• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.5
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• pp.517-524
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• 2004

The fuzzy set theory has been wide used in clustering of machine learning with data mining since fuzzy theory has been introduced in 1960s. In particular, fuzzy C-means algorithm is a popular fuzzy clustering algorithm up to date. An element is assigned to any cluster with each membership value using fuzzy C-means algorithm. This algorithm is affected from the location of initial cluster center and the proper cluster size like a general clustering algorithm as K-means algorithm. This setting up for initial clustering is subjective. So, we get improper results according to circumstances. In this paper, we propose a cluster merging using enhanced density based fuzzy C-means clustering algorithm for solving this problem. Our algorithm determines initial cluster size and center using the properties of training data. Proposed algorithm uses grid for deciding initial cluster center and size. For experiments, objective machine learning data are used for performance comparison between our algorithm and others.

• Journal of the Economic Geographical Society of Korea
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• v.17 no.4
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• pp.688-701
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• 2014

This article is focused on the agglomeration and decline factors of the footwear industries in Busan metropolitan area from the industrial cluster point of perspective. For the research, 'the components and network of industrial cluster model' are presented which is restructured of M. Porter's cluster model. Moreover, this research have examined the agglomeration and decline process of the footwear industries in Busan area and conducted a survey targeting footwear enterprises in Busan area. In the late 1980's, the footwear industries in Busan area formed the largest footwear industrial cluster in the world. However, the industrial cluster started to decline from early 1990's and now it is reduced in to 1/10 size of the past. The growth factors of Busan footwear industrial cluster include cheap and plentiful labours, penetration of OEM production, entrepreneur spirit, human resources network, government's support and so on. Moreover, the agglomeration of relative companies also created high competitiveness in this cluster. The decay factors are pointed out sudden rise of labour cost, shortage of factory site, rise of land price, alteration of government policy, international relocation of footwear production and growth of overseas industrial cluster. Busan footwear industrial cluster nowadays has declined in its size, but it is the only footwear industrial cluster in Korea.

• Communications of the Korean Mathematical Society
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• v.20 no.4
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• pp.813-826
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• 2005

Regarding all particles at a fixed site as a cluster, the size of the largest cluster under the zero range invariant measures is well studied by Jeon et al.[5] for the case of density one. Here, the density of the finite zero-range process is given by the ratio between the number m of particles and the number n of sites. In this paper, we study the lower density case, i.e., the case m = o(n). Especially, when m ~ $n^{\beta}$,0 < ${\beta}$ < 1, we show that there is an interesting cutoff point around $\beta$ = 1/2.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.17 no.4
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• pp.267-278
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• 2013

We consider zero range processes with density dependent jump rates g given by $g=g(n,k)=g_1(n)g_2(k/n)$ with $g_1(x)=x^{-\alpha}$ and $$g_2(x)=\{^{x^{-\alpha}\;if\;a&lt;x}_{Mx^{-\alpha}\;if\;x{\leq}a}$$. (0.1) In this case, with 1/2 < a < 1 and ${\alpha}$ > 0, we show that non-complete condensation occurs with maximum cluster size an. More precisely, for any ${\epsilon}$ > 0, there exists $M^*$ > 0 such that, for any 0 < M ${\leq}M^*$, the maximum cluster size is between (a - ${\epsilon}$)n and (a + ${\epsilon}$)n for large n. This provides a simple example of non-complete condensation under perturbation of rates which are deep in the range of perfect condensation (e.g. ${\alpha}$ >> 1) and supports the instability of the condensation transition.

• Transactions on Electrical and Electronic Materials
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• v.4 no.1
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• pp.1-6
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• 2003

We have studied the size confinement effect on the properties of melting-like transition of small icosahedral copper clusters using a classical molecular dynamics simulation based on a well fitted empirical potential. We investigated the caloric curves of icosahedron nanoclusters and the significant depression in the melting temperatures of the copper nanoclusters was compared with that of the bulk copper. A structural transitions from decahedral to icosahedral shapes were shown. As the cluster size increased, the melting temperature increased, and the latent heat increased but seem to be saturated. However, the specific heat was unrelated to the cluster size.

• Journal of Information Processing Systems
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• v.14 no.4
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• pp.926-940
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• 2018

In clustering-based approaches, cluster heads closer to the sink are usually burdened with much more relay traffic and thus, tend to die early. To address this problem, distance-aware clustering approaches, such as energy-efficient unequal clustering (EEUC), that adjust the cluster size according to the distance between the sink and each cluster head have been proposed. However, the network lifetime of such approaches is highly dependent on the distribution of the sensor nodes, because, in randomly distributed sensor networks, the approaches do not guarantee that the cluster energy consumption will be proportional to the cluster size. To address this problem, we propose a novel approach called CACD (Clustering Algorithm Considering node Distribution), which is not only distance-aware but also node density-aware approach. In CACD, clusters are allowed to have limited member nodes, which are determined by the distance between the sink and the cluster head. Simulation results show that CACD is 20%-50% more energy-efficient than previous work under various operational conditions considering the network lifetime.

