• 천문학회보
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• 제46권1호
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• pp.52.3-53
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• 2021

It is yet to be understood what controls the star formation activity in high-redshift galaxy clusters. One recently proposed mechanism is that the star formation activity in galaxy clusters are fed by gas and galaxies in large-scale structures surrounding them, which we call as "web feeding model". Using galaxies in the COSMOS2015 catalog, with mass completeness at log(M/M_⦿)≥9.54 and reliable photometric redshift data (σ_Δz/(1+z) ≲ 0.01), we study the star formation activities of galaxy clusters and their surrounding environment to test the web feeding model. We first identify the overdense regions with number density exceeding the 4σ-level from photometric redshift data as galaxy clusters, and we find that they are well matched with clusters identified in the X-ray extended source catalog. Furthermore, we identify galaxy large scale structures, and will present the correlation or anti-correlation between quiescent galaxy fraction, an indicator of star-forming activity, and the prevalence of galaxy large scale structures.

• 천문학회지
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• 제44권5호
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• pp.177-193
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• 2011

We present a photometric study of five open clusters (Czernik 5, Alessi 53, Berkeley 49, Berkeley 84, and Pfleiderer 3) in the Sloan Digital Sky Survey. The position and size of these clusters are determined using the radial number density profiles of the stars, and the member stars of the clusters are selected using the proper motion data in the literature. We estimate the reddening, distance and age of the clusters based on the isochrone fitting in the color-magnitude diagram. The foreground reddenings for these clusters are estimated to be E(B - V ) = 0.71 - 1.55 mag. The distances to these clusters are derived to be 2.0 - 4.4 kpc, and their distances from the Galactic center range from 7.57 kpc to 12.35 kpc. Their ages are in the range from 250 Myr to 1 Gyr. Berkeley 49 and Berkeley 84 are located in the Orion spur, Czernik 5 is in the Perseus arm, and Pfleiderer 3 and Alessi 53 are located beyond the Perseus arm.

• 천문학회지
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• 제39권4호
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• pp.89-94
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• 2006

We present JHK-band near-infrared photometry of the star clusters in the dwarf irregular galaxy IC 5152. After excluding possible foreground stars, a number of candidate star clusters are identified in the near-infrared images of IC 5152, which include young populations. Especially, five young star clusters are identified in the(J-H, H-K) two color diagram and the total extinction values toward these clusters are estimated to be $A_v=2-6$ from the comparison with the theoretical values given by the Leitherer et al.(1999)'s theoretical star cluster model.

• 천문학회보
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• 제40권1호
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• pp.45.1-45.1
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• 2015

Galaxy clusters have provided important information to understand the evolution of the universe, since the number density and mass of clusters are tightly related to the cosmological parameters. In addition, galaxy clusters are an excellent laboratory to investigate the galaxy evolution in dense environments. However, finding galaxy clusters at high redshift ($z{\geq}1$) still remains as a main subject in astronomy due to their rareness and difficulty in identifying such objects from optical imaging data alone. Here, we report a spectroscopic follow-up observation of distant galaxy cluster candidates identified by a deep optical-NIR dataset of Infrared Medium-deep Survey. Through the galaxy spectra taken with the IMACS instrument on the Magellan telescope, we confirm at least 3 massive clusters at z~0.92. Interestingly, the maximum spatial separation between these clusters is ~8Mpc, which implies that this system is a new supercluster in the distant universe. We also discuss properties of galaxies in these clusters based on multi-wavelength photometric data.

