• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.05a
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• pp.39-42
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• 2000

Both evolutionary programming (EP) and genetic algorithm (GA) are classified as evolutionary computation. They have been successful in finding a solution in a wide search space. In this paper, our objectives are to find the coefficients of characteristic equation, in terms of the stability indices using EP and GA, and to make a comparison of both methods.

• Journal of the Korean Society of Radiology
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• v.12 no.4
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• pp.505-510
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• 2018

In this study, we allocate bits by quantizing these fractal coefficients through a quantizer which can extract the probability distribution. In the coding process of IFS, a variable size block method is used to shorten the coding time and improve the compression ratio. In the future, it will be necessary to further improve the coding time and the compression rate while maintaining the best image quality in the fractal coding process.

• The Korean Journal of Applied Statistics
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• v.21 no.5
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• pp.875-888
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• 2008

Mosaic plots, proposed by Hartigan and Kleiner (1981, 1984), are very useful in visualizing categorical data. In mosaic plot, multi-way classified cell frequencies are represented by rectangles with proportional area. The plot is easy to understand while preserving the information contained in the data. Plot's appearance, however, does change substantially depending on the order of variables and the orders of categories with variable put into the plot. In this study, we propose the algorithms for ordering variables and categories of the categorical data to be explored via mosaic plots. We demonstrate our methods to three well-known datasets: Titanic, Housing and PreSex.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.5_6
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• pp.321-327
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• 2004

SPIHT algorithm is a wavelet based fast and effective technique for image compression. It uses a list structure to store status information which is generated during set-partitioning of toro-tree. Usually, this requires lots of additional memory depending on how high the bit-rate is. Therefore, in this paper, we propose a new technique called MZC-BFS, which needs no additional memory when running SPIHT algorithm. It explicitly performs a breadth first search of the spatial-tree using peano-code and eliminates additional memory as it uses pre-status significant test for encoding and LSB bits of some coefficients for decoding respectively. This method yields nearly the same performance as SPIHT. This may be desirable in fast and simple hardware implementation and reduces the cost of production because no lists and additional memory are required.

• Journal of the Korean Geographical Society
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• v.39 no.2
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• pp.212-228
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• 2004

This paper is concerned with an important aspect of regional income convergence, ${\beta}$-convergence, which refers to the negative relationship between initial income levels and income growth rates of regions over a period of time. The common research framework on ${\beta}$-convergence which is based on OLS regression models has two drawbacks. First, it ignores spatially autocorrelated residuals. Second, it does not provide any way of exploring spatial heterogeneity across regions in terms of ${\beta}$-convergence. Given that empirical studies on ${\beta}$-convergence need to be edified by spatial data analysis, this paper aims to: (1) provide a critical review of empirical studies on ${\beta}$-convergence from a spatial perspective; (2) investigate spatio-temporal income dynamics across the U.S. labor market areas for the last 30 years (1969-1999) by fitting spatial regression models and applying bivariate ESDA techniques. The major findings are as follows. First, the hypothesis of ${\beta}$-convergence was only partially evidenced, and the trend substantively varied across sub-periods. Second, a SAR model indicated that ${\beta}$-coefficient for the entire period was not significant at the 99％ confidence level, which may lead to a conclusion that there is no statistical evidence of regional income convergence in the US over the last three decades. Third, the results from bivariate ESDA techniques and a GWR model report that there was a substantive level of spatial heterogeneity in the catch-up process, and suggested possible spatial regimes. It was also observed that the sub-periods showed a substantial level of spatio-temporal heterogeneity in ${\beta}$-convergence: the catch-up scenario in a spatial sense was least pronounced during the 1980s.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.3
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• pp.60-67
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• 2016

In cumulative transfer functions, as number of transfer increase, the impact of individual transfer to transfer cost increase linearly or non linearly. This function can effectively explain various passengers's travel behavior who choose their travel routes in integrated transit line networks including bus and railway modes. Using the function, it is possible to simulate general situations such that even though more travel times are expected, less number of transfer routes are preferred. However, because travel cost with cumulative transfer function is known as non additive cost function types in route search algorithms, finding an optimal route in integrated transit networks is confronted by the insolvable enumeration of all routes in many cases. This research proposes a methodology for finding an optimal path considering cumulative transfer function. For this purpose, the reversal phenomenon of optimal path generated in route search process is explained. Also a heuristic methodology for selecting an optimal route among multiple routes predefined by the K path algorithm. The incoming link based entire path deletion method is adopted for finding K ranking path thanks to the merit of security of route optimality condition. Through case studies the proposed methodology is discussed in terms of the applicability of real situations.

