• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.117-119
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• 2006

In this work, we suggest another method to localize DFT in spatial domain. This enables DFT algorithm to be used for local pattern matching. Once calculated, it costs same load to calculate localized DFT regardless of the size or the position of local region In spatial domain. We applied this method to face detection problem and got the results which prove the utility of our method.

• Proceedings of the Safety Management and Science Conference
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• 2012.04a
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• pp.573-577
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• 2012

Based on latest research, the parametric quality statistics cannot be used in non-normal process with demand pattern of many-variety and small-volume, since it involves extremely small sample size. The research proposes nonparametric quality statistics according to the number of lot or batch in the non-normal process. Additionally, the nonparametric Process Capability Index (PCI) is used with 14 identified non-normal distributions.

• Journal of the Korea Society of Computer and Information
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• v.14 no.10
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• pp.251-258
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• 2009

Data mining is a method that extract useful knowledges from huge size of data. Recently, a focussing research part of data mining is to find interesting patterns in graph databases. More efficient methods have been proposed in graph mining. However, graph analysis methods are in NP-hard problem. Graph pattern mining based on pattern growth method is to find complete set of patterns satisfying certain property through extending graph pattern edge by edge with avoiding generation of duplicated patterns. This paper suggests an efficient approach of reducing computing time of pattern growth method through pattern growth's property that similar patterns cause similar tasks. we suggest pruning methods which reduce search space. Based on extensive performance study, we discuss the results and the future works.

• The Transactions of the Korea Information Processing Society
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• v.5 no.3
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• pp.833-841
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• 1998

The ann of this study is 10 propose all eff'tcient mclhod for partition of multi-dimensIOnal feature space into pattern subspace for automated generation of fuzzy rule. The suggested mclhod predicates on sequential subdivision of the fuzzy subspacc. and the size of construc1cd pattern space is variable. Under this procedure, n-dimensional pattern space, after considering the distributional characteristic patterns, is partitioned into two different pattern subspaces. From the two subspaces, the pattern space for further subdivision is chosen; then, this subdivision procedure recursively repeats itself until the stopping condition is fulfilled. The result of this study is applied to 2, 4, 7 band of satellite Landsat TM and satisfac10ry result is acquired.

• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.39-42
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• 2000

Motion estimation plays an important role for video coding. In this paper, we derive optimal search patterns for fast block matching motion estimation. By analyzing the block matching algorithm as a function of block shape and size, we can find an optimal search pattern for initial motion estimation. The proposed idea, which has been verified experimentally by computer simulations, can provide an analytical basis for the current MPEG-2 proposals. In order to choose a more compact search pattern for BMA, we exploit the statistical relationship between the motion and the frame difference of each block.

• ETRI Journal
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• v.13 no.2
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• pp.34-41
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• 1991

In this paper, a new distributed parallel algorithm for pattern classification based upon Self-Organizing Neural Network(SONN)[10-12] is developed. This system works without any information about the number of clusters or cluster centers. The SONN model showed good performance for finding classification information, cluster centers, the number of salient clusters and membership information. It took a considerable amount of time in the sequential version if the input data set size is very large. Therefore, design of parallel algorithm is desirous. A new distributed parallel algorithm is developed and experimental results are presented.

• Journal of the Korea Fashion and Costume Design Association
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• v.18 no.2
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• pp.101-113
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• 2016

This study was conducted in order to analyze draping and flat pattern according to jacket design, and provide basic materials for developing a jacket pattern that can enhance fitness, functionality, and aesthetic expression of clothes by reflecting esthetic expression of draping and efficiency of flat pattern at the same time. For the experimental jacket designs of a one-piece sleeve jacket and a two-piece sleeve jacket were selected among the entries of the designer Rubina for 2014 F/W Seoul Fashion Week. Designer brand Rubina usually produced clothes using draping and the designer brand company provided the experimental patterns for the study. We also had flat patterns of the same design and size specifications designed by a flat patternmaker who has 30 year-experience in flat pattern like Rubina. The test apparel jacket was made of 20's cotton yarns. Three models wore the jackets and evaluation on appearance fitness was conducted by 7 members in an expert panel group from August 10, 2015 to September 10, 2015. As a result of appearance fitness analysis on one-piece sleeve jacket, there were significant difference in 4 items among 17 items in terms of overall appearance. The appearance of jackets by draping had higher score than those using flat pattern. As for two-piece sleeve jacket, there were significant differences in 7 items among 17 items related to overall appearance. As for the items related to sleeve, 5 items out of 13 showed significant differences. Except for one item, appearance of jackets using draping had higher score than flat pattern. As for motion fitness, draping was evaluated to be more comfortable. Applying the items with high scores in appearance and motion fitness in draping to flat pattern, The study suggests a new jacket pattern development that would increase the satisfaction of consumers for future research.

