• Journal of Fisheries and Marine Sciences Education
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• v.21 no.1
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• pp.121-133
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• 2009

This study tested the relations of schools organizational climate and teachers' job stresses, perceived by 913 teachers from 45 elementary, junior- and senior-high schools. Pearson's correlation analysis for the relations between the sub-factors of both organizational climate and job stresses and cannonical correlation analysis for the relative contribution of individual variable of organizational climate upon job stress were applied for the test. The results of Pearson's correlation analysis showed that while 'intimacy', 'esprit', 'considerations', and 'production emphasis' climate had negative correlations with job stress sub-factors, 'disengagement' and 'aloofness' climate had positive correlation. 'Student guidance', a sub-factor of job stresses, did not have statistically significant correlation with any sub-factors of organizational climate. Findings from cannonical correlation analysis showed 2 significant cannonical functions to explain the relations between the sets of variables. 'Disengagement' from organizational climate positively contributed with 'authority forfeiture' and 'dissention and conflict' of the job stresses variables.

• Journal of Yeungnam Medical Science
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• v.35 no.1
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• pp.63-69
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• 2018

Background: Kinovea software that tracking semi-automatically the motion in video screen has been used to study motion-related tasks in several studies. However, the validation of this software in open field test to assess locomotor activity have not been studied yet. Therefore, this study aimed to examine the reliability and validity of this software in analyzing locomotor activities. Methods: Thirty male Institute Cancer Research mice were subjected in this study. The results examined by this software and the classical method were compared. Test-retest reliability and inter-rater reliability were analyzed with Pearson's correlation coefficient and intraclass correlation coefficient (ICC). The validity of this software was analyzed with Pearson's correlation coefficient. Results: This software showed good test-retest reliability (ICC=0.997, 95% confidence interval [CI]=0.975-0.994, p<0.001). This software also showed good inter-rater reliability (ICC=0.987, 95% CI=0.973-0.994, p<0.001). Furthermore, in three analyses for the validity of this software, there were significant correlations between two methods (Pearson's correlation coefficient=0.928-0.972, p<0.001). In addition, this software showed good reliability and validity in the analysis locomotor activity according to time interval. Conclusion: This study showed that this software in analyzing drug-induced locomotor activity has good reliability and validity. This software can be effectively used in animal study using the analysis of locomotor activity.

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.1
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• pp.155-166
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• 2008

The quantitative bivariate spatial pattern analysis was applied for the water quality and nutrients data of Masan Bay, and for this analysis Pearson's r as aspatial correlation measurement, Moran's I as spatial association measurement and L index as integration of aspatial and spatial measurement methods were used. To understand the aspatial and spatial characteristics implicated in L index, Pearson's r as well as Moran's I were classified into 3 types respectively, and Pearson's r and Moran's I were combined with 9 types, and also quantile of L index value was used for each of those 9 types. Finally, these types were defined as 5 groups having not overlapped L index range. According to the application result of L index groups, bivariate water quality and nutrients showed no aspatial correlation regardless of spatial association in February and July, but they showed aspatial correlation having clustered spatial pattern in May and November. The result of this study providing the guideline for the interpretation of aspatial correlation and spatial association using L index is expected to be helpful for the marine environment pattern analysis using quantitative index for further study.

• Journal of KIISE
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• v.41 no.10
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• pp.799-809
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• 2014

In this paper, we address the problem of computing Pearson correlation coefficients and Spearman's rank correlation coefficients in a secure manner while data providers preserve privacy of their own data in distributed environment. For a data mining or data analysis in the distributed environment, data providers(data owners) need to share their original data with each other. However, the original data may often contain very sensitive information, and thus, data providers do not prefer to disclose their original data for preserving privacy. In this paper, we formally define the secure correlation computation, SCC in short, as the problem of computing correlation coefficients in the distributed computing environment while preserving the data privacy (i.e., not disclosing the sensitive data) of multiple data providers. We then present SCC solutions for Pearson and Spearman's correlation coefficients using secure scalar product. We show the correctness and secure property of the proposed solutions by presenting theorems and proving them formally. We also empirically show that the proposed solutions can be used for practical applications in the performance aspect.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.11
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• pp.115-120
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• 2019

This study was undertaken to determine the correlation between β-amyloid, serum lipid levels, and cognitive function in the elderly with mild Alzheimer's dementia. The study was conducted in December 2018, enrolling 45 elderly people with mild Alzheimer's disease. Blood analysis measured the β-amyloid and serum lipid levels, and cognitive function was measured using MMSE-K. The correlation between β-amyloid, serum lipid levels and cognitive function was determined using Pearson's correlation analysis. A significantly negative correlation was observed between the β-amyloid level and cognitive function (p<0.05). Furthermore, serum lipid levels and cognitive function also revealed a significantly negative correlation between TC and LDL levels (p<0.05). These results indicate that increasing levels of β-amyloid, TC, and LDL augments a negative correlation that decreases the cognitive function, signifying that management of pathologic factors related to dementia is important for the prevention and improvement of cognitive function in dementia patients.

