• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 한국정보통신학회 2014년도 춘계학술대회
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• pp.781-783
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• 2014

Mobile ad hoc network(MANET) consists of node that has mobility. MANET has increased overhead that caused by frequent topology changes. For reducing overhead, hierarchical network that communicates through cluster head node has been researched. When traffic is concentrated on cluster head node, cluster member node can't send message. To solve this problem, we proposed Step Parent algorithm. Proposed algorithm, cluster member node checks traffic of cluster head node using route path of other cluster head node in efficient coverage area. When cluster head node has increased traffic, cluster member node make a new route path by route path by routing path to another cluster head node. So cluster member node sends a message to destination node, we check improving delivery ratio.

• Journal of Environmental Health Sciences
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• 제46권6호
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• pp.726-734
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• 2020

Objectives: The aim of this study was to analyze and classify the characteristics of potential damage from hazardous chemical accidents in 229 administrative units in South Korea by reflecting the social and environmental characteristics of areas where chemical accidents can occur. Methods: A number of indicators were selected through preceding studies. Factor analysis was performed on selected indicators to derive factors, and cluster analysis was performed based on the factor scores. Results: As a result of the cluster analysis, 229 administrative units were divided into three clusters, and it was confirmed that each cluster had its own characteristics. Conclusions: The first cluster, "areas at risk of accident occurrence and spread of damage" was a type with a high potential for accident damage and a high density of hazardous facilities. The second cluster, "Urban infrastructure damage hazard areas" appeared to be a cluster with high urban development characteristics. Finally, the third cluster 'Urban and environmental damage hazard areas' appeared to be a cluster with an excellent natural environment. This study went further from the qualitative discussion related to existing chemical accidents to identify and respond to accident damage by reflecting the social and environmental characteristics of the region. Distinct from the previous studies related to the causes of accidents and the response system, it is meaningful to conduct empirical research focusing on the affected areas by analyzing the possibility of accident damage in reflection of the social and environmental characteristics of the community.

• International Journal of Internet, Broadcasting and Communication
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• 제13권3호
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• pp.178-192
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• 2021

File system forensics typically focus on the contents or timestamps of a file, and it is common to work around file/directory centers. But to recover a deleted file on the disk or use a carving technique to find and connect partial missing content, the evidence must be analyzed using cluster-centered analysis. Forensics tools such as EnCase, TSK, and X-ways, provide a basic ability to get information about disk clusters, but these are not the core functions of the tools. Alternatively, Sysinternals' DiskView tool provides a more intuitive visualization function, which makes it easier to obtain information around disk clusters. In addition, most current tools are for Windows. There are very few forensic analysis tools for MacOS, and furthermore, cluster analysis tools are very rare. In this paper, we developed a tool named FACT (Forensic Analyzer based Cluster Information Tool) for analyzing the state of clusters in a HFS+ file system, for digital forensics. The FACT consists of three features, a Cluster based analysis, B-tree based analysis, and Directory based analysis. The Cluster based analysis is the main feature, and was basically developed for cluster analysis. The FACT tool's cluster visualization feature plays a central role. The FACT tool was programmed in two programming languages, C/C++ and Python. The core part for analyzing the HFS+ filesystem was programmed in C/C++ and the visualization part is implemented using the Python Tkinter library. The features in this study will evolve into key forensics tools for use in MacOS, and by providing additional GUI capabilities can be very important for cluster-centric forensics analysis.

