• Current Research on Agriculture and Life Sciences
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• v.15
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• pp.53-67
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• 1997

The objective of this study is to provide with the hydro-meteological and probabilistic characteristics of the storms of typhoons that have been passed through the Korean peninsula during the last twenty-three years since 1961. The paths and intensities of the typhoons were analyzed. Fifty weather stations were selected and the rainfall data during typhoon periods were collected. Rainfall data were analyzed for the patterns and probabilistic distributions. The results were presented to describe the areal distributions of probabilistic characteristics. The results obtained from this study can be summarized as follows: 1. The most frequent typhoon path that has passed through the Korean peninsula was type E, followed by types CWE, W, WE, and S. The most frequent typhoon intensity was type B, followed by A, super A, and e types, respectively. 2. The third quartile typhoon rainfall patterns appear most frequently followed by the second, first, and last quartiles, respectively, in Seoul, Pusan, Taegu, Kwangju and Taejon. The single typhoon rainfalls with long rainfall durations tended to show delayed type rainfall patterns predominantly compared to the single rainfalls with short rainfall durations. 3. The most frequent probabilistic distribution of typhoon rainfall event is Pearson type-III, followed by Two-parameter lognormal distribution, and Type-I extremal distribution. 4. The most frequent probability distribution model of seashore location was Pearson type-III distribution. The most frequent probability distribution model of inland location was two parameter lognormal distribution.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.05a
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• pp.31-33
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• 2007

Devising an efficient one-pass frequent pattern mining algorithm has been an issue in data mining research in recent past. Pattern growth algorithms like FP-Growth which are found more efficient than candidate generation and test algorithms still require two database scans. Moreover, FP-growth approach requires rebuilding the base-tree while mining with different support counts. In this paper we propose an item-based tree, called I-Tree that not only efficiently mines frequent patterns with single database scan but also provides multiple mining scopes with multiple support thresholds. The 'build-once-mine-many' property of I-Tree allows it to construct the tree only once and perform mining operation several times with the variation of support count values.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.11
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• pp.5287-5303
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• 2018

Handling vast amount of data found in large transactional datasets is an obvious challenge for the conventional data mining algorithms. Addressing this challenge, our paper proposes a parallel approach for proper decomposition of mining problem into sub-problems in order to find frequent patterns from these datasets. The proposed, Pattern Mining for Large Distributed Dataset (PMLDD) approach, ensures minimum dependencies as well as minimum communications among sub-problems. It establishes a linear aggregation of the intermediate results so that it can be adapted to large-scale programming models like MapReduce. In this context, an algorithmic structure for MapReduce programming model is presented. PMLDD guarantees an efficient load balancing among the sub-problems by a specific selection criterion. Further, it optimizes the number of required iterations over the dataset for mining frequent patterns as compared to the existing approaches. Finally, we believe that our approach is scalable enough to handle larger datasets in terms of performance evaluation, and the result analysis justifies all these mentioned concerns.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.771-773
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• 2005

There have been researches about analyzing the information retrieval patterns of log file to efficiently obtain the users' information research patters in web environment. The methods frequently used in their researches is to suggest the algorithms by which the frequent one is derived from the path traversal patterns in efficient way. But one of their general problems is not to provide the proper solution in case of complex, that is, general topological patterns. Therefore this paper tries to suggest a efficient algorithm after defining the general information retrieval pattern.

• Journal of the Korean Society of Clothing and Textiles
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• v.35 no.3
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• pp.359-370
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• 2011

This study analyzes the textiles design of natural indigo dyed products in Korea and Japan. In this study, a total of 556 Korean natural indigo dyed products, and 2,730 Japanese natural indigo dyed products were used for analysis. The subjects of this study were 556 natural indigo dyed products and 2,730 Japanese natural indigo dyed products selling natural indigo dyed products which were found using search engine keywords of natural indigo dyeing and natural dyeing. Research and analysis was treated regarding the products, items, patterns, and the representation techniques of the patterns. The results of this study are as follows. In the pattern used for natural indigo dyed products, 71.4% of Korean products have no pattern, but 77.1% of Japanese products have patterns. On the representation techniques of the patterns, Korean products used tie-dyeing and a dip patterned fabric. While in the Japanese products, the most frequent patterning techniques were paraffin dye, followed by tie-dyeing, yarn-dyed and weaving, screen printing, and yarn-dyed and knitting. Regarding the kinds of patterns for natural indigo dyed products, only 8 kinds of patterns were used in Korean products; however, over 50 kinds of various patterns were used in Japanese products. Most patterns in the Korean products were ion patterns made by tie-dyeing. While in the Japanese products, the most frequent patterns were stripe patterns, followed by flower, dot, and ion patterns. Based on these research results, the problems of the textile design of Korean natural indigo dyed products were that most of the products have no pattern, and even though there were patterns, they lacked variations between the products. While in the case of Japan, they used the traditional and modem patterns of various textile representation techniques.

