• Journal of the Korean Data and Information Science Society
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• v.21 no.4
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• pp.803-811
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• 2010

This study analyzes the characteristics of preference ratings by dividing estimated values into four groups according to rank correlation coefficient after obtaining preference estimated value to user's ratings by using collaborative filtering algorithm. It is known that the value of standard error of skewness and standard error of kurtosis lower in the group of higher rank correlation coefficient This explains that the preference of higher rank correlation coefficient has lower extreme values and the differences of preference rating values. In addition, top n recommendation lists are made after obtaining rank fitting by using the result ranks of prediction value and the ranks of real rated values, and this top n is applied to the four groups. The value of top n recommendation is calculated higher in the group of higher rank correlation coefficient, and the recommendation accuracy in the group of higher rank correlation coefficient is higher than that in the group of lower rank correlation coefficient Thus, when using standard error of skewness and standard error of kurtosis in recommender system, rank correlation coefficient can be higher, and so the accuracy of recommendation prediction can be increased.

• 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%.

• The Journal of the Korea Contents Association
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• v.17 no.1
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• pp.201-212
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• 2017

This study presented the new evaluation index which can evaluate the discrimination of DEA models. To evaluate the discrimination of DEA models, data were analyzed using importance index as suggested in previous study and the coefficient of variation as suggested in this study for the discrimination evaluation. This study selected the CCR-DEA, BCC-DEA, entropy, bootstrap, super efficiency, and cross efficiency DEA model for the discrimination evaluation and accomplished empirical analysis. In order to grasp the rank correlation of the models, this study implemented the rank correlation analysis between the efficiency of CCR model and BCC model and entropy, bootstrap, super efficiency, and efficiency of the cross efficiency model. The obtained results of this study are as follows. First, the discrimination rank of models using the importance index and the coefficient of variation was shown to be identical. Therefore, the coefficient of variation can be used the discrimination evaluation index of DEA model. Second, the discrimination of the super efficiency model was found to be the highest rank among 4 models according to the analysis of this present study. Third, the highest rank correlation with CCR model was the super efficiency model. In addition, the super efficiency model was found to be the highest rank correlation with BCC model.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.7
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• pp.1564-1570
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• 2013

In this paper, we propose a robust pupil detection method using rank order filter and cross-correlation. Potential pupil candidates are detected using rank order filter. Eye region is binarized using variable threshold to find eyebrow, and pupil candidates at the eyebrow are removed. The positions of pupil candidates are corrected, the pupil candidates are grouped into pairs based on geometric constraints. A similarity measure is obtained for two eye of each pair using cross-correlation, we select a pair with the largest similarity measure as a final pupil. The experiments have been performed for 500 images of the BioID face database. The results show that it achieves the high detection rate of 96.8% and improves about 11.6% than existing method.

• Journal of the Korea Society of Computer and Information
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• v.21 no.4
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• pp.63-71
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• 2016

This paper is about applying efficient data mining method which improves the score calculation and proper building performance of credit ranking score system. The main idea of this data mining technique is accomplishing such objectives by applying Correlation based Feature Selection which could also be used to verify the properness of existing rank scores quickly. This study selected 2047 manufacturing companies on KOSPI market during the period of 2009 to 2013, which have their own credit rank scores given by NICE information service agency. Regarding the relevant financial variables, total 80 variables were collected from KIS-Value and DART (Data Analysis, Retrieval and Transfer System). If correlation based feature selection could select more important variables, then required information and cost would be reduced significantly. Through analysis, this study show that the proposed correlation based feature selection method improves selection and classification process of credit rank system so that the accuracy and credibility would be increased while the cost for building system would be decreased.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.47
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• pp.169-179
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• 1998

Median rank is used to systemize the evaluation of research personnel in a research institution. Suggested evaluation system is purposed to enhance the fairness, distinguish the factors of evaluation and maximize the synergy of researchers. The factors of evaluation are largely divided into the subjective and the objective factor. The final rank of the researchers is determined with the converted median rank value. The propriety of applying median rank is tested by Spearman's rank correlation coefficient. We also suggest the method of determining the rank of researchers. This evaluation system is not fixed in special case but can be changed in situation. It also can be applied to any other personnel evaluation system through the appropriate revision.

• 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.

• 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.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.12
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• pp.1199-1206
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• 2015

In this study, the exhaust gas of a diesel engine operating on biodiesel(BD) fuel(a mixture of diesel and soybean oil) was investigated for different fuel mixing ratios in the range of BD3 to BD100. The experiments were conducted using injection pressures of 400, 600, 800, 1000, and 1200 bar. The Pearson correlation coefficient and Spearman rank-order correlation coefficient were used to quantify the NOx and Soot emissions based on the fuel mixing ratio and injection pressure. Consequently, the Pearson correlation coefficient obtained for NOx and Soot emissions according to the mixing ratio and injection pressure was -0.811 and the corresponding Spearman rank-order correlation coefficient was -0.884, which indicated that the correlation of the NOx and Soot emissions was linear. Thus, the NOx and Soot have a trade-off relationship. Moreover, at each injection pressure, the Pearson correlation coefficient was a negative number, which indicated an inversely proportional relationship between NOx and Soot.

• Korean Journal of Health Education and Promotion
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• v.30 no.5
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• pp.201-210
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• 2013

Objectives: The public relies on the news media to understand health risks. To examine the surveillance function of Korean health journalism, this study compared the rank-order of the 10 most frequently diagnosed cancers with that of the 10 cancers most frequently covered by three major Korean newspapers. Methods: News stories published between 1999 and 2010 by the Chosun-Ilbo, Joong-Ang-Ilbo, and Dong-A-Ilbo were examined. Data on cancer incidence were collected using the epidemiological data published by a governmental public health institution. To compare the level of the crude rates and the amount of news coverage, rank-order correlation tests and regression analyses were employed. Results: A reduction in the rank-ordered correlation coefficient was observed despite an increase in the overall number of cancer news stories released. The significance of the correlation disappeared after 2006. The big difference of the rank order between the crude rate and the amount of news coverage was observed in the cancer of breast, uteri, thyroid, and gallbladder/biliary. Finally, the three newspapers did not follow the amount change in stomach, lung, liver, and uterine cervix cancer. The four cancers' rank orders of crude rate were lowering, signifying a reduction of the comparative dangerousness of the four cancers. Conclusions: The news media's customization of news content and the negative bias in journalism are suggested as possible influences on the news media's inaccurate representation of cancer risk.