• Journal of Distribution Science
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• 제14권1호
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• pp.67-74
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• 2016

Purpose - In this paper, the degree of similarity and dissimilarity between pairs of 50 major cities in China can be shown on the basis of three evaluation variables(internet businessman index, internet shopping index and e-commerce development index). Dissimilarity distance matrix is used to analyze both similarity and dissimilarity between each fifty city in China by calculating dissimilarity as distance. Higher value signifies higher degree of dissimilarity between two cities. Cluster analysis is exploited to classify 50 cities into a number of different groups such that similar cities are placed in the same group. In addition, multidimensional scaling(MDS) technique can obtain visual representation for exploring the pattern of proximities among 50 major cities in China based on three development performance attributes. Research design, data, and methodology - This research is performed by the 2013 report provided with AliResearch in China(1/1/2013~11/30/2013) and utilized multivariate methods such as dissimilarity distance matrix, cluster analysis and MDS by using CLUSTER, KMEANS, PROXIMITIES and ALSCAL procedures in SPSS 21.0. Results - This research applies two types of cluster analysis and MDS on three development performances based on the 2013 report of Aliresearch. As a result, it is confirmed that grouping is possible by categorizing the types into four clusters which share similar characteristics. MDS is exploited to carry out positioning of both grouped locations of cluster and 50 major cities belonging to each cluster. Since all the values corresponding to Shenzhen, Guangzhou and Hangzhou(which belong to cluster 1 among 50 major cities) are very large, these cities are superior to other cities in all three evaluation attributes. Twelve cities(Beijing, ShangHai, Jinghua, ZhuHai, XiaMen, SuZhou, NanJing, DongWan, ZhangShan, JiaXing, NingBo and FoShan), which belong to cluster 3, are inferior to those of cluster 1 in terms of all three attributes, but they can be expected to be the next e-commerce revolution. The rest of major cities, in particular, which belong to cluster 4 are relatively inferior in all three attributes, so that this automatically evokes creative innovation, which leads to e-commerce development as a whole in China. In terms of internet businessman index, on the other hand, Tainan, Taizhong, and Gaoxiong(which belong to cluster 2) are situated superior to others. However, these three cities are inferior to others in an internet shopping index sense. The rest of major cities, in particular, which belong to cluster 4 are relatively inferior in all three evaluation attributes, so that this automatically evokes innovation and entrepreneurship, which leads to e-commerce development as a whole in China. Conclusions - This study suggests the implications to help e-governmental officers and companies make strategies in both Korea and China. This is expected to give some useful information in understanding the recent situation of e-commerce in China, by looking over development performances of 50 major cities. Therefore, we should develop marketing, branding and communication relevant to online Chinese consumers. One of these efforts will be incentives like loyalty points and coupons that can encourage consumers and building in-house logistics networks.

• Journal of Internet Computing and Services
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• 제9권4호
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• pp.43-50
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• 2008

Various studies are being conducted to achieve efficient routing and reduce energy consumption in wireless sensor networks where energy replacement is difficult. Among routing mechanisms, the clustering technique has been known to be most efficient. The clustering technique consists of the elements of cluster construction and data transmission. The elements that construct a cluster are repeated in regular intervals in order to equalize energy consumption among sensor nodes in the cluster. The algorithms for selecting a cluster head node and arranging cluster member nodes optimized for the cluster head node are complex and requires high energy consumption. Furthermore, energy consumption for the data transmission elements is proportional to $d^2$ and $d^4$ around the crossover region. This paper proposes a means of reducing energy consumption by increasing the efficiency of the cluster construction elements that are regularly repeated in the cluster technique. The proposed approach maintains the number of sensor nodes in a cluster at a constant level by equally partitioning the region where nodes with density considerations will be allocated in cluster construction, and reduces energy consumption by selecting head nodes near the center of the cluster. It was confirmed through simulation experiments that the proposed approach consumes less energy than the LEACH algorithm.

• Journal of the Korea Academia-Industrial cooperation Society
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• 제19권12호
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• pp.480-490
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• 2018

This study investigated the profiles of anger expression (anger control, anger in, anger out) and their variation in forms, and determined the differences in depression, aggression, and negative affect intensity of middle school students. For this purpose, the survey responses of 296 middle school students in Seoul were analyzed. The major study results are as follows. (1) Cluster analyses yielded four anger expression profiles: cluster 1 was characterized by high scores for anger control, anger in and anger out, cluster 2 by low scores for anger control, high scores for anger in and anger out, cluster 3 by low scores for anger control, anger in and anger out, and cluster 4 by low scores for anger in, high scores for anger control and anger out. (2) Between-cluster differences in depression, aggression, and negative affect intensity were all significant. The posteriori test indicated that cluster 4 was higher than the other three clusters in terms of depression. Cluster 3 was higher than the other three clusters on aggression, cluster 2 was higher than cluster 4 in terms of aggression. The interventions by aggression expression cluster are discussed and the implications of this research to education and counseling are explained.

