• The Korean Journal of Ecology
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• v.9 no.3
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• pp.135-147
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• 1986

The simplification and the searching trends of complex data which assumed relationship between predictor variables and object variables are one of primary objective of ecological research. This study was aimed to apply cononical analysis consisting of canonical correlation analysis and canonical variate analysis related to lichen vegetation and several environmental variables which are elevation, height on grond, exposure side and cover values. Data collected from the Duckyoo National Park in August 1985. Lichen species was ranked by eqivocation information theory with cover values. Canonical correlation analysis was applied to one data set both set both environmental variables and lichem family. In order to make two sets of data matrix the scale of position vector ordination was calculated from the vector scalar product for lichen species. Canonical variate analysis was applied to rearranged data which was made by interval class code for environmental variables. The sharpness values was calculated in frequency of cotingency tables and the dispersion profiles of each species in classes of environmental variables was designed to extract component values based on the decomposition of expected frequencies in contingency table. The results of canonical correlation analysis revealed canonical first correlation value 0.815(89%), and second correlation value 0.083(11%). Significance test showed that the hypothesis of joint mutuallity of canonical correlation is accepted (P>0.05). The relation between canonical score of vegetation variables and that of environmental variable indicated linear tendency.

• The Journal of the Society of Korean Medicine Diagnostics
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• v.11 no.2
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• pp.84-95
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• 2007

Background and Purpose: We have studied the trends of EEG signals in the voluntary breathing condition by applying the fractal analysis. According to chaos theory, irregularity of EEG signals can result from low dimensional deterministic chaos. A principal parameter to quantify the degree of Chaotic nonlinear dynamics is correlation dimension. The aim of this study was to analyze correlation between the correlation dimension of EEG and HRV(heart rate variability). We have studied the trends of EEG signals in the voluntary breathing condition by applying the fractal analysis. Methods: EEG raw data were measured by moving windows during 15 minutes. Then, the correlation dimension(D2) was calculated by each 40-seconds-segment in 15 minutes data, totally 36 segments. 8 channels EEG study on the Fp, F, T, P was carried out in 30 subjects. Results and Conclusion: Correlation analysis of HRV was calculated with deterministic non-linear data and stochastic non-linear data. 1. Ch1(Fp1), Ch4(F3), Ch4(F4) is positive correlated with In LF. 2. Ch1(Fp1), Ch3(F3) is positive correlated with In TF.

• Journal of Wellbeing Management and Applied Psychology
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• v.4 no.4
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• pp.1-14
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• 2021

Purpose: This study aims to measure the level of satisfaction with the overall education of current students, who are major consumers of education by department at the Health Care Convergence University, and to establish development strategies such as improving education quality and satisfaction by deriving problems and improvements. Research design, data and methodology: This study drew conclusions through secondary data analysis based on data surveyed by the Educational Performance Management Center of a university in the academic year of 2020. The target of the education consumer satisfaction survey was 470 students of the College in the academic year 2020. Frequency analysis and correlation analysis were applied to the data using the statistical package program SPSS 25 version. Results: In the major curriculum satisfaction survey, the department with the highest score was optics and optics, 4.11, and the department with the lowest score was medical IT, 3.29. Conclusions: The department with the highest correlation in the correlation analysis result of the demand survey by department was the Department of Medical Management and the Department of Medical IT, with a correlation coefficient r=0.984, and the lowest correlation in the correlation analysis result of the demand survey by department was the Department of Medical IT and Dental Hygiene, with a correlation coefficient r= -0.085.

• Journal of the Korean Solar Energy Society
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• v.33 no.4
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• pp.101-110
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• 2013

The propose of this study is to understand the phenomenon of radiation and comparison of analysis of two methods. One is analysis method of same-time data and the another is analysis method of rank data. We confirmed that two methods of correlation analysis had the effectiveness and suitability. The followings are main results from this study. 1) The seasonal correlation coefficient of long and short-wave radiation is higher in winter than in summer because of high humidity in the summer season can makes easily cloud in the sky locally. 2) According to analysis method, there is big difference in correlation coefficient from 0.494(Analysis method of same-time data) to 0.967(Analysis method of rank data) with short-wave radiation by the location during summer. These results have significant value in solar radiation research and analysis. It has explored a new way for solar radiation research of analysis method as well.

• Korean Journal of Remote Sensing
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• v.22 no.5
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• pp.337-350
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• 2006

The characteristics of neighborhood correlation images for change detection were explored at different spatial resolution scales. Bi-temporal QuickBird datasets of Las Vegas, NV were used for the high spatial resolution image analysis, while bi-temporal Landsat $TM/ETM^{+}$ datasets of Suwon, South Korea were used for the mid spatial resolution analysis. The neighborhood correlation images consisting of three variables (correlation, slope, and intercept) were evaluated and compared between the two scales for change detection. The neighborhood correlation images created using the Landsat datasets resulted in somewhat different patterns from those using the QuickBird high spatial resolution imagery due to several reasons such as the impact of mixed pixels. Then, automated binary change detection was also performed using the single and multiple neighborhood correlation image variables for both spatial resolution image scales.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.704-706
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• 2022

In this study, we analyzed the correlation between the amount of photovoltaic power generation and the factors of meteorological changes. A total of 52,561 data were used in the correlation analysis from January 2018 to January 2020, and the variables used in the correlation analysis were time, horizontal plane scattering solar radiation, direct solar radiation, wind velocity, and relative humidity. The temperature was used. Based on this data, we used the Google Colab platform to analyze the correlation, and the analysis revealed whether there was a correlation between solar power and meteorological change factors.