• Journal of Oriental Neuropsychiatry
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• v.28 no.2
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• pp.83-94
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• 2017

Objectives: The purpose of this study was to conduct a characteristic study on Bell's palsy patients using the Core Seven Emotion Inventory (CSEI) followed by correlation analysis with BAI and BDI. Methods: This study was conducted by analyzing medical records of 30 patients that had visited ${\bigcirc}{\bigcirc}$ University Oriental hospital and completed the Core Seven Emotions Inventory (CSEI), BAI and BDI. A total of 30 patients diagnosed with Bell's palsy were analyzed using SPSS (Statistical Package for the Social Science, IBM, United States of America, Version 22.0). Descriptive statistics, Independent t-test, One-way repeated measure, ANOVA and Pearson Correlation analysis were used for data analysis. Results: 1. Kyeong (驚), Bi (悲) and Gong (恐) emotions were relatively higher than U (憂), Hui (喜). 2. According to sex, female patients exhibited higher Kyeong (驚) and Gong (恐) emotions than male patients. 3. According to age, patients older than 60 exhibited higher Hui (喜) emotion than patients younger than 59. 4. According to the correlation between prognosis and age in patients older than 60 revealed negative correlation in Kyeong (驚) and Gong (恐) emotions. Conclusions: Using the Core Assessment Instrument based on Chiljeong for Bell's palsy patients is effective relative to diagnostic and clinical aspects of Bell's palsy.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.228-239
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• 2022

Many countries around the world using ICT technologies have various technologies to keep pace with the 4th industrial revolution, and various algorithms and systems have been developed accordingly. Among them, many industries and researchers are investing in unmanned automation systems based on AI. At the time when new technology development and algorithms are developed, decision-making by big data analysis applied to AI systems must be equipped with more sophistication. We apply, Pearson's correlation analysis is applied to six independent variables to find out the job satisfaction that office workers feel according to their job characteristics. First, a correlation coefficient is obtained to find out the degree of correlation for each variable. Second, the presence or absence of correlation for each data is verified through hypothesis testing. Third, after visualization processing using the size of the correlation coefficient, the degree of correlation between data is investigated. Fourth, the degree of correlation between variables will be verified based on the correlation coefficient obtained through the experiment and the results of the hypothesis test

• International Journal of Contents
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• v.18 no.1
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• pp.17-26
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• 2022

With the acceleration of urbanization and industrialization, air pollution has become increasingly serious, and the pollution control situation is not optimistic. Climate change has become a major global challenge faced by mankind. To actively respond to climate change, China has proposed carbon peak and carbon neutral goals. However, atmospheric pollutants and meteorological factors that affect air quality are complex and changeable, and the complex relationship and correlation between them must be further clarified. This paper uses China's 2013-2018 high-resolution air pollution reanalysis open data set, as well as statistical methods of the Pearson Correlation Coefficient (PCC) to calculate and visualize the design and analysis of environmental monitoring big data, which is intuitive and it quickly demonstrated the correlation between pollutants and meteorological factors in the temporal and spatial sequence, and provided convenience for environmental management departments to use air quality routine monitoring data to enable dynamic decision-making, and promote global climate governance. The experimental results show that, apart from ozone, which is negatively correlated, the other pollutants are positively correlated; meteorological factors have a greater impact on pollutants, temperature and pollutants are negatively correlated, air pressure is positively correlated, and the correlation between humidity is insignificant. The wind speed has a significant negative correlation with the six pollutants, which has a greater impact on the diffusion of pollutants.

• Journal of the Korean Society of Clothing and Textiles
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• v.30 no.1 s.149
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• pp.83-93
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• 2006

The purpose of this study is to analyze the relationship among subjective textures, sensibilities and objective handle of knit fabrics and to provide useful information in planning and designing knit fabrics. We made 20 plain knit fabrics, as specimens, with a combination of 5 kinds of wool/rayon fiber contents and 4 kinds of stitch loop length. For the subjective evaluation, we used 29 questions of subjective textures and sensibilities and employed statistical analysis tools such as factor, Pearson's correlation analysis. An objective handle was measured by Kawabata evaluation system and HV and THV was calculated by KN-402-KT and KN-301-winter. The analysis of a Pearson's correlation with objective properties and handles and structural properties of knit fabrics demonstrated a highly linear relationship. Especially, wool/rayon contents and WT of tensile properties and loop stitch length and G of shear properties showed a correlation coefficient over 0.9. But a relationship of objective properties and subjective textures and sensibilities was non-linear and a linear multi-regression analysis showed that a objective handle had a lower prediction power in the area of subjective textures and sensibilities.

• Journal of Digital Convergence
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• v.12 no.6
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• pp.509-517
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• 2014

The objective of this study was to investigate the degree of interpersonal relationship in nursing students according to their characteristics. This descriptive correlation study conducted visit-surveys with organized questionnaires and sampled 306 nursing students. Data was analyzed by t-tests, ANOVA, Pearson's correlation coefficients and multiple regression analysis using SPSS/WIN 14.0. Findings revealed that; 1) the degree of interpersonal relationship in nursing students according to their characteristics were significantly different in age and grade; 2) Pearson's correlation revealed a significant association among interpersonal relationship, family function and self-differentiation; 3) multiple regression analysis showed self-differentiation and family function significantly influenced interpersonal relationship in nursing students. Based on the findings of this study, nursing professionals should provide proper program of interpersonal relationship related to self-differentiation and family function.