• Journal of Korean Institute of Industrial Engineers
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• v.32 no.3
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• pp.242-252
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• 2006

Data mining is the exploration and analysis of huge amounts of data to discover meaningful patterns. One of the most important data mining problems is association rule mining. Recent studies of mining association rules have proposed a closure mechanism. It is no longer necessary to mine the set of all of the frequent itemsets and their association rules. Rather, it is sufficient to mine the frequent closed itemsets and their corresponding rules. In the past, a number of algorithms for mining frequent closed itemsets have been based on items. In this paper, we use the transaction itself for mining frequent closed itemsets. An efficient algorithm is proposed that is based on a link structure between transactions. Our experimental results show that our algorithm is faster than previously proposed methods. Furthermore, our approach is significantly more efficient for dense databases.

• Journal of Fashion Business
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• v.19 no.4
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• pp.57-74
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• 2015

The history of foot-binding was once regarded as a unique practice accentuating the beauty of a woman and the culture of the costume, to be found nowhere except in China. This thesis makes it an aim to understand the culture of costume in China by analyzing the beauty of foot-binding, and its meanings associated with the historical background of the costume. The method of investigation was by both previous literature on the topic and case analysis. The shoes were analyzed by colors, patterns and decorations; selecting 70 pieces easily accessible in the Tianjin Huaxia Shoes Culture Museum. In terms of form, the general type was of the most frequent, followed by one with an elevated toe, mixed type, and one of the downward toe, sequentially. The color of foot-binding shoes were mostly vivid chromatic colors, while the achromatic ones like black and grey constituting significant portions. In view of the patterns, plants patterns were the most frequent, followed by the mixed patterns of mostly flowers with butterflies, bats, and birds desiring the prosperity of descendants. In view of the ornaments, embroidery was the most frequent, while the mixed shoes included tassels, sequins, applique, and shoes without ornaments were of distributions. The forms, colors, patterns and ornaments clearly associated with the wishes of artistic beauty, sexuality, and rise in women's social status may be in the hope of leading others to understand the costume culture embedded in the Chinese by providing important clues about them.

• Journal of the Korean Society of Food Culture
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• v.9 no.3
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• pp.241-250
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• 1994

In this study, we analyzed 2-day food records of the 1990 Korean National Nutrition Survey data for 2,000 households, and investigated most popular menu patterns by area, income, meal. The basic menu patterns of Korean, excluding side dishes, were Rice+Soup, Rice+Stew, Rice, Others, Rice+Soup+Stew in the order of proportion for all analyzed sectors. And the proportion of menus with the rice as a main dish was about 90% on the whole. The most popular menus of Korean were Rice+Soup+Kimchi(4.52%), Noodle+Kimchi(4.30%). When they ate rice as a main dish, they had soup, kimchi, and 1 or 2 other side dishes. At large cities, Noodle+Kimchi was the most frequent menu(5.20%). On the other hands, small cities and rural areas, Rice+Soup+Kimchi+Cooked vegetable was common. For the households which salaries less than 5 million won, Rice+Stew+Kimchi is the most prevalent, but households which salaries higher than 5 million won, Noodle+Kimchi was most frequent. At breakfast and dinner, the proportion of Rice+Stew+Kimchi+Cooked vegetable was 4.70%. But at lunch, Noodle+Kimchi was the most frequent and other menu combinations based on noodle were also common. Therefore most households showed conventional rice based menu patterns, but these patterns were decreasing for the large cities, and high income households. Especially at lunch, they used various menus which were not based on rice.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.3
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• pp.461-467
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• 2019

Advances in location-aware and IoT (Internet of Things) technology increase the rapid generation of massive movement data. Knowledge discovery from massive movement data helps us to understand the urban flow and traffic management. This paper proposes a method to analyze frequent origin-destination sequence patterns from irregular spatiotemporal taxi pick-up locations. The proposed method starts by conducting cluster analysis and then run a frequent sequence pattern analysis based on identified clusters as a base unit. The experimental data is Seoul taxi trajectory data between 7 a.m. and 9 a.m. during one week. The experimental results present that significant frequent sequence patterns occur within Gangnam. The significant frequent sequence patterns of different regions are identified between Gangnam and Seoul City Hall area. Further, this study uses administrative boundaries as a base unit. The results based on administrative boundaries fails to detect the frequent sequence patterns between different regions. The proposed method can be applied to decrease not only taxis' empty-loaded rate, but also improve urban flow management.

• Journal of Digital Convergence
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• v.15 no.6
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• pp.229-236
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• 2017

An efficient frequent pattern algorithm is essential for mining association rules as well as many other mining tasks for convergence with its application spread over a very broad spectrum. Models for mining pattern have been proposed using a FP-tree for storing compressed information about frequent patterns. In this paper, we propose a centroid frequent pattern growth algorithm which we called "CAWFP-Growth" that enhances he FP-Growth algorithm by making the center of weights and frequencies for the itemsets. Because the conventional constraint of maximum weighted support is not necessary to maintain the downward closure property, it is more likely to reduce the search time and the information loss of the frequent patterns. The experimental results show that the proposed algorithm achieves better performance than other algorithms without scarifying the accuracy and increasing the processing time via the centroid of the items. The MapReduce framework model is provided to handle large amounts of data via a pseudo-distributed computing environment. In addition, the modeling of the proposed algorithm is required in the fully distributed mode.