• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.155-161
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• 2015

Efficient energy consumption is a one of the key issues in wireless sensor networks. Clustering-based routing algorithms have been popular solutions for such an issue. Re-clustering is necessary for avoiding early energy drain of cluster head nodes in such routing strategies. The re-clustering process itself, however, is another source of energy consumption. It is suggested in this work to adaptively set the frequency of re-clustering by comparing the energy levels of cluster heads and a threshold value. The algorithm keeps the clusters if all the cluster heads' energy levels are greater than the threshold value. We confirm through simulations that the suggested algorithm shows better energy efficiency than the existing solutions.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.848-850
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• 2014

Mobile Ad hoc Networks(MANET) is consist of node that has mobility, MANET build cluster formation for using energy efficient. In existing LEACH algorithm elect cluster head node in coverage area by distribution function. However, when the cluster head node, that elected by distribution function, is divided coverage area unevenly, the network can't consumption energy efficiency. To solve this problem, we proposed CSWC(Coverage Scheduling Weight-value Control) algorithm. When the coverage area is divided nonchalance, proposed algorithm increased number of hops, that determines coverage area, for balance coverage area. As the result proposed algorithm is set balance coverage area, the network consumption energy efficiency.

• Korean Journal of Microbiology
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• v.26 no.3
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• pp.247-255
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• 1988

Using the numerical clustering method, 14 clusters (containing three or more strains) among 231 bacterial isolates from St. 1,17 clusters among 252 isolates from St.2,17 clusters among 301 isolates from St.3, and 15 clusters among 260isolates from St.4 were found at the 70% similarity value. The predominant organisms were identified as genera Aeromonas, Vibrio, and Alcaligenes at St.1, Alcaligenes at St.2, Aeromonas, Vibrio, and Moraxella-Acinetobacter group at St.3, and Pseudomonas at St.4.

• ETRI Journal
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• v.27 no.4
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• pp.465-468
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• 2005

This paper presents a new trust evaluation scheme in an ad hoc network. To overcome the limited information about unfamiliar nodes and to reduce the required memory space, we propose a cluster-based trust evaluation scheme, in which neighboring nodes form a cluster and select one node as a cluster head. The head issues a trust value certificate that can be referred to by its non-neighbor nodes. In this way, an evaluation of an unfamiliar node's trust can be done very efficiently and precisely. In this paper, we present a trust evaluation metric using this scheme and some operations for forming and managing a cluster. An analysis of the proposed scheme over some security problems is also presented.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2007.11a
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• pp.203-204
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• 2007

This paper investigated the influence on partial discharge distribution of various defects at the model power cable joints interface using K-means clustering. As the result of analyzing discharge number distribution of ${\Phi}-n$ cluster, clusters shifted to $0^{\circ}\;and\;180^{\circ}$ with increasing applying voltage. It was confirmed that discharge quantity and euclidean distance between centroids were increased with applying voltage from the analyzing centroid distribution of ${\Phi}-q$ cluster. The degree of dispersion was increased with calculating standard deviation of ${\Phi}-q$ cluster centroid. The tendency both number of discharge and mean value of ${\Phi}-q$ cluster centroid were some different with defect types.

• Korean Journal of Environment and Ecology
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• v.29 no.2
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• pp.236-249
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• 2015

The master plan of forest land management proposes forest watershed management that considers regional characteristics in order to overcome the problem of uniform forest land management. In order to manage the forest watersheds in Gyeonggi-do, this study classified 1,823 forest watersheds in Gyeonggi-do and attempted to understand their characteristics. It conducted a factor analysis and cluster analysis from the perspective of conservation value and development pressure using forest land indicators. In terms of conservation value, three factors were drawn: the topography factor, vegetation factor and public service factor, while in terms of development pressure, three factors were drawn: the easiness of development factor, economic benefits factor and development activity factor. Using these factors, forest watersheds were divided into three clusters in terms of conservation value while they were divided into three clusters in terms of development pressure. Using the results of the cluster analysis from a conservation-development perspective, the forest watersheds were classified into nine different types, and the characteristics were identified by each type. It is judged that the factors and clusters drawn as a result of the research accurately reflect the present conditions of Gyeonggi-do, and the nine types of forest watersheds have clear characteristics according to each type, which are judged to be utilized in forest management in the future.

