• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.5
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• pp.1951-1966
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• 2020

Recent advancements in mobile device technology have enabled real-time positioning so that mobile patterns of people and favorable locations can be identified and related researches have become plentiful. One of the fields of research is the relationship between the object properties and the favored location to visit. The object properties of a person include personality, which is a major property jobs, income, gender, and age. In this study, we analyzed the relationship between the human personality and the preference of the location to visit. We used Spearman's Rank correlation coefficient, one of the many methods that can be used to determine the correlation between two variables. Instead of using actual data values, Spearman's Rank correlation coefficient deals with the ranks of the two data sets. In our research, the personality and the location data sets are used. Our personality data is ranked in five ranks and the location data is ranked in 8 ranks. Spearman's Rank correlation coefficient showed better results compared to Pearson linear correlation coefficient and Kendall rank correlation coefficient. Using Spearman's correlation coefficient, the degree of the relationship between the personality and the location preference is found to be 43%.

• Nuclear Engineering and Technology
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• v.52 no.8
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• pp.1798-1806
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• 2020

In this study, we investigated whether there is a significant relationship between the natural radiation dose rate and the cancer incidences in Korea by using a big data analysis. The natural dose rate data for this analysis were the measurement data obtained from the 171 monitoring posts of the 113 administrative districts in Korea over the 10 years from 2007 to 2016. The relative cancer incidences for this analysis were the difference in the cancer patients per hundred thousand people year-on-year in the administrative districts with the five highest and the five lowest natural gamma dose rates each year over the same period. To analyze the correlation between the two variables, Spearman's rank correlation coefficient between the two rates was derived using R, a well-known big data analysis tool. The analysis showed that Spearman's rank correlation coefficient was more than 0.05 and that the correlation between the two variables was not statistically significant.

• Korean Journal of Human Ecology
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• v.15 no.3
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• pp.439-447
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• 2006

The purpose of this study is to explore the accuracy and reliability of subjective evaluation instruments in evaluating sensibility of similar fabrics, Kendall's coefficient of concordance W (agreement among subjects) and Spearman rank correlation coefficient (reproducibility after 1 week) were used to evaluate which one is more efficient. Eight kinds of linen-like silk fabrics finished with polyurethane resin were used, Subjective evaluation instruments such as rating scale method, contrasting method against a control, rank ordering method, paired comparison and Quad analysis were used, 'Stiffness and Pliability' and 'Preference of summer fabric' were estimated, From the result of subjective stiffness and pliability, which are effective on objective properties of fabric, the rating scale method in Kendall's coefficient of concordance W and Quad analysis in Spearman rank correlation coefficient were given the highest score, From the result of subjective preference of summer fabric, which are effective on individual sensibility, contrasting method against a control in Kendall's coefficient of concordance W and Quad analysis in Spearman rank correlation coefficient revealed the highest score, Regarding the accuracy, reliability and efficiency, Quad analysis was an efficient method for subjective evaluation of linen-like silk fabrics.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.6
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• pp.633-641
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• 2020

Residential complexes offer a sense of community and convenience, but making closed and privated space have been criticized.Closed urban spaces have issues encouraging residential segregation.large apartment complexes over 1,000 households,the most poular housing type in Korea, seems to make urban space more closed and privated than ever before. Our study puts forward and tests the hypothesis that large apartment complexes with over 1,000 households are linked to residential segregation. First of all, we examined the degree of residential segregation of metropolitan cities in Korea over a nine-year period (2011-2019). The dissimilarity index and the delta index were used for determining the extent of residential segregation. Next, we tested our hypothesis by Spearman's rank correlation analysis. Spearman's rank correlation analysis was performed on the residential segregation index per administrative division ("dong") and the number of large apartment complexes per administrative division ("dong").

• Integrative Medicine Research
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• v.7 no.2
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• pp.136-140
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• 2018

Background: The Sasang constitutional analysis tool (SCAT) is an integrated Sasang constitutional analysis system developed by the Korea Institute of Oriental Medicine. This study aimed to evaluate the reliability of a questionnaire for measuring personality and pathophysiological symptoms that is one of the components of the SCAT. Methods: In this study, data were collected from university students in their twenties. Tests were administered twice, with an interval of 4 weeks between tests. Test-retest data from 176 students were collected and used for analysis. Internal consistency reliability was analyzed by using Cronbach's alpha coefficient, and test-retest reliability was analyzed by using Spearman's rank correlation coefficient. Results: Cronbach's alpha coefficient was 0.788 for personality, 0.511 for eating habits, 0.718 for digestion, 0.667 for heat- or cold-wise penchant, and 0.612 for water ingestion. Spearman's rank correlation coefficients, which were used to assess correlations between test and retest results, ranged from 0.444 to 0.828. Conclusion: The internal consistency and test-retest reliability of the SCAT questionnaire were found to be satisfactory.

