• The Bulletin of The Korean Astronomical Society
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• v.35 no.2
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• pp.42.1-42.1
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• 2010

We present ultraviolet (UV) photometric properties of dwarf galaxies in Fornax cluster and Ursa Major group in comparison with Virgo cluster using GALEX data. We construct UV color-magnitude relations (CMRs) of dwarf galaxies matching with available optical photometry and SDSS data. Majority of dwarf galaxies in Fornax cluster show sequence in UV CMRs consistent with that of dwarf elliptical (dEs) in Virgo cluster indicating similar age and metallicity properties of dEs in two clusters. The dS0 sequence in Fornax cluster is not distinct as much as that in Virgo cluster. Dwarf galaxies in outer region of the Fornax cluster show more bluer UV colors with a wide scatter in CMRs, which indicates recent star formation activity. We show that the UV colors of dwarf galaxies are related with the distribution and strength of the X-ray emission in the cluster. In contrast to the Fornax cluster, most dwarf galaxies in Ursa Major group are located in the blue cloud showing recent or on-going star formation, and few galaxies show characteristics of dEs. We discuss relationship between UV properties of dwarf galaxies and different environment of cluster.

• Journal of Environmental Science International
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• v.18 no.8
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• pp.899-910
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• 2009

We classified wind sectors according to the wind features in South Korea. In order to get the information of wind speed and wind direction, we used and improved on the atmospheric numerical model. We made use of detailed topographical data such as terrain height data of an interval of 3 seconds and landuse data produced at ministry of environment, Republic of Korea. The result of simulated wind field was improved. We carried out the cluster analysis to classify the wind sectors using the K-means clustering. South Korea was classified as 8 wind sectors to the annual wind field.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.6
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• pp.619-625
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• 2009

FastSLAM which uses the Rao-Blackwellized particle filter is one of the famous solutions to SLAM (Simultaneous Localization and Mapping) problem that estimates concurrently a robot's pose and surrounding environment. However, the particle depletion problem arises from the loss of the particle diversity in the resampling process of FastSLAM. Then, the performance of FastSLAM degenerates over the time. In this work, DIR (Density Information-based Resampling) technique is proposed to solve the particle depletion problem. First, the cluster is constructed based on the density of each particle, and the density of each cluster is computed. After that, the number of particles to be reserved in each cluster is determined using a linear method based on the distance between the highest density cluster and each cluster. Finally, the resampling process is performed by rejecting the particles which are not selected to be reserved in each cluster. The performance of the DIR proposed to solve the particle depletion problem in FastSLAM was verified in computer simulations, which significantly reduced both the RMS position error and the feature error.

• The KIPS Transactions:PartA
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• v.10A no.4
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• pp.331-338
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• 2003

Cluster is the cost-effective parallel processing environment, and consists of the off-the-shelf computers connected by the computer net works. The characteristics of cluster are the node heterogeneity, the variety of node load, and the variety of network load. Because these characteristics influence the performance of parallel program executions, the load sharing for cluster is important, and by using the proper load sharing strategy, we can reduce the execution time of parallel programs. In this paper, we propose modified GSS algorithm, αGSS. In the proposed load sharing algorithms α GSS, the size of tasks are decided using the BogoMIPS of node. From the result of out experiments, we conclude that the proposed αGSS algorithm is effective in the heterogeneous cluster.

• Asian Journal of Business Environment
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• v.7 no.1
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• pp.25-29
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• 2017

Purpose - In this paper, we categorize and segment the 28 national universities in South Korea and measure the degree of dissimilarity (or similarity) between pairs of ones by using dissimilarity distance matrix and cluster analysis, respectively, based on the seven quantitative evaluation of educational conditions (percentage of small-scale courses, percentage of lecture by the faculty, collection of books per student, material purchase per student, percentage of building capacity, percentage of real estate capacity and rate of accommodation) in 2015. In addition, multidimensional scaling (MDS) techniques can obtain visual representation for exploring patterns of proximities among 28 national universities based on seven attributes of educational conditions. Research design, data, and methodology - This work is carried out by the 2015 Announcement of University Information, which is provided by Ministry of Education in South Korea and utilized by multivariate analyses with CLUSTER, PROXIMITIES and ALSCAL modules in IBM SPSS 23.0. Results - We make certain that 28 national universities can be categorized into five clusters which have similar traits by applying two-stage cluster analysis. MDS is utilized to perform positioning of grouped places of cluster and 28 national universities joining every cluster. Conclusions - Both types and traits of each national university can be relatively assessed and practically utilized for each university competitiveness based on underlying results.

