• Journal of the Korean Society of Environmental Restoration Technology
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• v.12 no.6
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• pp.99-111
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• 2009

There have been continuous studies about urban parks since 1971 until now. However, there was neither deep analysis of park space nor research about green areas and lawn space. Below is the summary of the main results obtained based on the analysis of the problems with the spatial structure and park facilities of 8 examinatory parks. The analysis of use pattern revealed that lawns in green areas are becoming almost unusable spaces. Therefore plans for more active utilization of lawn space is necessary. There were high correlations among unnecessary and necessary factors of park, use of green areas and the reasons for not using it; thus the analysis suggested that other plans be considered for utilization of lawn space in oder to obtain stronger efficacy. The objective of the present research was to suggest an opinion concerning the improvement of spatial structure of urban parks, by making unusable spaces of parks usable through appropriate park structuring, so that users can utilize more parks. Especially with regard to green areas, the present research has a meaning in that it suggested a method of improving spatial structure by means of green areas desired by users and facilities they can use.

• Journal of Fashion Business
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• v.17 no.2
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• pp.63-81
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• 2013

A Study using compare and analyze about differences among three patterns(shape and size of pattern, fitting and amount of air gap and so on) through 3D simulation. This study use 3D simulation program, DC Suite version 3.0. The results are as a follows: The results of estimation about total appearance, the pattern of Bunka is best of all pattern about total fitting and silhouette of front and back side. The pattern of armstrong and on&on stand low in estimation. As the total fitting, the pattern of Bunka is 4.40, the pattern of Armstrong is 2.60 and the pattern of On&on is 1.60. The result show better pattern of Bunka than pattern of Armstrong and On&on. When we examine about space between body and cloth, the pattern of Bunka is best. The pattern of Armstrong don't have problems about back side but front side have some problem of getting loose. Because it only have a waist dart so dart size is too big. The pattern of On&on have so much space because it don't have a waist dart. On the amount of air gap, the pattern of Bunka squash up body so it have the amount of air gap 0.08 at bust circumference and underbust circumference. Next is the pattern of Armstrong, amount of air gap is 0.14 at bust circumference and 0.23 at underbust circumference. The pattern of On&on's amount of air gap is 0.30 at bust circumference and 0.37 at underbust circumference. So the pattern of Bunka is bodice block of the best closing adhesion and the On&on is a loose-fitting pattern.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.3
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• pp.305-323
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• 2010

This paper proposes an efficient and yet powerful local descriptor called phase-space partition based descriptor (PPD). This descriptor is designed for the mobile image matching and retrieval. PPD, which is inspired from SIFT, also encodes the salient aspects of the image gradient in the neighborhood around an interest point. However, without employing SIFT's smoothed gradient orientation histogram, we apply the region based gradient statistics in phase space to the construction of a feature representation, which allows to reduce much computation requirements. The feature matching experiments demonstrate that PPD achieves favorable performance close to that of SIFT and faster building and matching. We also present results showing that the use of PPD descriptors in a mobile image retrieval application results in a comparable performance to SIFT.

• ETRI Journal
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• v.29 no.3
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• pp.336-352
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• 2007

Sequential pattern mining has become an essential task with broad applications. Most sequential pattern mining algorithms use a minimum support threshold to prune the combinatorial search space. This strategy provides basic pruning; however, it cannot mine correlated sequential patterns with similar support and/or weight levels. If the minimum support is low, many spurious patterns having items with different support levels are found; if the minimum support is high, meaningful sequential patterns with low support levels may be missed. We present a new algorithm, weighted interesting sequential (WIS) pattern mining based on a pattern growth method in which new measures, sequential s-confidence and w-confidence, are suggested. Using these measures, weighted interesting sequential patterns with similar levels of support and/or weight are mined. The WIS algorithm gives a balance between the measures of support and weight, and considers correlation between items within sequential patterns. A performance analysis shows that WIS is efficient and scalable in weighted sequential pattern mining.

• Journal of the Korean Institute of Educational Facilities
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• v.23 no.6
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• pp.19-26
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• 2016

In this study, moving awareness of students having different physical conditions in homebase and attitudes of students to spacial use in user's aspect were analyzed. As shown in the results, the dissatisfaction degree of the second grade using homebase type was higher than the first and the third grades using exclusive space for a class, homeroom type. The necessity of exclusive space for a class was highly shown in the second grade students. Students of the first and the third grades showed similar pattern in using frequency of homeroom. The results showed that behavior pattern of students was different with their physical conditions. Especially, factors showing obvious differences between the two groups were possession awareness of their belongings, tendency to route choice of high frequency, stay awareness of main stay in time to rest and point of time using restroom. These results will be useful to design various models in variation type of schools.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.4
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• pp.355-359
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• 2014

