• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2001년도 추계 학술대회논문집
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• pp.58-62
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• 2001

Aparallel computing environment was constructed based on Windows 2000 operating system. This cluster was configured using Fast-Ethernet system to hold up together the clients within a network domain. For the parallel computation, MPI implements for Windows such as MPICH.NT.1.2.2 and MP-MPICHNT.1.2 were used with Compaq Visual Fortran compiler which produce a well optimized executives for x86 systems. The evaluation of this cluster performance was carried out using a preconditioned Navier-Stokes code for the 2D analysis of a compressible and viscous flow around a compressor blade. The parallel performance was examined in comparison with those of Linux clusters studied previously by changing a number of processors, problem size and MPI libraries. The result from the test problems presents that parallel performance of the low cost Fast-Ethernet Windows cluster is superior to that of a Linux cluster of similar configuration and is comparable to that of a Myrinet cluster.

• 응용통계연구
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• 제25권3호
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• pp.447-456
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• 2012

For a sensitive survey in which the population is comprised of several clusters with a quantitative attribute, we present an additive quantitative randomized response model by cluster sampling that adapts a two-stage cluster sampling instead of a simple random sample based on Himmelfarb-Edgell's additive quantitative attribute model and Gjestvang-Singh's one. We also derive optimum values for the number of 1st stage clusters and the optimum values of observation units in a 2nd stage cluster under the condition of minimizing the variance given constant cost. We can see that Himmelfarb-Edgell's model is more efficient than Gjestvang-Singh's model under the condition of cluster sampling.

• 천문학회보
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• 제39권2호
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• pp.51.1-51.1
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• 2014

The Virgo cluster, the nearest galaxy cluster, is dynamically young, hosting numerous globular clusters in galaxies as well as intracluster globular clusters (IGCs). We obtained spectra of globular cluster candidates in the core region of the Virgo cluster using Hectospec at MMT to study the kinematics of the globular clusters. The targets are located at a large range (50 kpc < d < 500 kpc) from M87, the most massive galaxy in Virgo. We distinguish the genuine globular cluster population in the targets by inspecting their spectral features and radial velocities. As a result, a significant number of IGCs are found. We present preliminary results of the kinematics of globular clusters in the Virgo core region.

• 천문학회지
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• 제29권2호
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• pp.269-278
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• 1996

We present the color-magnitude diagrams (CMD) of more than 24,000 stars in the field of an intermediate age open cluster M11, based on wide field CCD imaging. The morphology of the CMDs varies strikingly as the distance from the center of the cluster increases. From the surface number density analysis, we confirm the mass segregation effect in this cluster: the bright, massive stars are centrally more concetrated than the faint, low mass stars. The slope of the field-corrected surface density with respect to magnitude progressively increases as the radius increases, up to r = 5'. Most of the field stars in or near the cluster main sequence band and in the bright part of the red stars in the CMDs appear to be nearly at the same distance as M11, and they are considered to be the major component of disk stars in the Sagittarius-Carina arm.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 ITC-CSCC -1
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• pp.314-317
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• 2000

Cluster system provides attractive scalability in terms of computation power and memory size. With the advances in high speed computer network technology, cluster systems are becoming increasingly competitive compared to expensive parallel machines. In parallel processing program, each task load is difficult to predict before running the program and each task is interdependent each other in many ways. Load imbalancing induces an obstacle to system performance. Most of researches in load balancing were concerned with distributed system but researches in cluster system are few. In cluster system, the dynamic load balancing algorithm which evaluates each processor's load in runtime is purpose that the load of each node are evenly distributed. But, if communication cost or node complexity becomes high, it is not effective method for all nodes to attend load balancing process. In that circumstances, it is good to reduce the number of node which attend to load balancing process. We have modeled cluster systems and proposed marginal dynamic load balancing algorithms suitable for that circumstances.