• Journal of IKEEE
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• 제13권1호
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• pp.71-76
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• 2009

As one of the most important requirements for wireless sensor networks, prolonging network lifetime can be realized by minimizing energy consumption in cluster heads as well as sensor nodes. While most of the previous researches have focused on the energy of sensor nodes, we devote our attention to cluster heads because they are most dominant source of power consumption in the cluster-based sensor networks. Therefore, we seek to minimize energy consumption by minimizing the maximum(MINMAX) energy dissipation at each cluster heads. This work requires energy-efficient clustering of the sensor nodes while satisfying given energy constraints. In this paper, we present a constraint satisfaction modeling of cluster-based routing in a heterogeneous sensor networks because mixed integer programming cannot provide solutions to this MINMAX problem. Computational experiments show that substantial energy savings can be obtained with the MINMAX algorithm in comparison with a minimum total energy(MTE) strategy.

• Journal of Microbiology and Biotechnology
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• 제21권6호
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• pp.567-573
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• 2011

We investigated the phylogenetic diversity of ammoniaoxidizing bacteria (AOB) in Yellow Sea continental shelf sediment by the cloning and sequencing of PCR-amplified amoA and 16S rRNA genes. Phylogenetic analysis of the amoA-related clones revealed that the diversity of AOB was extremely low at the study site. The majority (92.7%) of amoA clones obtained belonged to a single cluster, environmental amoA cluster-3, the taxonomic position of which was previously unknown. Phylogenetic analysis on AOB-specific 16S rRNA gene sequences also demonstrated a very low diversity. All of the cloned 16S rRNA gene sequences comprised a single phylotype that belonged to the members of uncultured Nitrosospira cluster-1, suggesting that AOB belonging to the uncultured Nitrosospira cluster-1 could carry amoA sequences of environmental amoA cluster-3.

• Proceedings of the IEEK Conference
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• 대한전자공학회 2004년도 학술대회지
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• pp.885-889
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• 2004

Fast and high-quality document clustering algorithms play an important role in providing data exploration by organizing large amounts of information into a small number of meaningful clusters. Hierarchical clustering improves the performance of retrieval and makes that users can understand easily. For outperforming of clustering, we implemented hierarchical structure with variety and readability, by careful selection of cluster topic words and deciding the number of clusters dynamically. It is important to select topic words because hierarchical clustering structure is summarizes result of searching. We made choice of noun word as a cluster topic word. The quality of topic words is increased $33\%$ as follows. As the topic word of each cluster, the only noun word is extracted for the top-level cluster and the used topic words for the children clusters were not reused.

• Journal of the Korean Institute of Telematics and Electronics B
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• 제31B권7호
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• pp.199-210
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• 1994

Most of clustering methods usually employ a center or predefined shape of a cluster to assign the input data into the cluster. When there is no information about data set, it is impossible to predict how many clusters are to be or what shape clusters take. (the shape of clusters could not be easily represented by the center or predefined shape of clusters) Therefore, it is difficult to assign input data into a proper cluster using previous methods. In this paper, to overcome such a difficulty a cluster is to be represented as a collection of several subclusters representing boundary of the cluster. And membership functions are used to represent how much input data bllongs to subclusters. Then the position of the nearest subcluster is adaptively corrected for expansion of cluster, which the subcluster belongs to by use of a competitive learning neural network. To show the validity of the proposed method a numerical example is illustrated where FMMC(Fuzzy Min-Max Clustering) algorithm is compared with the proposed method.