• Journal of Information Processing Systems
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• v.20 no.2
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• pp.185-199
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• 2024

In this paper, an improved automated spectral clustering (IASC) algorithm is proposed to address the limitations of the traditional spectral clustering (TSC) algorithm, particularly its inability to automatically determine the number of clusters. Firstly, a cluster number evaluation factor based on the optimal clustering principle is proposed. By iterating through different k values, the value corresponding to the largest evaluation factor was selected as the first-rank number of clusters. Secondly, the IASC algorithm adopts a density-sensitive distance to measure the similarity between the sample points. This rendered a high similarity to the data distributed in the same high-density area. Thirdly, to improve clustering accuracy, the IASC algorithm uses the cosine angle classification method instead of K-means to classify the eigenvectors. Six algorithms-K-means, fuzzy C-means, TSC, EIGENGAP, DBSCAN, and density peak-were compared with the proposed algorithm on six datasets. The results show that the IASC algorithm not only automatically determines the number of clusters but also obtains better clustering accuracy on both synthetic and UCI datasets.

• Journal of the Korean Statistical Society
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• v.15 no.1
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• pp.1-8
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• 1986

The k-medians clustering method is considered to partition observations into k clusters. Consistency and advantage of bootstrap confidence sets of k optimal cluster centers are discussed. The k-medians and k-means clustering methods are compared by using actual data sets.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.11
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• pp.5015-5024
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• 2012

This research focused on the strategy formulation for the Innopolis as a Global Innovation Cluster. The study was performed based on both theoretical study and qualitative study approaches. Particularly, scenario planning as a foresight method was used for the strategy formulation. The major determinants for the success of the Innopolis can be summarized as follows; the enhancement of the host institution for the development of the innovation cluster, the relational capability of the Innopolis among daedeok, gwangju, daegu and the alignment and cooperation of the International Science & Business Belt. In terms of the needs of times, this study regarding the strategy for the formation of the Innopolis as the global innovation cluster is anticipated to be a good reference for policy makers and researchers in coming years.

• International Journal of Internet, Broadcasting and Communication
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• v.9 no.2
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• pp.64-69
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• 2017

The abstract should summarize the contents of the paper and written below the author information. Use th In Wide-area Wireless Sensor Networks, network lifetime is short due to energy consumption due to transmission distance. To improve this, we divide the sensor field into layers and reduce transmission distance through multi-hop transmission. However, there is a problem in that the transmission rate drops because there is no Cluster Head in the layer, or the transmission distance increases due to the layer, and energy is wasted. There are DL-LEACH and EDL-LEACH as Protocols to improve this. DL-LEACH uses either single-hop transmission or multi-hop transmission depending on the situation. As a result, the transmission distance is optimized, thereby reducing energy consumption. In case of EDL-LEACH, it is proposed to improve the data rate in DL-LEACH. It is the same as DL-LEACH, but the Cluster Head is mandatory for all layers to improve the transmission rate. Although there is no Cluster Head for each layer, the transmission rate is improved, but the network life is shortened. In this paper, we try to improve the network lifetime while maintaining the EDL-LEACH transmission rate. The shortened network lifetime is due to Cluster Head overload near the base station. To improve this, the Cluster Head distribution method is improved and the network lifetime is improved.

• Applied Chemistry for Engineering
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• v.7 no.2
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• pp.321-325
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• 1996

Quantum chemical calculations are used to characterize the decomposition of nitrogenmonoxide over $Cu^{n+}$-Y zeolite. The method of theoretical calculations, such as CNDO/2, have been applied to cluster models representing cation sites in zeolite to obtain total energies, LUMO energies, and Wiberg bond orders. The calculated total energies and bond orders of cluster models showed the reaction mechanism of NO decomposition over $Cu^{n+}$ site in zeolite framework. The suggested cluster models of varying Si/Al ratios studied with exchange cations in the $Cu^+$ and in the $Cu^{2+}$ states. And the calculated LUMO energies can predict L acidifies of cluster models. The results from these experiments showed the possibility of the mechanism of NO decomposition, progressing adsorption of NO, conversion to $N_2$ and $O_2$, desorption of $N_2$ and $O_2$ in sequence. The L acidity of $Cu^{2+}$ ion in cation site is more strong than $Cu^+$.

