• The Bulletin of The Korean Astronomical Society
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• v.38 no.2
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• pp.77.1-77.1
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• 2013

산개성단은 은하계 내에서 그 일생을 보내며 자체적인 역학적 진화를 한다. 또한, 거대 성간 분자운, 은하의 회전 그리고 은하의 중력 등에 영향을 받아 성단의 헤일로 영역에 조석꼬리와 같은 구조로 나타날 수 있다. 이러한 현상을 관측하기는 어려운데 그 이유는 넓은 영역에 걸쳐 있는 성단의 흐린 구성원에 대한 고유운동 자료가 없어 낱별과 성단의 구성원을 구별하는 것이 어렵기 때문이다. 우리는 이 문제를 통계적으로 해결하기 위하여 "4차원 구성원 확률" 이라는 새로운 방법을 개발하였다. 이 방법은 별의 공간 좌표와 색-등급도 상에서 위치를 동시에 고려하여 구성원 확률을 구하는 독창적인 방법이다. 본 발표에서는 이 방법을 적용한 결과를 고유운동으로 얻은 구성원확률과 비교하고, 몬테칼로 시뮬레이션으로 검증한 결과를 소개하고자 한다. 우리의 방법을 통하여, 은하면에 있는 다양하고 많은 산개성단에 대하여 관측연구를 수행한다면, 다양한 조석꼬리의 가능성 검증을 할 수 있고, 은하와 성단의 상호 작용과 역학적 진화에 대한 이해의 폭을 넓힐 수 있을 것으로 기대한다.

• Publications of The Korean Astronomical Society
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• v.24 no.1
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• pp.9-18
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• 2009

From the short-period variability survey (SPVS) in Bohyunsan Optical Astronomy Observatory, we obtained time-series BV CCD images in the region of an open cluster M38 (NGC 1912) for 23 nights from February 1, 2007 to December 7, 2008. We found 18 $\delta$ Scuti stars and 2 $\gamma$ Doradus stars. Among them, only 3 $\delta$ Scuti stars were known ones. From the color-magnitude diagram (CMD) of M38, most of them have been located in the instability strip. The two $\gamma$ Doradus stars have been located within $\gamma$ Doradus strip of M38. But, only four $\delta$ Scuti stars were located within radius 10' from the center of M38. To confirm of their membership for M38, we need more study, such as, proper motion by spectroscopic observation.

• Journal of The Korean Astronomical Society
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• v.49 no.2
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• pp.53-57
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• 2016

We present an optical UBVRI photometric analysis of the poorly studied open star cluster IC 2156 using Sloan Digital Sky Survey data in order to estimate its astrophysical properties. We compare these with results from our previous studies that relied on the 2MASS JHK near-infrared photometry. The stellar density distributions and color-magnitude diagrams of the cluster are used to determine its geometrical structure, real radius, core and tidal radii, and its distance from the Sun, the Galactic plane, and the Galactic center. We also estimate, the age, color excesses, reddening-free distance modulus, membership, total mass, luminosity function, mass function, and relaxation time of the cluster.

• The Journal of the Korea Contents Association
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• v.11 no.3
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• pp.48-55
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• 2011

In this paper, we analyze the input-output characteristics of fuzzy inference systems according to the division of entire input spaces and the fuzzy reasoning methods to identify the fuzzy model for nonlinear process. And fuzzy model is expressed by identifying the structure and parameters of the system by means of input variables, fuzzy partition of input spaces, and consequence polynomial functions. In the premise part of the rules Min-Max method using the minimum and maximum values of input data set and C-Means clustering algorithm forming input data into the hard clusters are used for identification of fuzzy model and membership function is used as a series of triangular membership function. In the consequence part of the rules fuzzy reasoning is conducted by two types of inferences. The identification of the consequence parameters, namely polynomial coefficients, of the rules are carried out by the standard least square method. And lastly, we use gas furnace process which is widely used in nonlinear process and we evaluate the performance for this nonlinear process.

• Health Policy and Management
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• v.17 no.4
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• pp.54-81
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• 2007

The paradigm of health promotion requests community participation and its active problem-solving. Community is conceptualized as a resource pool to be organized. Such resource is called community capacity. Community participation is a process of capacity building. Community voluntary associations are considered as valuable resource to be used for health promotion. This paper tried to identify the network structure among community voluntary associations and to infer the possibility to make such network of organizations participate in health promotion programs. Two survey data were used for this research: 1) Measurements and Evaluations of Community Capacity on Dobong-gu (N=94) 2) A development plan of health medicine service to be Healthy Gangdong-gu (N=69). The questionnaire included such variables measuring community capacity as leadership, membership, organizational resources, and inter-organizational network, etc. Both regions had the following common characteristics: 1) There were positive correlations between the organization's budget and membership. 2) Organizational types were associated with their founded years. Two regions showed the following differences: Dobong displayed the high density of community organizations, but Gangdong showed the low density. Dobong community organizations were able to be classified into three network clusters such as women & environments, youth & adolescent, and sports organizations. Each cluster of organizations favored the different type of health promotion programs. Gangdong community organizations were less developed, and not possible to be clustered. Depending upon the level of community capacity or community organizations' differentiation, the strategy of community participation could be settle down in different ways. Particularly the health agency had to pay more attention to support the growth of civil organizations.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.9
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• pp.1905-1912
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• 2009