• Journal of Environmental Impact Assessment
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• v.13 no.3
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• pp.137-151
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• 2004

Many of today's environmental problems are regional in scope and their effects overlap and interact. The purpose of this paper is to developed a simple method for an integrated assessment of environmental conditions across the Mid-Nakdong River Region, by combining data on land use, impervious cover, roads, streams, riparian areas, forest patches, population, pollutant loadings, soil erosion and topography. A cluster analysis was used to identify groups of sub-watersheds with similar environmental characteristics. The mean value for each group was used to find watershed that may be more vulnerable to future environmental degradation. Watersheds in cluster I and II had high amount of forest, but the amount of riparian vegetation was low. Watersheds in cluster III, which located in the middle Geumho River and the main course of Nakdong River, had a greater proportion of their agriculture, a greater proportion of agriculture on steep slopes, and less forest adjacent to streams. Watersheds in cluster IV and V were in the most urbanized areas of the region. The principal adverse impacts for watersheds in this group were high scores for urban area, impervious cover, pollutant loadings, population density, forest fragmentation, and low amounts of forest and riparian forest cover. Notwithstanding the exploratory nature of cluster analysis, it appears to be a useful tool for grouping watersheds with similar environmental characteristics.

• Journal of Digital Convergence
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• v.14 no.9
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• pp.309-315
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• 2016

The node mobility in the wireless mobile network environment increases the energy consumption. This paper proposes a CNMA (cluster-based node management algorithm) to reduce the energy consumption caused by node mobility, and to prolong the life cycle for cluster member nodes. The proposed CNMA traces the mobility for nodes between cluster header and member, and it analyses the energy capacity as monitoring periodically their relationship. So, it makes a division and merges by analysing the state transition for nodes. This paper is to reduce the energy consumption due to the node mobility. The simulation results show that the proposed CNMA can efficiently control the energy consumption caused by mobility, and it can improve the energy cycle.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.44 no.4 s.316
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• pp.21-27
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• 2007

Recently cluster system built from personal computers and network devices are easily and economically constructed. Rapid technological change discloses new processors on the market yielding cluster systems heterogeneity. A parallel system in heterogeneous environment needs work managers for utilizing the full power of the heterogeneous cluster system. In this paper, we compare MPI and Cilk in a heterogeneous cluster system in terms of performance and code complexity. Experimental results show that Cilk is better than MPI with small sizes of data transfers while MPI outperforms Cilk with big sizes of data transfers. Also, We find that Cilk requires less programming efforts to write a parallel program.

• Human Ecology Research
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• v.56 no.6
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• pp.603-617
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• 2018

This study analyzed research trends in the field of Practical Arts (Technology & Home Economics) education. From 958 articles published between 2010 and 2018 in the Journal of Korean Practical Arts Education (JKPAE), Journal of Korean Home Economics Education Association (JHEEA), and Korean Journal of Technology Education Association (KJTEA), 958 keywords were extracted and analyzed using NetMiner 4. When the general network structure was analyzed, keywords such as practical arts education, curriculum, textbook, home economics education, and students were high in the degree centrality and closeness centrality, and textbook, practical arts education, curriculum, student, home economics education, and invention were high in the node betweenness centrality. The cluster analysis showed that a four-cluster solution was most appropriate: cluster 1, technology and experiential learning activities; cluster 2, curriculum studies and practical problem; cluster 3, relationships; and cluster 4, creativity and character education. The three journals showed differences in the knowledge network structure: The topics of JKPAE and JKHEEA focused on general content knowledge and curriculum, while the topics of KJTEA were spread across invention and creativity education, and curriculum studies.

• Health Policy and Management
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• v.33 no.2
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• pp.118-128
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• 2023

Background: Personal socio-economic abilities are crucial as it affects health inequalities. These multidimensional inequalities across the regions have been structured and fixed. This study aimed to analyze health vulnerabilities by regional cluster and identify regional health disparities of self-rated health, using nationally representative cross-sectional data. Methods: This study used personal and regional data. Data from the Community Health Survey 2021 were analyzed. K-means cluster analysis was applied to 250 si-gun-gu using administrative regional data. The clusters were based on three areas: physical environment, health-related behaviors and biological factors, and the psychosocial environment through the conceptual framework for action on the social determinants of health. And binary logistic regression analyses were conducted to examine the differences in self-rated health status by the regional clusters, controlling human biology, environment, lifestyle, and healthcare organization factors. Results: The most vulnerable group was group 3, the moderate vulnerable group was group 1, and the least vulnerable group was group 2. The group 2 was more likely to have high self-rated health status than the moderate vulnerable group (odds ratio [OR], 1.023; p<0.001). And the group 3 showed low self-rated health status than the moderate vulnerable group (OR, 0.775; p<0.001). However, the moderate vulnerable group had significantly higher self-rated health status than the most vulnerable group (group 2: OR, 1.023; p<0.001; group 3: OR, 0.775; p<0.001). Conclusion: These results demonstrate that community members' health status is influenced by regional determinants of health and individual levels. And these contribute to understanding the importance of specific and differentiated interventions like locally tailored support programs considering both individual and regional health determinants.