• Korean Journal of Community Nutrition
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• v.5 no.1
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• pp.83-91
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• 2000

The aims of this study are to evaluate the quality of hospital food services and the evaluate the quality in selected hospitals trough the use of the questionnaires. A survey of 30 hospital food and nutrition service department was undertaken and detailed information was collected from each, including, surveys of 1, 016 patient. Statistical data analysis was completed using the SAS/win 6.11 package for descriptive analysis, t-test X$^2$-test ANOVA principal component analysis , and cluster analysis and cluster analysis. In the case of patient satisfaction with hospital food and food services, overall satisfaction scores of male and female were 3.54 and 3.45 showing higher levels than the average score(3.00) The aspect of the food and food service which received the lowest ratings by patients was 'meal rounding while dining'. After conduction of factor analysis of variables affecting the patients meal satisfaction 3 groups including the 'menu satisfaction factor', 'service satisfaction factor ' and 'nutrition management satisfaction factor ' were selected. 3 clusters were categorized by the 'service cluster' 'nutrition management cluster', 'men cluster', and 'menu nutrition service cluster' after conducting a cluster analysis with influencing variables affecting patients meal satisfaction. The overview results of patient satisfaction by cluster were : in the case of the service group, such factors as taste, portion size, dealing with complaints while dining meal rounding while dining should be managed with caution In case of the nutrition management group, such factors as taste, portion size, temperature of the food intake, and dependence on hospital food should be managed with care, In the case of the menu groups, such factors as punctuality of meal times, contaminated substances in meals and serving mistakes, cleanliness of dishes, kindness of the server meal rounding while dining should by particularly managed with importance.

• Journal of Veterinary Clinics
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• v.28 no.4
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• pp.422-426
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• 2011

For a national survey in which wide geographic region or an entire country is targeted, multi-stage sampling approach is widely used to overcome the problem of simple random sampling, to consider both herd- and animallevel factors associated with disease occurrence, and to adjust clustering effect of disease in the population in the calculation of sample size. The aim of this study was to establish sample size for estimating bovine tuberculosis (TB) in Korea using stratified two-stage sampling design. The sample size was determined by taking into account the possible clustering of TB-infected animals on individual herds to increase the reliability of survey results. In this study, the country was stratified into nine provinces (administrative unit) and herd, the primary sampling unit, was considered as a cluster. For all analyses, design effect of 2, between-cluster prevalence of 50% to yield maximum sample size, and mean herd size of 65 were assumed due to lack of information available. Using a two-stage sampling scheme, the number of cattle sampled per herd was 65 cattle, regardless of confidence level, prevalence, and mean herd size examined. Number of clusters to be sampled at a 95% level of confidence was estimated to be 296, 74, 33, 19, 12, and 9 for desired precision of 0.01, 0.02, 0.03, 0.04, 0.05, and 0.06, respectively. Therefore, the total sample size with a 95% confidence level was 172,872, 43,218, 19,224, 10,818, 6,930, and 4,806 for desired precision ranging from 0.01 to 0.06. The sample size was increased with desired precision and design effect. In a situation where the number of cattle sampled per herd is fixed ranging from 5 to 40 with a 5-head interval, total sample size with a 95% confidence level was estimated to be 6,480, 10,080, 13,770, 17,280, 20.925, 24,570, 28,350, and 31,680, respectively. The percent increase in total sample size resulting from the use of intra-cluster correlation coefficient of 0.3 was 22.2, 32.1, 36.3, 39.6, 41.9, 42.9, 42,2, and 44.3%, respectively in comparison to the use of coefficient of 0.2.

• Journal of Industrial Technology
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• v.21 no.B
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• pp.149-153
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• 2001

A study on the particle growth in $TEOS/O_2$ plasma was performed, and particle size and its distribution was measured by the electrical aerosol analyzer (EAA), light scattering particle size analyzer and the particle size was also determined by SEM. The effects of process variables such as total gas flow rate, reactor pressure, supplied power and initial reactant concentration on the particle growth were investigated. From the EAA results, the particle size distribution is divided into three groups of the cluster size and the small and large size particles. The particle size distribution measured by the light scattering particle size analyzer becomes bimodal, because the cluster size particles smaller than 20 nm in diameter cannot be detected by the light scattering particle size analyzer. The size of particles measured by the light scattering particle size analyzer is in good agreements with those by the SEM. Also we could understand that the particle formation is very sensitive to the changes of reactor pressure and reactant concentration. As the total gas flow rate increases, the particle size decreases because of the shorter residence time. As the reactor pressure, or the reactant concentration increases, the particle concentration increases and the particles grow more quickly by the faster coagulation between particles.

• Journal of The Korean Astronomical Society
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• v.37 no.5
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• pp.323-328
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• 2004

In this paper we review the observational results on Relic radio sources in clusters of galaxies. We discuss their observational properties, structures and radio spectra. We will show that Relics can be divided according to their size, morphology, and location in the galaxy cluster. These differences could be related to physical properties of Relic sources. The comparison with cluster conditions suggests that Relics could be related to shock waves originated by cluster mergers.