• Journal of Korean Library and Information Science Society
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• v.35 no.4
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• pp.229-250
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• 2004

The purpose of this study is to investigate the correlation between users' preferences of Personality types and their attitude towards patterns of Web OPAC use mainly focus on their search behaviour and their preferences for the interface. Data res collected through the MBTI test and self-designed online questionnaire. The original MBTI personality types were re-coded into 4 categories of preferences of personality types, that is, E(Extraversion), I(Introversion), S(Sensing), N(iNtuition), T(Thinking)-F(Feeling), and J(Judging)-P(Perception) and then analysed their correlation with patterns of Web OPAC use by Person's correlation coefficient (r) in SPSS Windows Ver. 11.0. It is noteworthy that 9 out of 28 factors of Web OPAC search behaviour and preferences for interfaces show statistically significant correlation with users' MBTI preferences of personality types.

• Archives of design research
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• v.14 no.4
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• pp.5-14
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• 2001

Among Human Sensibility-oriented products a gap between the images that designers try to express through that product and users emotional evaluation becomes an issue. The data on the correlation between image words used for design evaluation and images used in the design process are especially significant. This study based on these correlations suggests a Fuzzy retrieval system supporting styling design with images and image words. In the system, the relational data are demonstrated by Fuzzy thesaurus as correlation coefficient from the degree of similarity among image words. And the degree of similarity is produced based on image evaluation. Image retrieval is conducted by the algorithm of Fuzzy thesaurus development, 1) among image words, 2) images to image words, 3) image words to images and 4) among images: 4 different modes are provided as retrieval modes. Also transfer between modes is carried by direct operating interface, therefore divergent thinking and convergent thinking is supported well. The system consists of operation for the gap and the measurement unit of emotional evaluation, and visualization units. Under unified interface environments are set in order for consistency of the operation.

• Journal of Educational Research in Mathematics
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• v.14 no.1
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• pp.71-88
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• 2004

The purpose of this study was to examine particular variables that play a significant role in the difficulty of math test items in College Scholastic Ability Test (CSAT). The study also aimed to develop a model of measuring the item difficulty. Variables correlated to item difficulty were drawn from the review of the related literature and the analysis of the content and difficulty of the past test items of CSAT. The first instrument was designed by using the correlated variables. According to the results of correlation analysis, the second instrument was made by deleting the variables which showed relatively low correlation with item difficulty and by refining some variables. Several models were proposed by using the revised instrument. The comparison of the R square and cross validity of each model reveals that integrated regression model was the most stable and accurate among the proposed models. The study also showed that statistically significant predictors were choice format, content domain, behavior domain, and the degree of item familiarity in the order of proportion of variance accounted by the predictors. Despite the limited scope of the present research, it can be suggested that its findings provide useful insights into predicting math test item difficulty.

• Journal of the Korean Society for Library and Information Science
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• v.43 no.3
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• pp.399-416
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• 2009

In this study, clustering methods with related tags were discussed for improving search and exploration in the tag space. The experiments were performed on 10 Delicious tags and the strongly-related tags extracted by each 300 documents, and hierarchical and non-hierarchical clustering methods were carried out based on the tag co-occurrences. To evaluate the experimental results, cluster relevance was measured. Results showed that Ward's method with cosine coefficient, which shows good performance to term clustering, was best performed with consistent clustering tendency. Furthermore, it was analyzed that cluster membership among related tags is based on users' tagging purposes or interest and can disambiguate word sense. Therefore, tag clusters would be helpful for improving search and exploration in the tag space.