• Journal of Satellite, Information and Communications
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• v.10 no.2
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• pp.40-45
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• 2015

In this paper, we proposed and implemented a crime prediction algorithm based upon crime influential factors. To collect the crime-related big data, we used a data which had been collected and was published in the supreme prosecutors' office. The algorithm analyzed various crime patterns in Seoul from 2011 to 2013 using the spatial statistics analysis. Also, for the crime prediction algorithm, we adopted a Bayesian network. The Bayesian network consist of various spatial, populational and social characteristics. In addition, for the more precise prediction, we also considered date, time, and weather factors. As the result of the proposed algorithm, we could figure out the different crime patterns in Seoul, and confirmed the prediction accuracy of the proposed algorithm.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2021.05a
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• pp.247-248
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• 2021

Recently, the government is pursuing to reduce the serious accidents in most industries, including the construction industry, by enacting laws on punishment. The accident rate tends to be depended on the size and type of construction sites, and the accidents occur frequently due to inadequate implementation of safety management system and management standards, especially, in small and medium-sized sites. This study has performed the profiling of 265,000 accident cases on construction sites by attribute analysis such as the ratio of days lost to work, and pattern of days lost to work compared to the size of the construction. It turned out that the proportion of accident cases was high mainly in small-scale construction sites, and long-term labor losses occurred. Shortly, it is necessary to establish an institutional standard for applying a realistic safety management cost calculation and management system centered on small-scale sites. Therefore, this study is expected to be used as fundamental data or guideline for developing a customized safety management and accident prevention system for a worker reflecting the conditions of a construction site in the future.

• Fashion & Textile Research Journal
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• v.17 no.2
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• pp.227-236
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• 2015

This study analyzed the lower body type of 30's Korean men to develop a slim-fit pants pattern. As the analysis data, direct measurement data of anthropometric measured value in the 6th Size Korea(KATS, 2010) was used as basic data with 481 men in 30's as analysis objects. The result are as follows. First, the result of analyzing factors for the lower body type classification indicated five factors. Second, the result of executing group analysis (with the independent variable of 5 clusters extracted from the factor analysis)classified the following three types. Type 1(36.8%) displayed a medium height of lower body type, small waist and hip, slim and fit body type with a slim shape between the knee and ankle. The shape between the waist and hip had characteristics of a slight curve and short length. Type 2(35.6%) displayed lowest height of a lower body type that was large and thick between the waist and the hip. The drop value of the waist and the hip was small; therefore, the body type was flat with a minimal curve. The underpart type (below the knee) was the thickest and the length was short. Type 3(27.7%) displayed the highest lower body type, a medium level waist size, flat and narrow waist and belly. This body type had a curve with big drop value of the waist and the hip, lower part from the hip to the ankle (including the knee) and a thick calf with along leg.

• Journal of Environmental Impact Assessment
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• v.29 no.2
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• pp.122-131
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• 2020

Marine Spatial Planning is an emerging strategy that promoting sustainable development at coastal and marine areas based on the concept of ecosystem services. Regarding its methodology, usage rate of resources and its impact should be considered in the process of spatial planning. Particularly, considering the rapid increase of coastal tourism, visitation pattern is required to be identified across coastal areas. However, actions to quantify visitation pattern have been limited due to its required high cost and labor for conducting extensive field-study. In this regard, this study aimed to pose the usage of social big data in Marine Spatial Planning to identify spatial visitation density and critical management zone throughout coastal areas. We suggested the usage of GPS information from Flickr and Twitter, and evaluated the critical management zone by applying spatial statistics and density analysis. This study's results clearly showed the coastal areas having relatively high visitors in the southern sea of South Korea. Applied Flickr and Twitter information showed high correlation with field data, when proxy excluding over-estimation was applied and appropriate grid-scale was identified in assessment approach. Overall, this study offers insights to use social big data in Marine Spatial Planning for reflecting size and usage rate of coastal tourism, which can be used to designate conservation area and critical zones forintensive management to promote constant supply of cultural services.

• Journal of the Korean Society of Clothing and Textiles
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• v.41 no.4
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• pp.646-660
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• 2017

This study provides basic data to develop a brassiere pattern that can cover the big breast of breast enlargement patients. In this study, we also showed areas of the brassiere cup pattern and the body surface of the breast on a breast enlargement patient. The results of the study are as follows. Correlation analysis was obtained between volume and body surface area and breast detail dimensions. After the correction process, we proposed a research bra pattern for breast augmentation patients. The cup-boundary in bra patterns of breast enlargement surgery patients is longer than the bra patterns of the general breast; therefore, the height of the inner and outer edges of the upper cups is higher. Also, it is necessary to set the new breast upper point when measuring the upper length in patients with breast augmentation surgery because the points of circumference of the breast are marked higher than chest circumference.

