• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.5
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• pp.79-85
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• 2009

A sink node and its neighbor nodes spend more energy than other nodes since a stationary sink node collects data from wireless sensor networks(WSNs). For larger WSNs, the unbalanced energy of nodes causes the operation of WSNs to stop rapidly. This paper proposes a data gathering method by adapting the mobile sink to prolong the life time of large WSNs. After partitioning a network into several clusters, a mobile sink visits each cluster and collects data from it. An efficient algorithm is proposed to improve the energy efficiency by delivering the message from the mobile sink to the cluster head as well as to reduce the data gathering delay, which is the disadvantage of the mobile sink. Also, The algorithm is analyzed for the energy consumption and the data gathering delay. The validity of the ananlysis result is confirmed by the simulation.

• Journal of Fashion Business
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• v.15 no.6
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• pp.148-162
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• 2011

The purpose of this study is to analyze lower body types of women and provide information of body improvement of Korean adult female clothing product to ready-made clothes companies. As for the method of this study, it was conducted to measure the parts of the lower body of adult women at the age from 19 to 24 years, to analyze their characteristics and to categorize body types. For study, it was measured 150 female women in Seoul. Data was analyzed by used SPSS/WIN 19.0 Program. The results of this study are as follows. The means of the subjects in their early 20s are 159.8cm in height, 67.0cm in waist circumference, 91.6cm in hip and 52.0kg in weight. As a result of comparison with the $5^{th}$ Korean's human body size on measurement data, 20 items out of 33 items showed significant difference. Factor analysis was executed for 66 body measure and calculation items to draw the body construction factors of the women's lower body in their early 20s and principal component analysis was performed by orthogonal varimax rotation to clarify the measurement of factors and to derive explanatory factors. As result of Cluster analysis, body types' characteristics divide into 3 types. Type1 has tall and fat body form, type2 has shortest and curvy body form and type3 has average height and the most skinny body form.

• Journal of Korean Society of Forest Science
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• v.99 no.4
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• pp.590-596
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• 2010

To investigate and to compare the structure of Picea jezoensis forests at Chunwangbong area in the Jirisan National Park, 33 plots(400) were set up by a random sampling method. Dead individuals of Picea jezoensis trees were 15.6%, these were observed mainly in the upper-layer trees. A few seedlings of Picea jezoensis were found in this investigation area. This result indicates that Picea jezoensis might be gradually decreased in the future. Picea jezoensis stands were classified into two major groups by cluster analysis. There were strong positive correlations between Syringa reticulata and Acer pseudosieboldianum, Tripterygium regelii, Quercus serrata; Betula ermani and Lonicera maackii; Euonymus macropterus and Acer ukurunduense; Acer pseudosieboldianum and Tripterygium regelii, and relatively weak negative correlations were showed between Picea jezoensis and Abies koreana; Betula ermani and Acer ukurunduense; Acer pseudosieboldianum and Tripterygium regelii. Species diversity index(H') of investigated groups ranged from 1.0000 to 1.3010.

• Journal of the Korean Data and Information Science Society
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• v.20 no.3
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• pp.551-562
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• 2009

In this paper, I would present a using method for The Fishing Operation Information(FOI) of National Federation of Fisheries Cooperatives(NFFC) through the availabilities analysis and put out the similarities by the section of the sea through classifying characteristics of fishing patterns by their locations. As a result, although the catch of FOI is nothing more than 33% level to National Fishery Production Statistics(NFPS), FOI data is useful in understanding the patterns of fishing operation by the location because both patterns and correlation were very similar in the usability analysis, comparing the FOI data with NFPS. So I classified optimal clusters for catch, the number of fishing days and the number of fishing vessels through 2 step cluster analysis by the big marine zone and divided fishing patterns.

• Journal of the Korean Society of Clothing and Textiles
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• v.32 no.2
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• pp.284-293
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• 2008

The purpose of this study was to identify men's beauty service markets based on socio-cultural appearance attitude and to compare their satisfaction and intention to revisit beauty service. The study was done by survey method. Data of three hundred men aged from 20's to 40's were collected by on-line survey. Descriptive analyses, factor analyses, cluster analyses, Duncan tests, multiple regressions, and path analyses were applied. The results are as follows: First, five factors were found for men's socio-cultural attitude for their appearance. They were high involvement in appearance, social appearance, appearance satisfaction, appearance comparison and low involvement in appearance. Second, cluster analysis based on socio-cultural attitude produced three customer groups such as high involvement, social concern & satisfaction, and low involvement. Third, customer groups showed significant differences in some demographics and some items of service dimensions, which resulted in significant differences in satisfaction, and intention to revisit beauty shop services. A high involvement group was composed of young and unmarried men with more frequent visit to beauty shop service. In general, both the high involvement and the social concern & satisfaction groups showed higher evaluations than the low concern group in some of service items, level of satisfaction, and intention to revisit. In conclusion, attitude on their appearance could be useful factors in segmenting men's beauty service market. Levels and types of beauty shop service should be differentiated among consumer markets.