• Journal of the Korea Society of Computer and Information
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• v.22 no.4
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• pp.115-122
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• 2017

The purpose of this study was to evaluate the effect of job satisfaction on turnover intention and organizational commitment in nurses through a systematic literature review and meta-analysis. For the study purpose, 26 studies were selected through a systematic process of using several databases and used to estimate the effect size of correlation between 3 variables. Meta-analysis was applied by usingcrandom effects model, and effect sizes on three types were calculated. Results are as follows. First, the effect size of correlation between job satisfaction and turnover intention is -.58. Second, the effect size of correlation between job satisfaction and organizational commitment is .77. Third, for the organizational commitment and turnover intention relationship, the effect of correlation is -0.68. Furthermore, publication bias analysis were assessed the results by using the funnel plot, Egger's regression test, fail-safe N, and trim-and-fill test. Based on these results, implications for the study were discussed.

• Journal of Ship and Ocean Technology
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• v.5 no.4
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• pp.44-50
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• 2001

Large container carriers are suffering from lack of knowledge on reliable correlation allowances between model tests and full-scale trials, especially at fully loaded condition, Careful full-scale sea trial with a full loading of containers both in holds and on decks was carried out to clarify it. Model test results were analyzed by different methods but with the same measuring data to figure out appropriated correlations factors for each analysis methods, Even if it is no doubt that model test technique is one of the most reliable tool to predict full scale powering performance, its assumptions and simplifications which have been applied on the course of data manipulation and analysis need a feedback from sea trial data for a fine tuning, so called correlation factor. It can be stated that the best correlation allowances at fully loaded condition for both 2-dimensional and 3-dimensional analysis methods are fecund through the careful sea trial results and relevant study on the large size container carriers.

• Journal of Oriental Neuropsychiatry
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• v.30 no.3
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• pp.153-164
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• 2019

Objectives: The purpose of this study was to examine the correlation between CSEI (The Core Seven-Emotions Inventory) and MMPI-2 (Minnesota Multiphasic Personality Inventory-2). Methods: We analyzed the correlation between students' demographic characteristics, blood type, MMPI-2, and CSEI using the SPSS (Statistical Package for the Social Science) 24.0. Descriptive Statistical Analysis, independent t-test, analysis of variance (ANOVA), subsequent analysis duncan (post hoc multiple comparison), and correlation analysis were conducted. Results: 1. According to the demographic characteristics of 91 participants in this study: 60 males (65.9%), 88 unmarried (96.7%), 58 without religion (63.7%), 54 who have experienced stress in the last three months (59.4%), and 82 in their 20s (90.1%) comprised the majority. 2. As a result of verifying correlation by subfactors of CSEI, Hui (喜) showed statistically significant negative correlation with U (憂), Bi (悲), and Gong (恐). Six emotions except Hui (喜) showed statistically significant positive correlation, except for the relationship between U (憂) and Kyeong (驚). 3. Hui (喜) of CSEI had negative correlation with eight factors of MMPI-2 Clinical Scales except Pa (Paranoia) and Ma (Hypomania), whereas Bi (悲) had positive correlation with nine factors of MMPI-2 clinical scales except Mf (Masculinity-Femininity). Sa (思), Bi (悲), and Gong (恐) had similar tendency of positive correlation with six factors of MMPI-2 Restructured Clinical Scales. Conclusions: Based on the above results, we concluded that CSEI's sub factors had consistent correlations with MMPI-2. Thus, CSEI could contribute to psychiatry clinical use.

• Journal of the Korea Society of Computer and Information
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• v.24 no.9
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• pp.119-125
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• 2019

The purpose of this study is to find out the relevant factors of the choice tendency of tourism users to Intelligent Tourism platform through big data analysis, which will help enterprises to make accurate positioning and improvement according to user information feedback in the tourism market in the future, so as to gain the favor of users' choice and achieve long-term market competitiveness. This study takes the Intelligent Tourism platform as the independent variable and the user choice tendency as the dependent variable, and explores the related factors between the Intelligent Tourism platform and the user choice tendency. This study make use of text mining and R language text analysis, and uses SPSS and AMOS statistical analysis tools to carry out empirical analysis. According to the analysis results, the conclusions are as follows: service quality has a significant positive correlation with user choice tendency; service quality has a significant positive correlation with tourism trust; Tourism Trust has a significant positive correlation with user choice tendency; service quality has a significant positive correlation with user experience; user experience has a significant positive correlation with user choice tendency Positive correlation effect.