063. Analyses of 12 samples with EPM and plaque assay methods showed that there was a correlation of 99.0% with Pearson correlation value r=0.990, $R^2$ 0.9811, and difference value of 1.605. Therefore, flow cytometry and epifluorescence microscopy would be effective for enumeration of Weissella cibaria bacteriophage with plaque assay.

• Korean Journal of Human Ecology
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• v.13 no.6
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• pp.833-845
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• 2004

This study examines different individual and environmental factors that affect children's self-control. For an analysis, locus of control, perceived competence, and achievement motivation were all included in individual variables. For family variables, mothers' parenting and patents' marriage conflict were examined. For classroom psycho-social environment, teacher support, peer relationship, class involvement, and teachers' supervision were used. The sample consisted of 548 fifth and sixth grade children. Statistics and methods used for the data analysis were Cronbach's alpha, frequency, percentage, Pearson's correlation, and Hierarchical Regression. Several major results were found from the analysis: First, locus of control, perceived competence, and achievement motivation had a positive correlation with children's self-control. Second, mothers' affective parenting had a positive correlation with children's self-control. However, mothers' controlling parenting and parents' marriage conflict had a negative correlation with it. Third, teacher support, peer relationship, and class involvement had a positive correlation with children's self-control. In addition, teacher supervision had a positive correlation with girls' self-control. Fourth, class involvement, locus of control, and academic competence were important variables predicting boys' self-control. On the other hand, Class involvement, achievement motivation, academic competence, teacher's supervision, and mothers' controlling parenting were important variables predicting girl's self-control.