• Bulletin of the Korean Space Science Society
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• 2009.10a
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• pp.29.4-30
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• 2009

Extra-tidal feature of the globular clusters such as tidal tails and halos can be a crucial evidence of the merging scenario of the Galaxy formation in the dynamical point of view. To search for such an extra-tidal feature of globular clusters located in the Galactic bulge(RGC<3kpc), we obtained wide-field near-infrared JHKs images of 6 metal-poor ([Fe/H]<-1.0) clusters and 3 metal-rich ([Fe/H]>-1.0) clusters. Observations were carried out using IRSF 1.4m telescope and SIRIUS near-infrared camera, during 2006~2007. The obtained images have a total maximum field-of-view of ~ $21'\times 21'$. To select clusters' member stars and minimize the field star contaminations, we applied CMD masking algorithm. Smoothed surface density contour maps with selected stars for each cluster show overdensity features around the tidal radius and beyond. Also, radial surface density profiles within the tidal radius of the clusters show an overdensity feature as a change of slope of the radial profile. The results add further observational constraints of the formation of the Galactic bulge.

• The Bulletin of The Korean Astronomical Society
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• v.39 no.1
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• pp.83.1-83.1
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• 2014

Open clusters consisting of a co-spatial and coeval population with a similar chemical composition are a superb astrophysical test bed in both stellar and galactic astronomy. We introduce not only several scientific issues relating to these objects but also comprehensive studies of the two young open clusters Westerlund 1 and IC 1848 formed in extremely different star-forming conditions. Westerlund 1 is known as the most massive starburst cluster in the Galaxy. Located in the Scutum-Centaurus spiral arm, the cluster is relatively close to the Galactic Center. The apparent surface density is very high. On the other hand, IC 1848 is a core cluster within the large-scale star-forming region W5 lying in the Perseus arm. Unlike Westerlund 1, IC 1848 with a putatively low metallicity exhibits a low surface density. We present the fundamental parameters of those young clusters, such as reddening, distance, and age, obtained from the broadband photometric analysis. The stellar initial mass function (IMF) of the clusters is used to investigate the effects of the different star-forming conditions on the star formation activity. With the results of previous studies for several young open clusters, our preliminary results support a possibility that star formation activity may be affected by the environmental factors or the initial condition of natal clouds. In addition, we shortly discuss the age scale and spread of pre-main sequence stars to understand the formation processes of star clusters.

• Journal of The Korean Astronomical Society
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• v.36 no.3
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• pp.189-212
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• 2003

I review the current status of understanding when, how long, and how giant elliptical galaxies formed, focusing on the globular clusters. Several observational evidences show that massive elliptical galaxies formed at z > 2 (> 10 Gyr ago). Giant elliptical galaxies show mostly a bimodal color distribution of globular clusters, indicating a factor of $\approx$ 20 metallicity difference between the two peaks. The red globular clusters (RGCs) are closely related with the stellar halo in color and spatial distribution, while the blue globular clusters (BGCs) are not. The ratio of the number of the RGCs and that of the BGCs varies depending on galaxies. It is concluded that the BGCs might have formed 12-13 Gyr ago, while the RGCs and giant elliptical galaxies might have formed similarly 10-11 Gyr ago. It remains now to explain the existence of a gap between the RGC formation epoch and the BGC formation epoch, and the rapid metallicity increase during the gap (${\Delta}t{\approx}$ 2 Gyr). If hierarchical merging can form a significant number of giant elliptical galaxies > 10 Gyr ago, several observational constraints from stars and globular clusters in elliptical galaxies can be explained.

• The Bulletin of The Korean Astronomical Society
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• v.43 no.2
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• pp.59.4-60
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• 2018

Ultra-diffuse galaxies (UDGs) are an unusual galaxy population. They are ghostlike galaxies with fainter surface brightness than normal dwarf galaxies, but they are as large as MW-like galaxies. The key question on UDGs is whether they are 'failed' giant galaxies or 'extended' dwarf galaxies. To answer this question, we study UDGs in massive galaxy clusters. We find an amount of UDGs in deep HST images of three Hubble Frontier Fields clusters, Abell 2744 (z=0.308), Abell S1063 (z=0.347), and Abell 370 (z=0.374). These clusters are the farthest and most massive galaxy clusters in which UDGs have been discovered until now. The color-magnitude relations show that most UDGs have old stellar population with red colors, while a few of them show bluer colors implying the existence of young stars. The stellar masses of UDGs show that they have less massive stellar components than the bright red sequence galaxies. The radial number density profiles of UDGs exhibit a drop in the central region of clusters, suggesting some of them were disrupted by strong gravitational potential. Their spatial distributions are not homogeneous, which implies UDGs are not virialized enough in the clusters. With virial masses of UDGs estimated from the fundamental manifold, most UDGs have M_200 = 10^10 - 10^11 M_Sun indicating that they are dwarf galaxies. However, a few of UDGs more massive than 10^11 M_Sun indicate that they are close to failed giant galaxies.

• Journal of the Korean Geographical Society
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• v.45 no.4
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• pp.502-520
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• 2010

The main objective of the paper is to develop a GIS-based method for delineating spatial clusters. Major tasks are: (i) to devise a sustainable algorithm with reference to various methods developed in the fields of geographic boundary analysis and cluster detection; (ii) to develop a GIS-based program to implement the algorithm. The main results are as follows. First, it is recognized that the AMOEBA technique utilizing LISA is the best candidate. Second, a modified version of the AMOEBA technique is proposed and implemented in a GIS environment. Third, the validity and usefulness of the modified AMOEBA algorithm is assured by its applications to test and real data sets.