• 한국통신학회논문지
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• 제35권3A호
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• pp.287-295
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• 2010

무선 센서 네트워크에서, 위치정보 없이 이동 싱크를 지원하는 연구들은 노드로 클러스터를 이루고 이들의 연결을 통해서 싱크로 데이터를 전달하는 가상의 인프라구조를 형성한다. 소스 노드가 위치한 클러스터와 싱크가 위치한 클러스터 간에는 이 구조를 통해서 연결되지만, 모든 클러스터 헤드와의 연결을 만들기 위해 플러딩을 하기 때문에 높은 라우팅 비용을 야기한다. 비록 다계층의 클러스터를 통해서 클러스터의 수를 줄일 수는 있지만, 싱크와 소스가 가깝더라도 다른 최상위 클러스터에 속한다면, 데이터는 우회될 수밖에 없다. 그래서 우리는 데이터 우회를 해결하고 클러스터의 수를 줄일 수 있는 멀티 홉 클러스터 기반의 프로토콜을 제안한다. 싱크의 위치 정보서비스와 싱크로의 데이터의 전달을 위해 랑데부 클러스터 헤드를 선정하지만, 소스와 싱크가 속한 클러스터 간의홉 수를 이용해서 효과적으로 데이터의 우회를 줄인다. 시뮬레이션은 기존 방안보다 효과적으로 데이터가 전달되는 것을 보인다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 신호처리소사이어티 추계학술대회 논문집
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• pp.377-380
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• 2003

A new color image segmentation scheme is presented in this paper. The proposed algorithm consists of image simplification, region labeling and color clustering. The vector-valued diffusion process is performed in the perceptually uniform LUV color space. We present a discrete 3-D diffusion model for easy implementation. The statistical characteristics of each labeled region are employed to estimate the number of total clusters and agglomerative hierarchical clustering is performed with the estimated number of clusters. Since the proposed clustering algorithm counts each region as a unit, it does not generate oversegmentation along region boundaries.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.601-605
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• 1991

In this paper an approximate solution method for the large-scale Traveling Salesman Problem(TSP) is presented. The method start with the subdivision of the problem domain into a number of clusters by considering their geometries. The clusters have limited number of nodes so as to get local solutions. They are linked to give the least path which covers the whole domain and become TSPs with start- and end-node. The approximate local solutions in each cluster are obtained by using geometrical property of the cluster, and combined to give an overall-approximate solution for the large-scale TSP.

• ETRI Journal
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• 제13권2호
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• pp.34-41
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• 1991

In this paper, a new distributed parallel algorithm for pattern classification based upon Self-Organizing Neural Network(SONN)[10-12] is developed. This system works without any information about the number of clusters or cluster centers. The SONN model showed good performance for finding classification information, cluster centers, the number of salient clusters and membership information. It took a considerable amount of time in the sequential version if the input data set size is very large. Therefore, design of parallel algorithm is desirous. A new distributed parallel algorithm is developed and experimental results are presented.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 하계종합학술대회 논문집 II
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• pp.1169-1172
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• 2003

In this paper, a CLB-based CPLD low-power technology mapping algorithm consider area and delay time is proposed. To perform low power technology mapping for CPLD, a given Boolean network have to be represented to DAG. The proposed algorithm are consist of three step. In the first step, TD(Transition Density) calculation have to be performed. In the second step, the feasible clusters are generated by considering the following conditions: the number of output, the number of input and the number of OR-terms for CLB(Common Logic Block) within a CPLD. The common node cluster merging method, the node separation method, and the node duplication method are used to produce the feasible clusters. In the final step, low power technology mapping based on the CLBs is packing the feasible clusters into the several proper CLBs. The proposed algorithm is examined by using benchmarks in SIS. In the case of that the number of OR-terms is 5, the experiments results show that reduce the power consumption by 30.73% comparing with that of TEMPLA, and 17.11% comparing with that of PLAmap respectively.

• Communications for Statistical Applications and Methods
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• 제20권1호
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• pp.53-62
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• 2013

This study focuses on spatial/temporal relationship deaths caused by Human Immunodeficiency Virus (HIV) and Alcohol Use Disorder (AUD). Several studies have found links between these two diseases. By looking for clusters in mortality of Alcohol and HIV related deaths this study contributes to the field through the identification of exact spatial/temporal time of high and low occurrence risks based on the observed over the expected number of deaths. This study does not provide political or social interpretations of the data. It merely wants to show where clusters are found.