• Journal of Sensor Science and Technology
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• v.15 no.6
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• pp.433-441
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• 2006

Because of the low power and low rate of a sensor network, outlier is frequently occurred in the time series data of sensor network. In this paper, we suggest periodic pattern analysis that is applied to the time series data of sensor network and predict outlier that exist in the time series data of sensor network. A periodic pattern is minimum period of time in which trend of values in data is appeared continuous and repeated. In this paper, a quantization and smoothing is applied to the time series data in order to analyze the periodic pattern and the fluctuation of each adjacent value in the smoothed data is measured to be modified to a simple data. Then, the periodic pattern is abstracted from the modified simple data, and the time series data is restructured according to the periods to produce periodic pattern data. In the experiment, the machine learning is applied to the periodic pattern data to predict outlier to see the results. The characteristics of analysis of the periodic pattern in this paper is not analyzing the periods according to the size of value of data but to analyze time periods according to the fluctuation of the value of data. Therefore analysis of periodic pattern is robust to outlier. Also it is possible to express values of time attribute as values in time period by restructuring the time series data into periodic pattern. Thus, it is possible to use time attribute even in the general machine learning algorithm in which the time series data is not possible to be learned.

• Fashion & Textile Research Journal
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• v.18 no.5
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• pp.658-667
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• 2016

The purpose of this study is 1) to research how practitioners in fashion industry in South Korea perceive concepts of Technical Design/Designer, 2) to compare and analyze issues at work by occupation, 3) to research specific works in garment development process, and 4) to compare and analyze work involvement by occupation, type of a company and etc, and 5) to propose the role of Technical Designers in apparel companies in South Korea. There were two methods to conduct this study, which were in-depth interview and survey. Both methods were conducted to designers, merchandisers, pattern makers, technical designers, and production coordinators. Frequency analysis, ANOVA, Duncan test, and Factor analysis were performed to get results by using SPSS 18.0 program. The results are following. There were 50 works during garment development process from the result of in-depth interview, and 6 factors were obtained from the result of Factor analysis, which were 'Works about Sample in Sample Development Process', 'Works about Product's Pattern and Size Spec', 'Works about Development of Garment's Design', 'Works about Planning of Product Development and Management of Product in Stock', 'Works about Production Process', and 'Preparation Works for Sample Development'. In conclusion, technical designer in apparel companies in South Korea should be in charge of works about sample in sample development process and decision making of product' size spec, which is included in works about product's pattern and size spec. Also, they should complete technical package after product is developed by designers.

• Fashion & Textile Research Journal
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• v.15 no.1
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• pp.130-137
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• 2013

The percentage of overweight people has increased in older people due to the change of body shape (including pregnancy and giving birth for women). Obesity is accompanied by body shape changes; subsequently, there are more pattern design considerations compared to standard body shapes. This paper classifies the upper body shape of overweight women in Korea, analyzes features by body shape and proposes basic pattern design data that reflects the features of plus-size women body shapes. The data on 540 subjects in the overweight group (from 20 to 69 years old)whose BMI was over 25 was selected. The following features by shape were identified in accordance with the upper body shape classification of overweight women. Body Shape1 had lower body obesity with long stature and arms in proportion to the trunk length and represented 22.2% of the subjects. Body Shape2 had most parts near average sizes for overweight body shapes with short height and arms that represented 37.6% of the subjects (the highest ratio). Body Shape3 was the smallest body shape in the four groups with the most distinct body figure and represented 30.7% of the subjects. Body Shape4 (9.4% of the subjects)was the upper body obesity type (the fattest group)and with of the waist bigger abdominal obesity type.