• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.4
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• pp.1237-1255
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• 2014

In wireless sensor networks (WSNs), hierarchical clustering is an efficient approach for lower energy consumption and extended network lifetime. In cluster-based multi-hop communications, a cluster head (CH) closer to the sink is loaded heavier than those CHs farther away from the sink. In order to balance the energy consumption among CHs, we development a novel cluster-based routing protocol for corona-structured wireless sensor networks. Based on the relaying traffic of each CH conveys, adequate radius for each corona can be determined through nearly balanced energy depletion analysis, which leads to balanced energy consumption among CHs. Simulation results demonstrate that our clustering approach effectively improves the network lifetime, residual energy and reduces the number of CH rotations in comparison with the MLCRA protocols.

• 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.

• Publications of The Korean Astronomical Society
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• v.30 no.2
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• pp.275-278
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• 2015

We studied a cluster family in the northern part of the Carina Nebula (NGC 3372) a group of clusters near NGC 3324 (Tr 15, NGC 3293, Loden 165, Loden 153 and IC 2581). We used data from UCAC4 to determine the cluster's membership and the near infrared CMDs of each cluster. We analyzed the spatial density and elongation as a function of radius for each cluster and found a possible interaction between NGC 3293 and Loden153. However, the shape distortion of NGC 3324 cannot be evaluated because of the inhomogenity in the coverage of UCAC4 in the east part of NGC 3324.

• Journal of Agricultural Extension & Community Development
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• v.29 no.4
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• pp.191-201
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• 2022

This study aims to segment the rural tourists markets according to benefits sought after the COVID-19 outbreak. Data were collected from 284 usable visits in 20 rural tourism village. Results show that it was classified into three clusters from factor-cluster analysis, The first cluster was 'negative participation type', and the overall pursuing benefit factor was low. The second cluster was 'complex pursuit type', and all the pursuing benefit factors were higher than the average. The third cluster was 'experience-seeking type', and the benefits of pursuing rural experiences, special experiences, and intimacy were high. Each cluster showed differences in educational background, age, residential area, type of visit, awareness, satisfaction, and behavioral intention of rural tourism villages.

• The KIPS Transactions:PartB
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• v.18B no.2
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• pp.67-72
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• 2011

Single nucleotide polymorphisms (SNPs) are a very important tool for the study of human genome structure. Cluster analysis of the large amount of gene expression data is useful for identifying biologically relevant groups of genes and for generating networks of gene-gene interactions. In this paper we compared the clusters of SNPs within asthma group and normal control group obtained by using hierarchical cluster analysis method with entropy distance. It appears that the 5-cluster collections of the two groups are significantly different. We searched the best set of SNPs that are useful for diagnosing the two types of asthma using representative SNPs of the clusters of the asthma group. Here support vector machines are used to evaluate the prediction accuracy of the selected combinations. The best combination model turns out to be the five-locus SNPs including one on the gene ALOX12 and their accuracy in predicting aspirin tolerant asthma disease risk among asthmatic patients is 66.41%.

• Korean Journal of Human Ecology
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• v.20 no.3
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• pp.677-689
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• 2011

The principal objective of this study was to evaluate the consumption behavior and perceptions of environmentally-friendly agricultural products (EAPs) according to the lifestyles of housewives in the Jeonbuk area, Korea. Self-administered questionnaires were collected from 267 housewives. Frequency analysis, chi-square, one-way ANOVA, factor analysis, and cluster analysis were used to analyze the data. Three clusters were obtained from the cluster analysis of LOHAS and wellbeing-related lifestyle: Cluster 1 "LOHAS-pursuit group", Cluster 2 "wellbeing-progress group", Cluster 3 "Utility-pursuit group". Of the housewives who were of LOHAS-pursuit group, about 50% were over 40 years old and had a professional job with a high household income. They had a high level of understanding about EAPs and purchased the highest percentage of EAPs among the groups. The housewives who were of the wellbeing-progress group, over 83% were between the ages of 30 and 40. Their consumption behaviors were very similar with that of the LOHAS-pursuit group, but the household income was lower. Of the housewives who were of the utility-pursuit group, about 63% under 30 years old. Their household income and level of understanding about EAPs were the lowest among the groups. They less interest in EAPs in comparison with other groups. For housewives' to choose EAPs properly, information and consumer education on these products, according to their lifestyles is necessary.

