• The KIPS Transactions:PartC
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• v.14C no.7
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• pp.589-596
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• 2007

Although flooding has the disadvantages like a transmission of duplicated packets and a packet collision, it has been used frequently to find a path between a source and a sink node in a wireless ad hoc network. Clustering is one of the techniques that have been proposed to overcome those disadvantages. In this paper, we propose a new flooding mechanism in ad hoc networks using cluster formation based on the link density which means the number of neighbors within a node's radio reach. To reduce traffic overhead in the cluster is to make the number of non-flooding nodes as large as possible. Therefore, a node with the most links in a cluster will be elected as cluster header. This method will reduce the network traffic overhead with a reliable network performance. Simulation results using NS2 show that cluster formation based on the link density can reduce redundant flooding without loss of network performance.

• Journal of Technology Innovation
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• v.24 no.1
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• pp.189-219
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• 2016

Innovation clusters have developed a key policy indicator in the level of national competitiveness. Many countries have enhanced their regional competitiveness by fostering innovation clusters at the national, regional, and industrial level. In Korea, the cluster policy has been introduced and employed to a national policy as a means of facilitating a regional innovation for over two decades. This study analyze that the changes of the institutional, physical and social configurations of innovation clusters. In particular, we identified configuration factors which are the growth and development impact factors of individual subjects from the case study of the Daedeok Innopolis. Also, the factors are derived and identified priorities of the configuration factors by using Analytic Hierarchy Process (AHP) method in long term perspective. As a result, we provide the growth of individual innovation subjects, as well as the growth of the cluster caused by the cyclic causality among configuration factors. Also, we can suggest that innovation policy from priorities of configuration factors for innovation cluster which the priorities have lessons for policy implementation and new cluster policy agenda in Korea, in specific, the Daedeok Innopolis.

• Journal of the Korea Society for Simulation
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• v.17 no.3
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• pp.95-105
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• 2008

In this paper, we propose the DAMMC(Distributed Authentication Model using Multi-level Cluster) for wireless sensor networks. The proposed model is that one cluster header in m-layer has a role of CA(Certificate Authority) but it just authenticates sensor nodes in lower layer for providing an efficient authentication without authenticating overhead among clusters. In here, the m-layer for authentication can be properly predefined by user in consideration of various network environments. And also, the DAMMC uses certificates based on the threshold cryptography scheme for more reliable configuration of WSN. Experimental results show that the cost of generation and reconfiguration certification are decreased but the security performance are increased compared to the existing method.

• The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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• v.26 no.4
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• pp.51-59
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• 2013

Objective : The aim of this study is to classify the patterns of Ryodoraku using cluster analysis on tinnitus patients. Method : 261 patients with tinnitus and 159 patients with other disease were analyzed. We used cluster analysis with SPSS 20.0 to classify the pattern of Ryodoraku. We searched the cluster characteristics and tried to interpret the specific patterns from previous studies. Result : We divided tinnitus patients to four groups and control patients to five groups. There were some shared patterns between tinnitus group and control group. One group on tinnitus patients showed lower age than other groups. Time, sex, total average did not show any differences among groups. Conclusion : Cluster analysis on tinnitus patients showed the possibility of presenting the specific Ryodoraku patterns. But because of weak Ryodoraku studies, clinical usefulness is unknown. Further study is needed.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.14 no.3
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• pp.287-298
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• 2001

Analysis of nonlinear behavior of prestressed concrete frame structures on PC is a time-consuming computing job if the problem size increase to a certain degree. Cluster system has emerged as one of promising computing environments due to its good extendibility, portability, and cost-effectiveness, comparing it with high-end work-stations or servers. In this paper, a parallel nonlinear analysis procedure of prestressed concrete frame structure is presented using cluster computing. Cluster system is configured with readily available pentium III class PCs under Win98 or Linux and fast ethernet. Parallel computing algorithms on element-wise processing parts including the calculation of stiffness matrix, element stresses and determination of material states, check of material failure and calculation of unbalanced loads are developed using MPL. Validity of the method is discussed through typical numerical examples. For the case of 4 node system, maximum speedup is 3.15 and 3.74 for Win98 and Linux, respectively. Important issues for the efficient use of cluster computing system based un PCs and ethernet are addressed.