• The Journal of the Korea Contents Association
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• v.21 no.4
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• pp.434-446
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• 2021

Recently, there has been a growing interest in the fourth industrial revolution, expected to have a significant impact on society. However, there are only a few studies on spatial distribution and location of the fourth industry. This study tried to classify the spatial distribution of the fourth industry by using LQ, a non-geographical method, and Getis-Ord's Gi^*, a geographical method. The results of the analysis are as follows. First, there are the specialized areas of the fourth industry in the non-Seoul metropolitan area as well as the Seoul metropolitan area. Second, industrial clusters and neighborhood areas of the fourth industry were located mostly in the Seoul metropolitan area. Third, industrial clusters were concentrated on the southern part of Gyeonggi Province and Seoul, and there are no industrial clusters in the northern part of the Seoul metropolitan area and the nature conservation area. This paper shows that the cluster area of the fourth industry is concentrated in the Seoul metropolitan area. Therefore, policies for the 4th industry are needed to solve this unbalanced spatial distribution of the fourth industry.

• ETRI Journal
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• v.43 no.1
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• pp.17-30
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• 2021

At present, multiple input multiple output radars offer accurate target detection and better target parameter estimation with higher resolution in high-speed wireless communication systems. This study focuses primarily on power allocation to improve the performance of radars owing to the sparsity of targets in the spatial velocity domain. First, the radars are clustered using the kernel fuzzy C-means algorithm. Next, cooperative and noncooperative clusters are extracted based on the distance measured using the kernel fuzzy C-means algorithm. The power is allocated to cooperative clusters using the Pareto optimality particle swarm optimization algorithm. In addition, the Nash equilibrium particle swarm optimization algorithm is used for allocating power in the noncooperative clusters. The process of allocating power to cooperative and noncooperative clusters reduces the overall transmission power of the radars. In the experimental section, the proposed method obtained the power consumption of 0.014 to 0.0119 at K = 2, M = 3 and K = 2, M = 3, which is better compared to the existing methodologies-generalized Nash game and cooperative and noncooperative game theory.

• Journal of the Economic Geographical Society of Korea
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• v.6 no.1
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• pp.45-60
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• 2003

As the process of economic globalization deepens market uncertainty and severe competition, modern companies are tend to rely on non-market, socio-economic mechanisms such as trust, collaboration, and interdependence, They are being more influenced by cultural economic mechanisms like networks, embeddedness, and placeness rather than explicit cost-reductions. This paper analyzes the characteristics of industrial clusters, the formation of social capital, and the process of institutionalization by comparing two distinctive types of clusters, say Teheran and East-Gate Valleys in Seoul, Korea. The one is mainly consisted of IT industries with increasing vertical integration supported by venture capitals and favorable business infrastructures. The other cluster has long been a traditional CBD frame of Seoul and has transformed to the most dynamic and productive area, characterized by one-stop 'R&D-production-distribution-consumption-after sales services'. The study of the developmental trajectory and key characteristics for these kinds of clusters can give us insight for the cluster theory. This paper firstly reviews the similarities and differences between the social capital in general and that of industrial clusters. It then profiles the growth of the two clusters over the past decade, and compares the current spatial and business structure of the two clusters, focusing on transactions costs, the creation and flow of information, and the local institutions. The paper concludes with some comments about the prospects and perils of the two types industrial clusters of Seoul.

• Journal of Environmental Science International
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• v.27 no.5
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• pp.309-317
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• 2018

In this study, a laser sheet technique and PLIF (Planar laser-induced fluorescence) are applied to a laboratory-scale pulverized coal burner of the open type, and the spatial relationship of the pulverized coal particle zone and the combustion reaction zone is examined by simultaneous measurement of Mie scattering and OH-LIF images. It is found that this technique can be used to investigate the spatial relationship of the combustion reaction zone and pulverized-coal particles in turbulent pulverized-coal flames without disturbing the combustion reaction field. In the upstream region, the combustion reaction occurs only in the periphery of the clusters where high-temperature burned gas of the methane pilot flame is entrained and oxygen supply is sufficient. In the downstream region, however, combustion reaction can be seen also within clusters of pulverized-coal particles, since the temperature of pulverized-coal particles rises, and the mixing with emitted volatile matter and ambient air is promoted.

• The KIPS Transactions:PartD
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• v.13D no.5 s.108
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• pp.633-640
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• 2006

Spatial clustering, which groups similar objects based on their distance, connectivity, or their relative density in space, is an important component of spatial data mining. Density-based and grid-based clustering are two main clustering approaches. The former is famous for its capability of discovering clusters of various shapes and eliminating noises, while the latter is well known for its high speed. Clustering large data sets has always been a serious challenge for clustering algorithms, because huge data set would make the clustering process extremely costly. In this paper, we propose an enhanced Density-Grid based Clustering algorithm for Large spatial database by setting a default number of intervals and removing the outliers effectively with the help of a proper measurement to identify areas of high density in the input data space. We use a density threshold DT to recognize dense cells before neighbor dense cells are combined to form clusters. When proposed algorithm is performed on large dataset, a proper granularity of each dimension in data space and a density threshold for recognizing dense areas can improve the performance of this algorithm. We combine grid-based and density-based methods together to not only increase the efficiency but also find clusters with arbitrary shape. Synthetic datasets are used for experimental evaluation which shows that proposed method has high performance and accuracy in the experiments.