• Journal of the Korea Society of Computer and Information
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• v.10 no.6 s.38
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• pp.17-26
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• 2005

In this paper we propose three nonparametric tests such as Wilcoxon test, Median test and Van der Waerden test, based on linear rank statistics for detecting edges in images. The methods used herein are based on detecting changes in gray-levels obtained using an edge-height parameter between two sub-regions in a 5$\times$5 window We compare and analysis the performance of three statistical edge detectors in terms of qualitative measures with the edge maps and objective, quantitative measures.

• Journal of Environmental Impact Assessment
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• v.6 no.1
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• pp.111-119
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• 1997

This study was carried out to suggest the best statistical test which may be used to quantify the change of water quality between two groups. Traditional t-test may not be used in cases where the normality of underlying population distribution is not assured. Three non-parametric tests which are based on the relative order of the measurements, were studied to find out the applicability in water quality data analysis. The sign test is based on the sign of the deviation of the measurement from the median value, and the binomial distribution table is used. The signed rank test utilizes not only the sign but also the magnitude of the deviation. The Wilcoxon rank-sum test which is basically same as Mann-Whitney test, tests the mean difference between two independent samples which may have missing data. Among the three non-parametric tests studied, the singed rank test was found out to be applicable in the quantification of the change of water quality between two samples.

• Journal of the Korean Operations Research and Management Science Society
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• v.40 no.4
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• pp.35-48
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• 2015

We analyze the systemic risk based on the information flows using the variance decomposition, DebtRank methods, and the Industry Sector Indices during 2001. 01 to 2015. 08. Using the KOSPI stock market as our setting, we find that (i) the systemic risk calculated by information flows of variance decompositions method shows strong positive relations with the market volatility, (ii) the magnitude of systemic risk measured from the information flows network by DebtRank method increases after the subprime financial crisis.

• Communications for Statistical Applications and Methods
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• v.23 no.3
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• pp.215-230
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• 2016

The powers of some tests for independence hypothesis against positive (negative) quadrant dependence in generalized Farlie-Gumbel-Morgenstern distribution are compared graphically by simulation. Some of these tests are usual linear rank tests of independence. Two other possible rank tests of independence are locally most powerful rank test and a powerful nonparametric test based on the $Cram{\acute{e}}r-von$ Mises statistic. We also evaluate the empirical power of the class of distribution-free tests proposed by Kochar and Gupta (1987) based on the asymptotic distribution of a U-statistic and the test statistic proposed by $G{\ddot{u}}ven$ and Kotz (2008) in generalized Farlie-Gumbel-Morgenstern distribution. Tests of independence are also compared for sample sizes n = 20, 30, 50, empirically. Finally, we apply two examples to illustrate the results.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.1
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• pp.18-33
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• 2014

A Word is the smallest unit for text analysis, and the premise behind most text-mining algorithms is that the words in given documents can be perfectly recognized. However, the newly coined words, spelling and spacing errors, and domain adaptation problems make it difficult to recognize words correctly. To make matters worse, obtaining a sufficient amount of training data that can be used in any situation is not only unrealistic but also inefficient. Therefore, an automatical word extraction method which does not require a training process is desperately needed. WordRank, the most widely used unsupervised word extraction algorithm for Chinese and Japanese, shows a poor word extraction performance in Korean due to different language structures. In this paper, we first discuss why WordRank has a poor performance in Korean, and propose a customized WordRank algorithm for Korean, named KR-WordRank, by considering its linguistic characteristics and by improving the robustness to noise in text documents. Experiment results show that the performance of KR-WordRank is significantly better than that of the original WordRank in Korean. In addition, it is found that not only can our proposed algorithm extract proper words but also identify candidate keywords for an effective document summarization.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.1
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• pp.110-114
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• 2010

We describe a new method for text categorization using TextRank algorithm. Text categorization is a problem that over one pre-defined categories are assigned to a text document. TextRank algorithm is a graph-based ranking algorithm. If we consider that each word is a vertex, and co-occurrence of two adjacent words is a edge, we can get a graph from a document. After that, we find important words using TextRank algorithm from the graph and make feature which are pairs of words which are each important word and a word adjacent to the important word. We use classifiers: SVM, Na$\ddot{i}$ve Bayesian classifier, Maximum Entropy Model, and k-NN classifier. We use non-cross-posted version of 20 Newsgroups data set. In consequence, we had an improved performance in whole classifiers, and the result tells that is a possibility of TextRank algorithm in text categorization.