• Journal of the Korean Association of Geographic Information Studies
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• v.7 no.3
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• pp.1-12
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• 2004

Nowadays, a satellite image is widely utilized in identifying and predicting urban spatial growth. It provides essential informations on horizontal expansion of urbanized areas. However, its usefulness becomes very limited in analyzing density of urban development. On the contrary, zonal data, typically census data, provides various density information such as population, number of houses, floor information within a given zone. The problem of the zonal data in analyzing urban growth is that the size of the zone is too big. The minimum administration unit, Dong, is too big to match the satellite images. This study tries to derive synergy effects by matching the merits of the two information sources-- image data and zonal data. For this purpose, basic statistical unit (census block size) is utilized as a zonal unit. By comparing the image and zonal data of 1985 and 2000 of Daegu metropolitan area, this study concludes that urban growth pattern is better explained when the two types of data are properly used.

• Korean Journal of Human Ecology
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• v.1 no.2
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• pp.100-112
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• 1998

The purpose of this study is to investigate the torso patterns by analyzing sensory evaluations. The anthropometric measurements for female college students were obtained between March and October in 1998, and a total of 197 anthropomatric data was used for the somatotype analysis. The appearance and fit of three kinds of torso patterns(ESMOD, FIT, and Muller & sohn) were evaluated by expert panel and the subjects. The results of the anthropometric measurements and sensory evaluations are as follows; The mean height of the anthropometric data for 197 students is 158.98cm. The largest proportion of the three somatotypes(H, M and A type) is big hip type(A type) consisting of 47.7% of all the respondents. The result of the torso pattern evaluations by expert panel indicates that the ESMOD pattern obtains the highest rating in general acceptability. A significant difference(p<.05) in the responses to two questions, the placement of the waist dart, and the gapping & creasing at back hip area was found. The ESMOD and Muller & sohn patterns are given the highest rating in the general acceptability. The result of the evaluation was obtained by the subjects. (Korean J. Human Ecology 1(2):100∼112, 1998)

• Communications for Statistical Applications and Methods
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• v.27 no.6
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• pp.589-602
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• 2020

The development of smart grids has enabled the easy collection of a large amount of power data. There are some common patterns that make it useful to cluster power consumption patterns when analyzing s power big data. In this paper, clustering analysis is based on distance functions for time series and clustering algorithms to discover patterns for power consumption data. In clustering, we use 10 distance measures to find the clusters that consider the characteristics of time series data. A simulation study is done to compare the distance measures for clustering. Cluster validity measures are also calculated and compared such as error rate, similarity index, Dunn index and silhouette values. Real power consumption data are used for clustering, with five distance measures whose performances are better than others in the simulation.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.3
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• pp.155-164
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• 2016

For frequency pattern analysis of large databases, the new tree-based frequency pattern analysis algorithm which can compensate for the disadvantages of the Apriori method has been variously studied. In frequency pattern tree, the number of nodes is associated with memory allocation, but also affects memory resource consumption and processing speed of the growth. Therefore, reducing the number of nodes in the tree is very important in the frequency pattern mining. However, the absolute criteria which need to order the transaction items for construction frequency pattern tree has lowered the compression ratio of the tree nodes. But most of the frequency based tree construction methods adapted the absolute criteria. FP-tree is typically frequency pattern tree structure which is an extended prefix-tree structure for storing compressed frequent crucial information about frequent patterns. For construction the tree, all the frequent items in different transactions are sorted according to the absolute criteria, frequency descending order. CanTree also need to absolute criteria, canonical order, to construct the tree. In this paper, we proposed a novel frequency pattern tree construction method that does not use the absolute criteria, IRFP-tree algorithm. IRFP-tree(Intersection Rule based FP-tree). IRFP-tree is constituted with the new paradigm of the intersection rule without the use of the absolute criteria. It increased the compression ratio of the tree nodes, and reduced the tree construction time. Our method has the additional advantage that it provides incremental mining. The reported test result demonstrate the applicability and effectiveness of the proposed approach.

• Journal of the Korea Society of Computer and Information
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• v.24 no.10
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• pp.159-165
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• 2019

About 58% of fires are electric fires. In this study, we analyzed the factors of fire caused by electricity and studied the system that can prevent fire in advance. In order to prevent disasters, basically, various electrical IoT sensors are needed to detect fire signs. Each of these sensors continuously receives a lot of situation information and sends it to the main system. The collected big data continuously checks whether the disaster is over the threshold that can cause disaster through pattern analysis, and can check whether there is any problem by comparing the data. In the event of a threshold, alarms are signaled and problems are reported. This prevents fire by preventing electrical problems such as overcurrent and leakage current.