• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.894-896
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• 2010

In mobile wireless sensor network, Whole nodes can move. In mobile wireless sensor network based on clustering, there can be frequent re-configuration of cluster according to frequent changes of location. Frequent reconfiguration of the cluster cause a lot of power consumption and data loss. To solve this problem, we suggest relay method for sending reliable data and decreases a number of re-configuration of cluster using relay node.

• Journal of Veterinary Science
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• v.22 no.6
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• pp.88.1-88.6
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• 2021

Toxoplasma gondii consists of three genotypes, namely genotype I, II and III. Based on its virulence, T. gondii can be divided into virulent and avirulent strains. This study intends to evaluate an alternative method for predicting T. gondii virulence using hierarchical cluster analysis based on complete coding sequences (CDS) of sag1, gra7 and rop18 genes. Dendrogram was constructed using UPGMA with a Kimura 80 nucleotide distance measurement. The results showed that the prediction errors of T. gondii virulence using sag1, gra7 and rop18 were 7.41%, 6.89% and 9.1%, respectively. Analysis based on CDS of gra7 and rop18 was able to differentiate avirulent strains into genotypes II and III, whereas sag1 failed to differentiate.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.4
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• pp.1001-1008
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• 2015

Mobile Ad hoc Network(MANET) consists of a node that has mobility. In MANET, the node has routing, the node builds a network of their own, no dependent infrastructure. Topology are exchanged due to node mobility in MANET. For reducing the change of topology, hierarchical network algorithm has been investigated. In hierarchical network, cluster member node communicates through cluster head node. When the load-balancing of cluster head node is exceed, assigned cluster member node can't communicate with base station. To solve this problem, we proposed Load Tolerance algorithm. The proposed algorithm, when cluster member node can't send a message by cluster head node that exceed load-balancing, then the cluster member node sends a message by selected load tolerance node. Through a simulation, the proposed algorithm improves packet delivery ratio in cluster routing.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.31 no.3
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• pp.79-99
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• 2020

The purpose of this study is to investigate the model of cluster analysis techniques for grouping public libraries and analyze their characteristics. Statistical data of public libraries of the National Library Statistics System were used, and three models of cluster analysis were applied. As a result of the study, cluster analysis was conducted based on the size of public libraries, and it was largely divided into two clusters. The size of the cluster was largely skewed to one side. For grouping based on size, the ward method of hierarchical cluster analysis and the k-means cluster analysis model were suitable. Three suggestions were presented as implications of the grouping method of public libraries. First, it is necessary to collect library service-related data in addition to statistical data. Second, an analysis model suitable for the data set to be analyzed must be applied. Third, it is necessary to study the possibility of using cluster analysis techniques in various fields other than library grouping.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2002.05a
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• pp.195-200
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• 2002

ART (Adaptive Resonance Theory [1]) neural network and its variations perform non-hierarchical clustering by unsupervised learning. We propose a scheme "arboART" for hierarchical clustering by using several ART1.5-SSS networks. It classifies multidimensional vectors as a cluster tree, and finds features of clusters. The Basic idea of arboART is to use the prototype formed in an ART network as an input to other ART network that has looser distance criteria (Ishihara, et al., [2,3]). By sending prototype vectors made by ART to one after another, many small categories are combined into larger and more generalized categories. We can draw a dendrogram using classification records of sample and categories. We have confirmed its ability using standard test data commonly used in pattern recognition community. The clustering result is better than traditional computing methods, on separation of outliers, smaller error (diameter) of clusters and causes no chaining. This methodology is applied to Kansei evaluation experiment data analysis.

• International Journal of Internet, Broadcasting and Communication
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• v.9 no.4
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• pp.51-58
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• 2017

This paper deals with the improvement of cluster head selection method in L-SEP for heterogeneous nodes among hierarchical routing protocols of wireless sensor network. Wireless sensor networks are classified into homogeneous and heterogeneous network. In heterogeneous network, SEP, L-SEP are mainly used because cluster head selection probability is different depending on node type. But, since protocol based on SEP has different cluster head selection probabilities depending on the node type, clusters that transmit data inefficiently can be formed. to improve this, it is necessary to select the cluster head that minimizes the transmission distance of member node and the cluster head. Therefore, we propose a protocol that improve the cluster head selection method.

• The Journal of Korean Association of Computer Education
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• v.22 no.5
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• pp.51-65
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• 2019

This study aims to provide educational implications for more strategic online software education by the types of online learning according to learners' self-regulated learning characteristics in the online software education environment and examining the characteristics of each type. For this, variables related to self-regulated learning characteristic were extracted from the log data of 809 students participating in the online software learning program of K University, and then analyzed using hierarchical cluster analysis. Based on hierarchical cluster analysis learner clusters according to the characteristics of self-regulated learning were derived and the differences between learners' learning characteristics and learning results according to cluster types were examined. As a result, the types of self-regulated learning of online software learners were classified as 'high level self-regulated learning type (group 1)', 'medium level self-regulated learning type (group 2)', and 'low level self-regulated learning type (group 3)'. The achievement level was found to be highest in 'high-level self-regulated learning type (group 1)' and 'low-level self-regulated learning type (group 3)' was the lowest. Based on these results, the implications for effective online software education were suggested.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.527-530
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• 2010

WSN is composed of a lot of small sensors with the limited hardware resources. In WSN, at the initial stage, sensor nodes are randomly deployed over the region of interest, and self-configure the clustered networks by grouping a bunch of sensor nodes and selecting a cluster header among them. Specially, in WSN environment, in which the administrator's intervention is restricted, the self-configuration capability is essential to establish a power-conservative WSN which provides broad sensing coverage and communication coverage. In this paper, we propose a communication coverage-aware cluster head election algorithm for Herearchical WSNs which consists of communication coverage-aware of the Base station is the cluster head node is elected and a clustering.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.510-513
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• 2010

In hierarchical wireless sensor network, Sensor nodes forming a cluster with a hierarchy. And there are being study for balanced energy consumption between cluster nodes. When forming network routing path, if there are configured incorrectly then it can be wasting energy. In this paper to solve these problem, We propose that it can consider sensor's communication range to create minimum hop layer when cluster heads configure routing path.

• Development and Reproduction
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• v.18 no.3
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• pp.167-172
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• 2014

In the present study, muscle tissues were obtained separately from individuals from Atlantic hairtail population (AHP), Gunsan hairtail population (GHP) and Chinese hairtail population (CHP), respectively. The seven decamer primers were used to generate the shared loci, specific, unique shared loci to each population and shared loci by the three hairtail populations. Here, averagely, a decamer primer generated 64.7 amplified products per primer in the AHP population, 55.7 in GHP population and 56.4 in CHP population. The number of unique shared loci to each population and number of shared loci by the three populations generated by genetic analysis using 7 decamer primers in AHP, GHP and CHP population. 119 unique shared loci to each population, with an average of 17 per primer, were observed in the AHP population, and 28 loci, with an average of 4 per primer, were observed in the CHP population. The hierarchical dendrogram point out three main branches: cluster 1 (ATLANTIC 01 ~ ATLANTIC 07), cluster 2 (GUNSAN 08 ~ GUNSAN 14) and cluster 3 (CHINESE 15 ~ CHINESE 21). The shortest genetic distance displaying significant molecular difference was between individuals' CHINESE no. 16 and CHINESE no. 18 (0.045). In the long run, individual no. 01 of the AHP population was most distantly related to CHINESE no. 19 (genetic distance = 0.430). Consequently, PCR analysis generated on the genetic data displayed that the geographic AHP population was widely separated from CHP population, while individuals of CHP population were fairly closely related to those of GHP population.