• Journal of the Korea Society of Computer and Information
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• v.19 no.8
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• pp.27-34
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• 2014

In this paper, we propose a pupil detection method using hybrid projection function and rank order filter. To reduce error to detect eyebrows as pupil, eyebrows are detected using hybrid projection function in face region and eye region is set to not include the eyebrows. In the eye region, potential pupil candidates are detected using rank order filter and then 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 template matching, we select a pair with the smallest similarity measure as final two pupils. The experiments have been performed for 700 images of the BioID face database. The pupil detection rate is 92.4% and the proposed method improves about 21.5% over the existing method..

• International Journal of Aeronautical and Space Sciences
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• v.14 no.4
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• pp.341-349
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• 2013

This paper considers the optimum design of flexbeam cross-sections for a full-scale bearingless helicopter rotor, using an efficient hybrid optimization algorithm based on particle swarm optimization, and an improved genetic algorithm, with an effective constraint handling scheme for constrained nonlinear optimization. The basic operators of the genetic algorithm, of crossover and mutation, are revisited, and a new rank-based multi-parent crossover operator is utilized. The rank-based crossover operator simultaneously enhances both the local, and the global exploration. The benchmark results demonstrate remarkable improvements, in terms of efficiency and robustness, as compared to other state-of-the-art algorithms. The developed algorithm is adopted for two baseline flexbeam section designs, and optimum cross-section configurations are obtained with less function evaluations, and less computation time.

• The Korean Journal of Food And Nutrition
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• v.27 no.6
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• pp.979-989
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• 2014

The purpose of this study was to investigate the association between dietary behavior and temperament & character in preschool children, and to offer basic data that can be applied for nutrition education and counseling. A total of 211 parents of preschool children aged 3~5 years performed the Korean version of Preschool Temperament and Character Inventory (K-psTCI), a questionnaire based on Cloninger's seven-factor model of personality, along with a questionnaire about the dietary behaviors of their children. K-psTCI represented seven factors such as harm avoidance (HA), novelty seeking (NS), reward dependence (RD), persistence (P), self-directedness (SD), cooperativeness (CO), and self-transcendence (ST). The subjects were divided into either the high rank group or low rank group based on the mean score of each factor. The high rank group of HA showed significantly less physical activity and less appetite than the low rank group of HA. The children in the high rank of NS were more likely to have picky eating and a late night snack. The children in the low rank of SD or CO were more likely to have undesirable dietary behaviors, such as picky eating, too much snacking, and lower appetite than those in the high rank of SD or CO. In conclusion, individual temperament & character in preschool children may be associated with their dietary behavior, and understanding temperament & character in children may be important facts to screen and to develop an effective nutrition education program for children.

• Journal of Digital Contents Society
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• v.9 no.4
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• pp.625-633
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• 2008

Recently, the participation, opening and joint ownership of the users are important issue. The users want professional and accurate information from web. But users often suffer from retrieving accurate information. Even though the users find information they want, it is not guaranteed that the information is reliable since there are too much information placed on the web. Thus, we propose the novel rank metric to promote reliability and efficiency in information retrieval. In order to verify our approach, we implement a web site based on the proposed rank metric for nonofficial medical science information. The proposed rank metric based on user's level. This is to give score of text through differential rate depending on the user's level. The proposed rank metric enhances the reliability of text which is reflecting the user's mental factor. Thus, this method can be used for enhancing the reliability of text.