• Journal of Environmental Science International
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• v.15 no.12
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• pp.1125-1139
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• 2006

The cluster analysis of diurnal precipitation patterns is performed by using daily precipitation of 59 stations in South Korea from 1973 to 1996 in four seasons of each year. Four seasons are shifted forward by 15 days compared to the general ones. Number of clusters are 15 in winter, 16 in spring and autumn, and 26 in summer, respectively. One of the classes is the totally dry day in each season, indicating that precipitation is never observed at any station. This is treated separately in this study. Distribution of the days among the clusters is rather uneven with rather low area-mean precipitation occurring most frequently. These 4 (seasons)$\times$2 (wet and dry days) classes represent more than the half (59 %) of all days of the year. On the other hand, even the smallest seasonal clusters show at least $5\sim9$ members in the 24 years (1973-1996) period of classification. The cluster analysis is directly performed for the major $5\sim8$ non-correlated coefficients of the diurnal precipitation patterns obtained by factor analysis In order to consider the spatial correlation. More specifically, hierarchical clustering based on Euclidean distance and Ward's method of agglomeration is applied. The relative variance explained by the clustering is as high as average (63%) with better capability in spring (66%) and winter (69 %), but lower than average in autumn (60%) and summer (59%). Through applying weighted relative variances, i.e. dividing the squared deviations by the cluster averages, we obtain even better values, i.e 78 % in average, compared to the same index without clustering. This means that the highest variance remains in the clusters with more precipitation. Besides all statistics necessary for the validation of the final classification, 4 cluster centers are mapped for each season to illustrate the range of typical extremities, paired according to their area mean precipitation or negative pattern correlation. Possible alternatives of the performed classification and reasons for their rejection are also discussed with inclusion of a wide spectrum of recommended applications.

• 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%.

• Journal of the Korea Society of Computer and Information
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• v.16 no.2
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• pp.101-111
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• 2011

A new MAC protocol, MT-MAC(Multi-Tier Medium Access Control) by name, is proposed for dense sensor networks. Depending on the density of nodes in a virtual cluster, the cluster header performs the splitting to several tiers in nodes of virtual cluster. MT-MAC split the tiers to use modfied-SYNC message after receiving the beacon message from the cluster header. Because only the sensor nodes in the same tier communicate each other, less power is consumed and longer network life time is guaranteed. By a simulation method with NS-2, we evaluated our protocol. In dense nodes environments, MT-MAC protocol shows better results than S-MAC in terms of packet delivery rates throughput and energy consumption.

• Korean Journal of Microbiology
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• v.38 no.4
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• pp.299-305
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• 2002

Clinically isolated Salmonella Enteritidis strain has a multi drug resistance plasmid, which confers ampicillin, chloramphe-nicol, sulfonamide, streptomycin and tetracycline, named pCAST2. We cloned a 7 kb Sacl fragment of pCAST2 which has sulfonamide, streptomycin and tetracycline resistance genes. The 7 kb SacI fragment showed the organization of sulII-strA-strB-tetR-tetA gene cluster which is different from the other clusters reported previously. In this study, we presented the method to detect this cluster by PCR analysis and showed that this cluster was found in Salmonella strains occurred sporadically at Kyungpook province in 2002.

• Journal of Internet Computing and Services
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• v.16 no.2
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• pp.7-17
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• 2015

To provide scalability, wireless sensor network has cluster-based architecture. Wireless sensor network can be implemented based on the IEEE 802.15.4 which is exploited in 2.4GHz ISM frequency band. Since this frequency band is used for various data communication, network status of wireless sensor networks frequently changes according to wireless environment. Thus, wireless channel selection to avoid reduction of transmission efficiency is required. This paper estimates network status using the information that a cluster-head collects in a cluster. Through objective function with throughput, RSSI level and reliability as input parameters, this paper proposes proper wireless channel selection. Simulation results show that the proposed method maintains transmission efficiency even though network status changes.