• Journal of the Korean Institute of Intelligent Systems
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• v.6 no.3
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• pp.81-88
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• 1996

Cluster analysis is based on partitioning a collection of data points into a number of clusters, where the data points in side a cluster have a certain degree of similarity and it is a fundamental process of data analysis. So, it has been playing an important role in solving many problems in pattern recognition and image processing. For these many clustering algorithms depending on distance criteria have been developed and fuzzy set theory has been introduced to reflect the description of real data, where boundaries might be fuzzy. If fuzzy cluster analysis is tomake a significant contribution to engineering applications, much more attention must be paid to fundamental questions of cluster validity problem which is how well it has identified the structure that is present in the data. Several validity functionals such as partition coefficient, claasification entropy and proportion exponent, have been used for measuring validity mathematically. But the issue of cluster validity involves complex aspects, it is difficult to measure it with one measuring function as the conventional study. In this paper, we propose four performance indices and the way to measure the quality of clustering formed by given learning strategy.

• Nutrition Research and Practice
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• v.13 no.2
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• pp.169-177
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• 2019

BACKGROUND/OBJECTIVES: Excessive sugar intake is one of the causes associated with obesity and several chronic diseases prevalent in the modern society. This study was undertaken to investigate the effect of parenting variables based on the theory of planned behavior, on the sweetness preferences and sweets intake of children. SUBJECTS/METHODS: Parents and their children (n = 103, aged 5-7 years) were enrolled to participate in a survey for this study, after providing the required informed consent. Parents were asked to fill out a self-administered questionnaire at their residence. The sweetness preference test for children was conducted at a kindergarten (or daycare center) by applying the one-on-one interview method. RESULTS: The children were divided into two clusters categorized by the K-mean cluster analysis: Cluster 1 had higher sweetness preference (0.42 M sugar, 35%; 0.61 M sugar, 65%); Cluster 2 exhibited lower sweetness preference (0.14 M sugar, 9.5%; 0.20 M sugar, 9.5%; 0.29 M sugar, 81%). Cluster 1 had a higher frequency of sweets intake (P < 0.01), and lower sweets restriction (P < 0.05) and nutrition quotient score (P < 0.05). Sweets intake was negatively correlated with the nutritional quotient (r = -0.204, P < 0.05). The behavioral intention of parents was higher in cluster 2 (P < 0.05), while affective attitude, feeding practice, and reward were higher in cluster 1 (P < 0.001, P < 0.05, and P < 0.01, respectively). Furthermore, behavioral intention of parents showed a negative correlation with affective attitude (r = -0.282, P < 0.01) and feeding practice (r = -0.380, P < 0.01), and a positive correlation with subjective norm (r = 0.203, P < 0.05) and parenting attitude (r = 0.433, P < 0.01). CONCLUSIONS: This study indicates that the sweetness preferences and sweets intake of children is related to the parent's affective attitude, feeding practice and reward. We suggest that to reduce the sugar consumption of children, guidelines for access to sweets and pertinent parenting practices are required.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.27 no.1
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• pp.124-130
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• 2023

In this paper, we intend to improve the network lifetime by improving the energy efficiency of sensor nodes in a wireless sensor network by utilizing machine learning using K-means clustering algorithm. A wireless sensor network is a wireless network composed of physical devices including batteries as physical sensors. Due to the characteristics of sensor nodes, all resources must be efficiently used to minimize energy consumption to maximize network lifetime. A cluster based approach is used to manage groups of relatively large numbers of nodes. In the proposed protocol, by improving the existing LEACH algorithm, we propose a clustering algorithm that selects a cluster head using a cluster based approach and a location based approach. The performance results to be improved were measured using Matlab simulation. Through the experimental results, K-means clustering was applied to the energy efficiency part. By utilizing K-means, it is confirmed that energy efficiency is improved and the lifetime of the entire network is extended.

• 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 Society of Clothing and Textiles
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• v.47 no.5
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• pp.959-976
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• 2023

This study participated in educational programs for young designers and received trainings in sewing technology through government and local government-supported projects led by a from a skilled craftsman. These initiatives aim to revitalize the Dongdaemun fashion cluster, which is currently experiencing stagnation. Our goal is to develop denim brands that reflect the unique regional characteristics stemming from the skilled sewing techniques and denim processes of the Changsin·Sungin regions, the production hubs supporting Dongdaemun, to discover solutions for revitalizing the local industry. For the research method, we collected data by actively participating in support projects related to the Dongdaemun fashion cluster. Additionally, we gathered data by conducting a theoretical review of the sewing industry in the Changsin·Sungin regions and the Dongdaemun fashion cluster. The research results include developing a denim brand collection-eight denim products-based on Changsin-dong's unique denim sewing technology and various denim washing processes acquired through the support project and regional characteristics. Overall, this study is meaningful in presenting a sustainable plan to revitalize the domestic sewing and manufacturing industry, focusing on the Dongdaemun fashion cluster. We achieved this by developing a denim brand that leverages the sewing and washing process technology and the unique regional characteristics of Changsin-dong.