• 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.

• Korean Journal of Community Nutrition
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• v.3 no.2
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• pp.273-280
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• 1998

This study was designed to estimate the improvement of Validity for food frequency questionnaire(FFQ) by offering multiple choice portion size in developing a questionnaire. Validity of the two methods(food frequency questionnaire I=FFQ I & Food frequency questionnaire II=FFQ II) was tested in comparison with reference method of the 7-day weighed record(7DWR). Dietary consumption data of the three methods(FFQ I, FFQ II & 7DWR) were collected from 101 female university students for the analysis. Validity was measured in two categories : One was the nutrient intake value from the three methods, the other was the identification of between individual variation within the group. Spearman's rank order correlation test and distribution graphs were used for the analysis. The result showed that individual intake value of the FFQII was closer to that of the 7DWR than that of the FFQ I.Spearman's rank order correlation between the FFQII and the 7DWR did not show any improved correlation. The distribution graphs of nutrient intake derived from both the FFQ I and the FFQII were different from that of the 7DWR. Therefore, it could be suggested that single one portion size food frequency questionnaire is an equally efficient method as a multiple choice food frequency questionnaire to be adopted in epidemiologic studies.

• Journal of Power System Engineering
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• v.19 no.1
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• pp.56-63
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• 2015

In this study, the exhaust characteristics of the diesel engine for the change of the mixing ratio of biodiesel fuel were quantitatively analyzed by using the numerical analysis method. As the fuel used in the experiment, the diesel and biodiesel(waste oil, soybean oil), the mixed fuel BD2(Diesel only), BD3, BD5, BD20, BD50 and BD100 were used. The injection pressure($p_{inj}$) was set to 400bar, 600bar, 800bar, 1000bar and 1200bar as the experimental variable. Also the concept of the standard deviation, Pearson's correlation coefficient and Spearman rank-order correlation coefficient based on the statistics was introduced in order to analyze the exhaust characteristics of the quantitative NOx and Soot according to the injection pressure and the mixing ratio variation of biodiesel blending fuel. It is considered that as a result of studies, for the waste oil, NOx and Soot can be simultaneously reduced through control of the mixing ratio at the regions of $p_{inj}=400bar$ and $p_{inj}=600bar$, and the Soot can be reduced without affecting on the emission of NOx at more than $p_{inj}=800bar$. For the soybean oil, NOx and Soot can be simultaneously reduced at $p_{inj}=400bar$ and the Soot can be reduced without affecting on the emission of NOx at $p_{inj}=600bar$.

• Journal of Internet Computing and Services
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• v.25 no.2
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• pp.39-47
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• 2024

Time series analysis is widely employed by many organizations to solve business problems, as it extracts various information and insights from chronologically ordered data. Among its applications, measuring time series similarity is a step to identify time series with similar patterns, which is very important in time series analysis applications such as time series search and clustering. In this study, we propose an efficient method for measuring time series similarity that focuses on anomalies rather than the entire series. In this regard, we validate the proposed method by measuring and analyzing the rank correlation between the similarity measure for the set of subsets extracted by anomaly detection and the similarity measure for the whole time series. Experimental results, especially with stock time series data and an anomaly proportion of 10%, demonstrate a Spearman's rank correlation coefficient of up to 0.9. In conclusion, the proposed method can significantly reduce computation cost of measuring time series similarity, while providing reliable time series search and clustering results.

• IE interfaces
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• v.24 no.4
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• pp.314-322
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• 2011

This study analyzes a relationship between Data Envelopment Analysis(DEA) efficiency scores and a normalization index in order to examine the validity of DEA models. A normalization index concerned in this study is 'sales per R&D project fund' which is regarded as a crucial R&D project performance evaluation index in practice. For this correlation analysis, three distinct DEA models are selected such as DEA basic model, DEA/AR-I revised model(i.e. DEA basic model with Acceptance Region Type I constraints) and Super-Efficiency(SE) model. Especially, SE model is adopted where efficient R&D projects(i.e. Decision Making Units, DMU's) with DEA efficiency score of unity from DEA basic model can be further differentiated in ranks. Considering the non-normality and outliers, two rank correlation coefficients such as Spearman's ${\rho}_s$ and Kendall's ${\tau}_B$ are investigated in addition to Pearson's ${\gamma}$. With an up-to-date empirical massive dataset of n = 482 R&D projects associated with R&D Loan Program of Korea Information Communication Promotion Fund in the year of 2011, statistically significant (+) correlations are verified between the normalization index and every model's DEA efficiency scores with all three correlation coefficients. Especially, the congruence verified in this empirical analysis can be a useful reference for enhancing the practitioner's acceptability onto DEA efficiency scores as a real-world R&D project performance evaluation index.