• Journal of the Korean Society of Clothing and Textiles
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• v.35 no.12
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• pp.1454-1465
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• 2011

Menswear body types are often labeled on garments (to indicate how the garments are designed to fit) with indicators of a size category such as regular, portly, and stout, athletic, or big and tall. A drop (relationships between the chest and waist girths) is related to the fit of a tailored suit. However, current standards are not designed for various drops or body types. There is not enough information of categorizing men's body shapes for the apparel sizing systems. In this article, a set of men's data from SizeUSA sizing survey was analyzed to investigate men's body shapes and drops. Factor analysis and a cluster analysis method were used to categorize men's body shapes. In the results, twenty-five variables were selected through the factor analysis and found four factors: girth factor, height factor, torso girth factor, and slope degree factor. According to the factor and cluster analysis, various body shapes were found: Slim Shape (SS - tall ectomorphy), Heavy Shape (HS - athletic, big & tall, endomorphy and mesomorphy), Slant Inverted Triangle Shape (SITS - regular, slight ectomorphy and slight mesomorphy weight range from normal to slightly overweight), Short Round Top Shape (SRTS - portly and stout, endomorphy). Body shapes were related to fitting categories. SS and HS were related to big & tall fitting category. SITS was related to regular. SRTS was related to portly and stout. Shape 1 (31%) and Shape 2 (26%) were related to current big & tall category. Shape 3 (34%) were related to regular. Shape 4 (9%) were in portly and stout category. ASTM D 6240 standard was the only available standard that presented a regular fitting category. Various drops were found within a same chest size group; however, this study revealed great variances of drops by body shape.

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.109-112
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• 2008

The purpose of this study is to find out the characteristics of disasters caused by typhoons passing through the sea area around the Korean Peninsula. It analyzed two cases, that is, in WEST and EAST cases. These include the typhoons passing through the Yellow Sea, west of the Peninsula and East Sea, east of the Peninsula without landing on the Peninsula. FCM (Fuzzy Clustering Method) analysis was performed on typhoons affecting the Korean Peninsula from 1951 to 2006. The analysis shows that WEST case's cluster has the curved track of NE-S, and EAST case's cluster has the straight track of NE-SW. Typhoons that pass through the Yellow Sea have little change in frequency and the weak intensity. On the other hand, the frequency and the intensity of typhoons passing through the East Sea show the increasing trend. The characteristic of disasters by typhoons affecting the Korean Peninsula from 1973 to 2006 appears differently for each case: EAST cases caused significant damage in flooding, while WEST cases did damage in houses, ships, roads, and bridges. Rainfall amount and maximum wind speed data are analyzed in order to understand the impact of the typhoons, and the result indicates that the WEST cases are influenced by the wind, and East cases by precipitation. The result of this study indicates that the characteristic of disasters is distinctive according to the Typhoon's track. If applied to establish the disaster prevention plan, this result could make a contribution to the damage reduction.

• Journal of KIISE
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• v.43 no.1
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• pp.61-70
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• 2016

In recent years, there has been a need for techniques for large-scale ontology inference in order to infer new knowledge from existing knowledge at a high speed, and for a diversity of semantic services. With the recent advances in distributed computing, developments of ontology inference engines have mostly been studied based on Hadoop or Spark frameworks on large clusters. Parallel programming techniques using GPGPU, which utilizes many cores when compared with CPU, is also used for ontology inference. In this paper, by combining the advantages of both techniques, we propose a new method for reasoning large RDFS ontology data using a Spark in-memory framework and inferencing distributed data at a high speed using GPGPU. Using GPGPU, ontology reasoning over high-capacity data can be performed as a low cost with higher efficiency over conventional inference methods. In addition, we show that GPGPU can reduce the data workload on each node through the Spark cluster. In order to evaluate our approach, we used LUBM ranging from 10 to 120. Our experimental results showed that our proposed reasoning engine performs 7 times faster than a conventional approach which uses a Spark in-memory inference engine.

• Journal of the Korean Geographical Society
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• v.39 no.2
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• pp.283-296
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• 2004

More than 0.5 percent of land in Korea is used for cemetery and the rate is growing in spite of the increase in cremation these days. The systematic management of tombs may be possible through the ‘Feature Extraction’ method which is applied to the high-resolution satellite imagery. For this reason, this research focused on finding out the radiometric characteristics of tombs and the classification of them. An IKONOS image of northwest areas of Seoul with 8km x 10km dimension was analyzed. After sampling 24 tombs in the study area, the statistical radiometric characteristics of tombs are analyzed. And tombs were classified based on the criteria such as landscape, NDVI, and cluster analysis. In addition, it was investigated if the aspect or slope of the terrain influenced to the classification of tombs. As a result of this research, authors find that there is similarity between the classification tv NDVI and the classification through cluster analysis. And aspect or slope didn't have much influence on the classification of tombs.

• International Journal of Highway Engineering
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• v.15 no.5
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• pp.91-99
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• 2013

PURPOSES : This study aims at proposing the methodology for benefit evaluations in pavement maintenance methods and timings using KoPMS(Korean Pavement Management System) software which was developed for efficient pavement management. METHODS : This study classified pavement sections into 4 clusters considering AADT(Annual Average Daily Traffic) and ESAL(Equivalent Single-Axle Load) using cluster analysis and used the deterioration models in each cluster. Increased user costs due to pavement deterioration as time goes by and agent costs for maintenance were estimated. Based on deterioration model and KoPMS software, Methodology for benefit evaluation was proposed in pavement maintenance methods and with/without implementation using real pavement section data. RESULTS : This study verified that considering agent costs only would be constrained to decide pavement maintenance methods and timings, and ascertained that decision making with agent and user costs would be effective. In addition, this study revealed that pavement maintenance methods and timings can be affected by AADT and ESAL and frequent pavement maintenances can be more efficient for benefits in pavement sections with more AADT and ESAL. Also this study found that user costs would be more affected to decision making than agent costs. Moreover, Delay of conducting pavement maintenance caused increased vehicle operating costs and environmental costs because of poor conditions of pavements. CONCLUSIONS : This study proposed LCCA and benefit estimation methodology of pavement with considering agent and user costs. The results of this study can be used for baseline data of efficient pavement asset management.