• Journal of the East Asian Society of Dietary Life
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• v.26 no.5
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• pp.400-406
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• 2016

This study used K-mean cluster analysis to evaluate the preference and satisfaction according to consumption behavior of naturally fermented bread products among customers residing in the Seoul area. Naturally fermented bread products were best recognized as "great nutrients for good health" ($3.91{\pm}0.87$). The preference for naturally fermented bread products was due to "good taste and flavor" ($3.39{\pm}0.95$), and customers with "intention to purchase" showed a mean of $3.21{\pm}0.94$. The overall satisfaction for naturally fermented bread products was $3.26{\pm}0.75$. Among the specific categories that contributed to this overall satisfaction, "quality" showed the highest satisfaction with $3.43{\pm}0.77$, whereas "price" ($2.77{\pm}0.76$) and "variety" ($2.77{\pm}0.75$) exhibited the lowest. Among the items to modify for naturally fermented bread products, "variety" was the most important item (21.8%), followed by "lower price" and "convenience of purchase" at 19.7% and 17.9%, respectively. In K-mean cluster analysis, customers who frequently visited the bakery and purchased naturally fermented bread products (cluster 1) expressed strong preference, satisfaction, and consumption behavior. Furthermore, these customers expressed high satisfaction in "quality", "convenience of purchase", and "variety" of naturally fermented bread products.

• Journal of Environmental Health Sciences
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• v.33 no.1 s.94
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• pp.49-56
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• 2007

The purpose of this study was to survey the distribution patterns of volatile organic compounds(VOCs) and formaldehyde in the various indoor environments using cluster analysis. We investigated VOCs and formaldehyde in subway stations, underground shopping areas, medical centers, maternity recuperation centers, public childcare centers, large stores, funeral houses, and indoor parking lots from June,2005 to May,2006. Concentration of TVOCs in maternity recuperations was 2,605.7 ${\mu}g/m^3$ that was higher than the guideline and other facilities. TVOCs in public childcare centers was 1,951.6 ${\mu}g/m^3$ also it exceeded the guideline. Moreover, concentration of TVOCs in every facility exceeded the guideline of Department of Environment, Korea. In case of formaldehyde, mean concentration, 336.5 ${\mu}g/m^3$, in only public childcare centers exceeded the 120 ${\mu}g/m^3$ of the guideline. Finally, by applying cluster analysis, three pattterns of the indoor air pollutions were distinguished. In the results of analysis, concentrations of TVOCs and formaldehyde of cluster 3 were higher than cluster 1 and 2 that were 2,561.4 ${\mu}g/m^3$ and 184.9 ${\mu}g/m^3$, respectively.

• Smart Media Journal
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• v.10 no.3
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• pp.23-30
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• 2021

Although the manufacturing time series data clustering technique is an important grouping solution in the field of detecting and improving manufacturing large data-based equipment and process defects, it has a disadvantage of low accuracy when applying the existing static data target clustering technique to time series data. In this paper, an evolutionary computation-based time series cluster analysis approach is presented to improve the coherence of existing clustering techniques. To this end, first, the image shape resulting from the manufacturing process is converted into one-dimensional time series data using linear scanning, and the optimal sub-clusters for hierarchical cluster analysis and split cluster analysis are derived based on the Pearson distance metric as the target of the transformation data. Finally, by using a genetic algorithm, an optimal cluster combination with minimal similarity is derived for the two cluster analysis results. And the performance superiority of the proposed clustering is verified by comparing the performance with the existing clustering technique for the actual manufacturing process image.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.26 no.1
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• pp.17-33
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• 2023

Disasters in coastal regions are a constant source of damage due to their uncertainty and complexity, leading to the proposal of green infrastructure as a nature-based solution that incorporates the concept of resilience to address the limitations of traditional grey infrastructure. This study analyzed trends in research related to coastal disasters and green infrastructure by conducting a co-occurrence keyword analysis of 2,183 articles collected from the Web of Science (WoS). The analysis resulted in the classification of the literature into four clusters. Cluster 1 is related to coastal disasters and tsunamis, as well as predictive simulation techniques, and includes keywords such as surge, wave, tide, and modeling. Cluster 2 focuses on the social system damage caused by coastal disasters and theoretical concepts, with keywords such as population, community, and green infrastructure elements like habitat, wetland, salt marsh, coral reef, and mangrove. Cluster 3 deals with coastal disaster-related sea level rise and international issues, and includes keywords such as sea level rise (or change), floodplain, and DEM. Finally, cluster 4 covers coastal erosion and vulnerability, and GIS, with the theme of 'coastal vulnerability and spatial technique'. Keywords related to green infrastructure in cluster 2 have been continuously appearing since 2016, but their focus has been on the function and effect of each element. Based on this analysis, implications for planning and management processes using green infrastructure in response to coastal disasters have been derived. This study can serve as a valuable resource for future research and policy in responding to and managing various disasters in coastal regions.