• Journal of Communications and Networks
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• v.12 no.4
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• pp.358-365
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• 2010

We develop a low complexity cooperative diversity protocol for low energy adaptive clustering hierarchy (LEACH) based wireless sensor networks. A cross layer approach is used to obtain spatial diversity in the physical layer. In this paper, a simple modification in clustering algorithm of the LEACH protocol is proposed to exploit virtual multiple-input multiple-output (MIMO) based user cooperation. In lieu of selecting a single cluster-head at network layer, we proposed M cluster-heads in each cluster to obtain a diversity order of M in long distance communication. Due to the broadcast nature of wireless transmission, cluster-heads are able to receive data from sensor nodes at the same time. This fact ensures the synchronization required to implement a virtual MIMO based space time block code (STBC) in cluster-head to sink node transmission. An analytical method to evaluate the energy consumption based on BER curve is presented. Analysis and simulation results show that proposed cooperative LEACH protocol can save a huge amount of energy over LEACH protocol with same data rate, bit error rate, delay and bandwidth requirements. Moreover, this proposal can achieve higher order diversity with improved spectral efficiency compared to other virtual MIMO based protocols.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.2
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• pp.67.4-68
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• 2021

In studying the dynamical evolution of galaxy clusters, one intriguing approach is to compare the spatial distributions of various components, such as the dark matter, the member galaxies, the gas, and the intracluster light (ICL; the diffuse light from stars, which are not bound any individual cluster galaxy). If we find a visible component whose spatial distribution coincides with the dark matter distribution, then we could draw a dark matter map without requiring laborious weak lensing analysis. Furthermore, if the component traces the dark matter distribution better for more relaxed galaxy cluster, we could use the similarity as a dynamical stage estimator of the galaxy cluster. We present a novel new methodology to quantify the similarity of two or more 2-dimensional spatial distributions. We apply the method to a sample of galaxy clusters at different dynamical stages simulated within N-cluster Run, which is an N-body simulation using the galaxy replacement technique. Among the various components (stellar particles, galaxies, ICL), the velocity defined ICL+ brightest cluster galaxy (BCG) component traces the dark matter best. Between the sample galaxy clusters, the relaxed clusters show stronger similarity of the spatial distribution between the dark matter and ICL+BCG than the dynamically young clusters.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.1 no.1
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• pp.1-17
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• 2007

This paper proposes and analyzes a scalable and an efficient cluster based group key management protocol by introducing identity based infrastructure for secure communication in mobile wireless sensor networks. To ensure scalability and dynamic re-configurability, the system employs a cluster based approach by which group members are separated into clusters and the leaders of clusters securely communicate with each other to agree on a group key in response to changes in membership and member movements. Through analysis we have demonstrated that our protocol has a high probability of being resilient for secure communication among mobile nodes. Finally, it is established that the proposed scheme is efficient for secure positioning in wireless sensor networks.

• Journal of the Korean housing association
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• v.17 no.1
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• pp.29-36
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• 2006

Welwyn Garden City benefits from the greater design cohesion and management of development which gave it a more distinctive 'brand image' almost from the outset than its older garden city(Letchworth, Hampstead). Its planner, Louis de Soissons, brought a more obvious sense of traditional formal urbanism to the design of the second garden city. This was rather different to the distinctive but rather more informal arts and crafts approach of Raymond Unwin. Here it attempts to analyze how they greatly and firmly established the concept of Housing Group in the residential design, and what similar elements between Unwin and de Soissons in the New Town planning. It is pointed out that the Housing Group theory is composed of recognizing urban life as totality, and group planning theory, and that they definitely originated a new technique in the residential area. It is analyzed that the syntactic relations between the group planning theory and enclosed housing cluster designs in the English garden city are epitomized in Welwyn Garden City.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.3
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• pp.397-402
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• 2007

In this paper, we present a method for clustering incomplete Microarray data using alternating optimization in which a prior imputation method is not required. To reduce the influence of imputation in preprocessing, we take an alternative optimization approach to find better estimates during iterative clustering process. This method improves the estimates of missing values by exploiting the cluster Information such as cluster centroids and all available non-missing values in each iteration. The clustering results of the proposed method are more significantly relevant to the biological gene annotations than those of other methods, indicating its effectiveness and potential for clustering incomplete gene expression data.