In this paper, we proposed the new fuzzy pattern classifier which combines several fuzzy models with simple consequent parts hierarchically. The basic component of the proposed fuzzy pattern classifier with hierarchical structure is a fuzzy model with simple consequent part so that the complexity of the proposed fuzzy pattern classifier is not high. In order to analyze and divide the input space, we use Fuzzy C-Means clustering algorithm. In addition, we exploit Conditional Fuzzy C-Means clustering algorithm to analyze the sub space which is divided by Fuzzy C-Means clustering algorithm. At each clustered region, we apply a fuzzy model with simple consequent part and build the fuzzy pattern classifier with hierarchical structure. Because of the hierarchical structure of the proposed pattern classifier, the data distribution of the input space can be analyzed in the macroscopic point of view and the microscopic point of view. Finally, in order to evaluate the classification ability of the proposed pattern classifier, the machine learning data sets are used.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.181-189
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• 2013

In this paper, we introduce the fuzzy neural network based on the individual input space to design the pattern recognizer. The proposed networks configure the network by individually dividing each input space. The premise part of the networks is independently composed of the fuzzy partition of individual input spaces and the consequence part of the networks is represented by polynomial functions. The learning of fuzzy neural networks is realized by adjusting connection weights of the neurons in the consequent part of the fuzzy rules and it follows a back-propagation algorithm. In addition, in order to optimize the parameters of the proposed network, we use real-coded genetic algorithms. Finally, we design the optimized pattern recognizer using the experimental data for pattern recognition.

• Journal of the Korean housing association
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• v.22 no.4
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• pp.33-41
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• 2011

The purpose of this study was to identify characteristics of space usage patterns by types of elderly households(single or couple). For the study, 74 elders who were older than 65 were selected and their living behaviors at their home during a day (24 hours) were analyzed. Respondents were classified into 6 types based on a combination of their household type, income level and health status. The results showed that the elderly residents tended to live a well-regulated life, however, each type had unique time and space use pattern. For example, the more the elder residents were healthy, the more they used many rooms. Frail elderly residents spent most of the day in their bedroom. Also, if they had a spouse, each one tended to use a separate private room for his or her daily life whether they shared a bedroom or not.

• Korean Institute of Interior Design Journal
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• v.26 no.1
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• pp.75-82
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• 2017

This study reviews the process of creating the patterns through the Christopher Alexander's books to discover the fundamental rules for creation of the pattern language. The essential ideas of 11 rules describing the characteristics of the pattern language are organized by keyword depending on the characteristics of each rule. Then, this study analyzes which keyword was applied importantly and how it had been developed chronologically in the Alexander's books. As a result, 5 keywords - reflection of cultural difference, reflection of human desires, solving the repeated problem, function suitable for principal purpose, and network structure - are applied to his early books in which the pattern language was theoretically developed, the pattern of traditional society was discovered and the network structure was developed. Another 5 keywords - user participation method, new problem solving, structure preserving transformation, post-mechanization method, and central invariant structure - are applied to the books in his mid-term after completion of the pattern theory which discover new pattern for contemporary society and apply the pattern language to time and space. In his later books which organize the theory of pattern language and suggest the direction for using the pattern language, 5 keywords - wholeness, post-mechanization method, user participation method, new problem solving, and structure preserving transformation - are applied. Users may use the pattern language more precisely if he/she considers the keywords of the early period in searching the patterns of existing environment, the keywords of the intermediate period in searching the patterns of new environment or in regard to time and space, and the keywords of the later period in considering direction of the application of the pattern language.

• Asian Journal of Atmospheric Environment
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• v.6 no.2
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• pp.127-135
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• 2012

Urbanization has led to a reduction in green spaces and thus transformed the spatial pattern of urban land use. An increase in air temperature directly affects forest vegetation, phenology, and biodiversity in urban areas. In this paper, we analyze the changing land use patterns and urban heat distribution (UHD) in Seoul on the basis of a spatial assessment. It is necessary to monitor and assess the functions of green spaces in order to understand the changes in the green space. In addition, we estimated the influence of green space on urban temperature using Landsat 7 Enhanced Thematic Mapper Plus (ETM+) imagery and climatic data. Results of the assessment showed that UHD differences cause differences in temperature variation and the spatial extent of temperature reducing effects due to urban green space. The ratio of urban heat area to green space cooling area increases rapidly with increasing distance from a green space boundary. This shows that urban green space plays an important role for mitigating urban heating in central areas. This study demonstrated the importance of green space by characterizing the spatiotemporal variations in temperature associated with urban green spaces.