Clustering results based on the FCM algorithm sometimes produces undesirable clustering result through data distribution in the clustered space because data is classified by comparison with membership degree which is calculated by the Euclidean distance between input vectors and clusters. Symmetrical measurement of clusters and fuzzy theory are applied to the classification to tackle this problem. The enhanced FCM algorithm has a low impact with the variation of changing distance about each cluster, middle of cluster and cluster formation. Improved hybrid network of applying FCM algorithm is proposed to classify patterns effectively. The proposed enhanced FCM algorithm is applied to the learning structure between input and middle layers, and normalized delta learning rule is applied in learning stage between middle and output layers in the hybrid network. The proposed algorithms compared with FCM-based RBF network using Max_Min neural network, FMC-based RBF network and HCM-based RBF network to evaluate learning and recognition performances in the two-dimensional coordinated data.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.5
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• pp.981-989
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• 2010

In this study, we introduce a new architecture of fuzzy inference system. In the fuzzy inference system, we use Fuzzy C-Means clustering algorithm to form the premise part of the rules. The membership functions standing in the premise part of fuzzy rules do not assume any explicit functional forms, but for any input the resulting activation levels of such radial basis functions directly depend upon the distance between data points by means of the Fuzzy C-Means clustering. As the consequent part of fuzzy rules of the fuzzy inference system (being the local model representing input output relation in the corresponding sub-space), four types of polynomial are considered, namely constant, linear, quadratic and modified quadratic. This offers a significant level of design flexibility as each rule could come with a different type of the local model in its consequence. Either the Least Square Estimator (LSE) or the weighted Least Square Estimator (WLSE)-based learning is exploited to estimate the coefficients of the consequent polynomial of fuzzy rules. In fuzzy modeling, complexity and interpretability (or simplicity) as well as accuracy of the obtained model are essential design criteria. The performance of the fuzzy inference system is directly affected by some parameters such as e.g., the fuzzification coefficient used in the FCM, the number of rules(clusters) and the order of polynomial in the consequent part of the rules. Accordingly we can obtain preferred model structure through an adjustment of such parameters of the fuzzy inference system. Moreover the comparative experimental study between WLSE and LSE is analyzed according to the change of the number of clusters(rules) as well as polynomial type. The superiority of the proposed model is illustrated and also demonstrated with the use of Automobile Miles per Gallon(MPG), Boston housing called Machine Learning dataset, and Mackey-glass time series dataset.

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.10
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• pp.1365-1371
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• 2017

Objective: This study was conducted to investigate the basic information on genetic structure and characteristics of Korean Native chickens (NC) and foreign breeds through the analysis of the pure chicken populations and commercial chicken lines of the Hanhyup Company which are popular in the NC market, using the 20 microsatellite markers. Methods: In this study, the genetic diversity and phylogenetic relationships of 445 NC from five different breeds (NC, Leghorn [LH], Cornish [CS], Rhode Island Red [RIR], and Hanhyup [HH] commercial line) were investigated by performing genotyping using 20 microsatellite markers. Results: The highest genetic distance was observed between RIR and LH (18.9%), whereas the lowest genetic distance was observed between HH and NC (2.7%). In the principal coordinates analysis (PCoA) illustrated by the first component, LH was clearly separated from the other groups. The correspondence analysis showed close relationship among individuals belonging to the NC, CS, and HH lines. From the STRUCTURE program, the presence of 5 clusters was detected and it was found that the proportion of membership in the different clusters was almost comparable among the breeds with the exception of one breed (HH), although it was highest in LH (0.987) and lowest in CS (0.578). For the cluster 1 it was high in HH (0.582) and in CS (0.368), while for the cluster 4 it was relatively higher in HH (0.392) than other breeds. Conclusion: Our study showed useful genetic diversity and phylogenetic relationship data that can be utilized for NC breeding and development by the commercial chicken industry to meet consumer demands.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.3
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• pp.231-238
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• 2002

As a modeling method where the merits of fuzzy inference system and evolutionary computation are put together, evolutionary fuzzy modeling performs global approximate optimization. The paper proposes fuzzy clustering as fuzzy rule generation process which is one of the most important steps in evolutionary fuzzy modeling. With application of fuzzy clustering into the experiment or simulation results, fuzzy rules which properly describe non-linear and complex design problem can be obtained. The efficiency of evolutionary fuzzy modeling can be improved utilizing the membership degrees of data to clusters from the results of fuzzy clustering. To ensure the validity of the proposed method, the real design problem of an automotive inner trim is applied and the global approximation is achieved. Evolutionary fuzzy modeling is performed for several cases which differ in the number of clusters and the criterion of rule selection and their results are compared to prove that the proposed method can provide proper fuzzy rules for a given system and reduce computation time while maintaining the errors of modeling as a satisfactory level.

• Journal of The Korean Astronomical Society
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• v.44 no.2
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• pp.39-48
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• 2011

UBV I CCD photometry of NGC 2353 is performed as a part of the "Sejong Open cluster Survey" (SOS). Using photometric membership criteria we select probable members of the cluster. We derive the reddening and distance to the cluster, i.e., E(B - V ) = 0.10 ${\pm}$ 0.02 mag and 1.17 ${\pm}$ 0.04 kpc, respectively. We find that the projected distribution of the probable members on the sky is elliptical in shape rather than circular. The age of the cluster is estimated to be log(age)=8.1 ${\pm}$ 0.1 in years, older than what was found in previous studies. The minimum value of binary fraction is estimated to be about 48 ${\pm}$ 5 percent from a Gaussian function fit to the distribution of the distance moduli of the photometric members. Finally, we also obtain the luminosity function and the initial mass function (IMF) of the probable cluster members. The slope of the IMF is ${\Gamma}=-1.3{\pm}0.2$.