• Korean Journal of Child Studies
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• v.27 no.3
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• pp.81-100
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• 2006

This study explored the relationship of behavioral inhibition to narrative representations. Narratives of 96 four-year-old children were recorded and analyzed by the scoring system of Robinson, Holmberg and Klute(in press). Six clusters were found : Constrained(47.9%), Anxious/Restricted(23.9%), Emotional Integrated/Empathic(12.5%), Empathic/Avoidant(6.3%), Dysregulated(5.2%) and Anxious/Avoidant(4.2%) clusters. Behavioral inhibition was determined by observations using "Play with Unfamiliar Peers(Rubin et al., 2002)". Behavioral inhibition differences corresponded to the children's narrative representation clusters; The Anxious/Restricted Cluster was related to more and the Emotional Integrated/Empathic Cluster to less inhibited behavior. In context-specific differences, more inhibited behavior was related to Anxious/Avoidant Clusters during show-and-tess and to Empathic/Avoidant Clusters during card-sorting activities, respectively.

• Journal of the Korean Data and Information Science Society
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• v.26 no.3
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• pp.581-592
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• 2015

In the GORRAM, the estimation of resource requirements for wartime equipment is based on the ELCON of the USA. The number of vulnerability groups of ELCON are 22, but unfortunately it is hard to determine how the 22 groups are classified. Thus, in this research we collected 505 types of basic items used in wartime and classified those items into new vulnerability groups using AHP and cluster analysis methods. We selected 11 variables through AHP to classify those items with cluster analysis. Next, we decided the number of vulnerability groups through hierarchical clustering and then we classified 505 types of basic items into the new vulnerability groups through K-means clustering.This paper presents new vulnerability groups of 505 types of basic items fitted to Korean weapon systems. Furthermore, our approach can be applied to a new weapon system which needs to be classified into a vulnerability group. We believe that our approach will provide practitioners in the military with a reliable and rational method for classifying wartime equipment and thus consequentially predict the exact estimation of resource requirements in wartime.

• The KIPS Transactions:PartB
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• v.14B no.2
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• pp.135-140
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• 2007

Feature selection is a preprocessing technique commonly used on high dimensional data. Feature selection studies how to select a subset or list of attributes that are used to construct models describing data. Feature selection methods attempt to explore data's intrinsic properties by employing statistics or information theory. The recent developments have involved approaches like correlation method, dimensionality reduction and mutual information technique. This feature selection have become the focus of much research in areas of applications with massive and complex data sets. In this paper, we provide a feature selection method considering data characteristics and generalization capability. It provides a computational approach for feature selection based on fuzzy cluster analysis of its attribute values and its performance measures. And we apply it to the system for classifying computer virus and compared with heuristic method using the contrast concept. Experimental result shows the proposed approach can give a feature ranking, select the features, and improve the system performance.

• Genomics & Informatics
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• v.1 no.1
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• pp.32-39
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• 2003

We present a latent variable model-based approach to the analysis of gene expression patterns, coupled with topographic clustering. Aspect model, a latent variable model for dyadic data, is applied to extract latent patterns underlying complex variations of gene expression levels. Then a topographic clustering is performed to find coherent groups of genes, based on the extracted latent patterns as well as individual gene expression behaviors. Applied to cell cycle­regulated genes of the yeast Saccharomyces cerevisiae, the proposed method could discover biologically meaningful patterns related with characteristic expression behavior in particular cell cycle phases. In addition, the display of the variation in the composition of these latent patterns on the cluster map provided more facilitated interpretation of the resulting cluster structure. From this, we argue that latent variable models, coupled with topographic clustering, are a promising tool for explorative analysis of gene expression data.

• Korea Journal of Hospital Management
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• v.9 no.1
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• pp.95-114
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• 2004

The purpose of this study was to identify the relationship between organizational culture based on the competing values approach, human resource management practices and organizational performance at a hospital. Participants were 138 employee in a general hospital. Data were collected during May, 2003 using four structured instruments. The data were analyzed using Chi-square test, One-way ANOVA, $scheff{\acute{e}}$ test and Cluster analysis. Three clusters were derived from cluster analysis. The first cluster consisted of cultures which were mixed developmental, consensual, hierarchial and rational culture equivalently. The second cluster consisted of the weak cultures, which was lower score than other clusters. The third cluster consisted of strong comprehensive cultures, which had higher score than other clusters. In the three clusters, hierarchial and rational culture were superior. The difference between human resource management practices and organizational commitment in organizational performance according to organizational culture clusters was found to be statistically significant. The cluster which had strong comprehensive cultures, in contrast to other clusters, more significantly affects on human resource management practices and organizational commitment. However, the strength of organizational culture does not have a significant effect on customer oriented service performance in organizational performance. These results showed that types of organizational culture were significantly related to human resource management practices and organizational commitment, and understanding the existing culture is essential to develop the organization of hospitals.