• 한국컴퓨터정보학회논문지
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• 제24권1호
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• pp.1-7
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• 2019

In this paper, we implemented a Wi-Fi based cluster system using raspberry pi for multidisciplinary education. The cluster implementation on the desktop was more difficult to maintain the complexity, big size, high price, power consumption as the number of nodes increased. In this paper, we implemented a cluster using Raspberry Pi, which is developed for educational purposes, to reduce the cost of connecting nodes. In addition, the complexity of system construction is reduced by replacing the connection between each node with Wi-Fi. Also, the inconvenience of configuration due to node increase was reduced. It is expected that the implementation of the cluster will be a good alternative in the educational environment where distributed processing and parallel processing are performed in the embedded environment. Also, it is confirmed that it can be applied to the multidisciplinary education.

• 한국경영과학회지
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• 제42권3호
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• pp.25-34
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• 2017

K-means is a popular and efficient data clustering method that only uses intra-cluster distance to establish a valid index with a previously fixed number of clusters. K-means is useless without a suitable number of clusters for unsupervised data. This paper aimsto propose the Group Search Optimization (GSO) using Silhouette to find the optimal data clustering solution with a number of clusters for unsupervised data. Silhouette can be used as valid index to decide the number of clusters and optimal solution by simultaneously considering intra- and inter-cluster distances. The performance of GSO using Silhouette is validated through several experiment and analysis of data sets.

• Journal of Information Processing Systems
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• 제20권2호
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• pp.185-199
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• 2024

In this paper, an improved automated spectral clustering (IASC) algorithm is proposed to address the limitations of the traditional spectral clustering (TSC) algorithm, particularly its inability to automatically determine the number of clusters. Firstly, a cluster number evaluation factor based on the optimal clustering principle is proposed. By iterating through different k values, the value corresponding to the largest evaluation factor was selected as the first-rank number of clusters. Secondly, the IASC algorithm adopts a density-sensitive distance to measure the similarity between the sample points. This rendered a high similarity to the data distributed in the same high-density area. Thirdly, to improve clustering accuracy, the IASC algorithm uses the cosine angle classification method instead of K-means to classify the eigenvectors. Six algorithms-K-means, fuzzy C-means, TSC, EIGENGAP, DBSCAN, and density peak-were compared with the proposed algorithm on six datasets. The results show that the IASC algorithm not only automatically determines the number of clusters but also obtains better clustering accuracy on both synthetic and UCI datasets.

• 한국통신학회논문지
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• 제38B권6호
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• pp.446-453
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• 2013

무선 센서네트워크에서 클러스터링 기법은 네트워크 확장성과 네트워크 수명 연장에 효율적이라고 인정받고 있다. 본 논문에서는 클러스터 기반 센서 네트워크에서 multi-hop to one-hop 전송 환경을 고려하여 에너지 효율성에 최적인 클러스터 비율(cluster ratio, CR)을 분석하는데 초점을 둔다. 본 논문에서는 지정한 클러스터 비율을 통한 시스템 홉 수(hop-count) 최소화와 노드 간 패킷수신율(packet reception ratio, PRR) 최대화 사이의 이해득실(trade-off) 관계를 분석하고 이 두 요소를 종합적으로 고려하여 목표함수를 유도한다. 제안한 목표함수를 통하여 얻은 최적의 클러스터 비율은 네트워크에서 패킷 전송에 드는 비용뿐만 아니라 노드 간 재전송 오버헤드를 줄여줌으로써 에너지 효율성을 향상시킨다. 본 논문에서 제안한 기법은 최소 홉 수 클러스터링 방안과 비교되며 시뮬레이션을 통하여 향상된 에너지 효율성을 검증하였다.

• Journal of the Korean Statistical Society
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• 제27권4호
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• pp.459-469
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• 1998

Balanced half sample method is a simple variance estimation method for complex sampling designs. Since it is simple and flexible, it has been widely used in large scale sample surveys. However, the usual BHS method overestimate the true variance in without replacement sampling and two-stage cluster sampling. Focusing on this point , we proposed an unbiased BHS variance estimator in a stratified two-stage cluster sampling and then described an implementation method of the proposed estimator. Finally, partially BHS design is explained as a tool of reducing the number of replications of the proposed estimator.