• The Korean Journal of Franchise Management
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• v.7 no.1
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• pp.21-29
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• 2016

Purpose - The primary purpose of this study is to employ effective marketing methods using market segmentation of coffee shops by determining how motivations to visit coffee shops have different impacts on demographic profile of visitors and characteristics of coffee shop visits, so as to draw out a better understanding of customers of coffee market. Research design, data, and methodology - Data were collected using surveys of self-administered questionnaires toward coffee shop users in Daejeon, Korea. A number of samples used in data analysis were 253 excluding unusable responses. The data were analyzed through frequency, reliability, and factor analysis using SPSS 20.0. Factor analysis was conducted through the principal component analysis and varimax rotation method to derive factors of one or more eigen values. In addition, the cluster analysis, multivariate ANOVA, and cross-tab analysis were used for the market segmentation based on the types of motivation for coffee shop visits. The process of the cluster analysis is as follows. Four clusters were derived through hierarchical clustering, and k-means cluster analysis was then carried out using mean value of the four clusters as the initial seed value. Result - The factor analysis delineated four dimensions of motivation to visit coffee shops: ostentation motivation, hedonic motivation, esthetic motivation, utility motivation. The cluster analysis yielded four clusters: utility and esthetic seekers, hedonic seekers, utility seekers, ostentation seekers. In order to further specify the profile of four clusters, each cluster was cross tabulated with socio-demographics and characteristics of coffee shop visits. Four clusters are significantly different from each other by four types of motivations for coffee shop visits. Conclusions - This study has empirically examined the difference in demographic profile of visitors and characteristics of coffee shop visits by motivation to visit coffee shops. There are significant differences according to age, education background, marital status, occupation and monthly income. In addition, coffee shops use pattern characterization in frequency of visits to coffee shops, relationships with companion, purpose of visit, information sources, brand type, average expense per visit, important elements of selection attribute were significantly different depending on motivations for coffee shop visits.

• Journal of The Korean Astronomical Society
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• v.40 no.4
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• pp.153-155
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• 2007

We have analyzed H and $K_s$-band images of the Arches cluster obtained using the NIRC2 instrument on Keck with the laser guide star adaptive optics (LGS AO) system. With the help of the LGS AO system, we were able to obtain the deepest ever photometry for this cluster and its neighborhood, and derive the background-subtracted present-day mass function (PDMF) down to $1.3M_{\bigodot}$ for the 5"-9" annulus of the cluster. We find that the previously reported turnover at $6M_{\bigodot}$ is simply due to a local bump in the mass function (MF), and that the MF continues to increase down to our 50 % completeness limit ($1.3M_{\bigodot}$) with a power-law exponent of ${\Gamma}$ = -0.91 for the mass range of 1.3 < M/$M_{\bigodot}$ < 50. Our numerical calculations for the evolution of the Arches cluster show that the ${\Gamma}$ values for our annulus increase by 0.1-0.2 during the lifetime of the cluster, and thus suggest that the Arches cluster initially had ${\Gamma}$ of $-1.0{\sim}-1.1$, which is only slightly shallower than the Salpeter value.

• The Korean Journal of Applied Statistics
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• v.27 no.2
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• pp.331-343
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• 2014

We propose two estimating procedures to analyze clustered interval-censored data with an informative cluster size based on a marginal model and investigate their asymptotic properties. One is an extension of Cong et al. (2007) to interval-censored data and the other uses the within-cluster resampling method proposed by Hoffman et al. (2001). Simulation results imply that the proposed estimators have a better performance in terms of bias and coverage rate of true value than an estimator with no adjustment of informative cluster size when the cluster size is related with survival time. Finally, they are applied to lymphatic filariasis data adopted from Williamson et al. (2008).

• Journal of the Korean Society of Costume
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• v.67 no.3
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• pp.47-65
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• 2017

The purpose of this study was to divide respondents by consumption values, and to examine the differences in their cosmetic purchase behavior. Cosmetic purchase behavior consisted of variables such as purchase frequency, purchase amount, place of purchase, purchase reason, reason for using cosmetics, purchase propensity, degree of using information source, and selection criteria. A survey was conducted with 308 women between the ages 20 and 29 from December 5th to 10th 2016. Data collected from the respondents through an Internet survey were analyzed using descriptive statistics, factor analyses, cluster analysis, analyses of variance and chi-square tests. Four consumption value dimensions emerged that were termed emotional, differentiated individuality-pursuing, functional and social value. The respondents were classified into three groups(emotional consumer group, functional consumer group, active consumer group) by cluster analysis using four dimensions of consumption value. The results of the analyses of variance and chi-square tests showed significant differences in purchase frequency, place of purchase, purchase reason, reason for using cosmetics, degree of using information source and selection criteria among groups classified by consumption value. However, there were no differences in purchase amount and purchase propensity among them.