• Transactions of the Korean Society of Mechanical Engineers B
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• v.37 no.3
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• pp.259-266
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• 2013

An automated cell tracking system is used to automatically analyze and track the changes in cell behavior in time-lapse cell images acquired using a microscope with a cell culture. Clustering is the partial overlapping of neighboring cells in the process of cell change. Separating clusters into individual cells is very important for cell tracking. In this study, we proposed an algorithm for separating clusters by using ellipse fitting based on a direct least square method. We extracted the contours of clusters, divided them into line segments, and then produced their fitted ellipses using a direct least square method for each line segment. All of the fitted ellipses could be used to separate their corresponding clusters. In experiments, our algorithm separated clusters with average precisions of 91% for two overlapping cells, 84% for three overlapping cells, and about 73% for four overlapping cells.

• The KIPS Transactions:PartB
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• v.19B no.1
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• pp.53-62
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• 2012

Clustering technology is used to deal efficiently with many searched documents in information retrieval system. But the accuracy of the clustering is satisfied to the requirement of only some domains. This paper proposes two methods to increase accuracy of the clustering. We define a common-word, that is frequently used but has low weight during clustering. We propose the method that automatically gathers the common-word and calculates its weight from the searched documents. From the experiments, the clustering error rates using the common-word is reduced to 34% compared with clustering using a stop-word. After generating first clusters using average link clustering from the searched documents, we propose the algorithm that reevaluates the similarity between document and clusters and reclassifies the document into more similar clusters. From the experiments using Naver JiSikIn category, the accuracy of reclassified clusters is increased to 1.81% compared with first clusters without reclassification.

• Journal of the Economic Geographical Society of Korea
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• v.16 no.2
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• pp.293-309
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• 2013

Innovation clusters have different factors depending on different stages. Innovation clusters in Gyeonggi now are early stages, which are necessary to investigate factors so that they go into upstages. Silicon Valley is known as one of the best innovation clusters, which are now represented as the forms of related variety. The purpose of the paper is to investigate current situation of innovation clusters in Silicon Valley and suggest appropriate policies for the development of innovation clusters in Gyeonggi. In order to do this, we visit several representative institutions regarding infra, human-training, industry-academic-institution cooperation, start-up assistance and local government. Throughout the case study, we propose implications, and produce policy tasks for the development of cluster policy in Gyeonggi.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.2
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• pp.1-8
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• 2018

K-means algorithm is one of the most popular and widely used clustering method because it is easy to implement and very efficient. However, this method has the limitation to be used with fixed number of clusters because of only considering the intra-cluster distance to evaluate the data clustering solutions. Silhouette is useful and stable valid index to decide the data clustering solution with number of clusters to consider the intra and inter cluster distance for unsupervised data. However, this valid index has high computational burden because of considering quality measure for each data object. The objective of this paper is to propose the fast and simple speed-up method to overcome this limitation to use silhouette for the effective large-scale data clustering. In the first step, the proposed method calculates and saves the distance for each data once. In the second step, this distance matrix is used to calculate the relative distance rate ($V_j$) of each data j and this rate is used to choose the suitable number of clusters without much computation time. In the third step, the proposed efficient heuristic algorithm (Group search optimization, GSO, in this paper) can search the global optimum with saving computational capacity with good initial solutions using $V_j$ probabilistically for the data clustering. The performance of our proposed method is validated to save significantly computation time against the original silhouette only using Ruspini, Iris, Wine and Breast cancer in UCI machine learning repository datasets by experiment and analysis. Especially, the performance of our proposed method is much better than previous method for the larger size of data.

• Bulletin of the Korean Chemical Society
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• v.12 no.6
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• pp.606-612
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• 1991

We have carried out an extended Huckel calculation to rationalize the role of $CuO_3$ chains and the size effect of the charged model clusters for the following charged model culsters : ${{Cu_6}{O_{21}}^{28-},\;{{Cu_6}{O_{22}}^{30-}\;,{{Cu_9}{O_{30}}^{39-}\;,{{Cu_9}{O_{32}}^{43-}\;,{{Cu_{12}{O_{38}}^{48-}\;,{{Cu_{15}{O_{50}}^{65-}\;,{{Cu_{18}{O_{54}}^{66-}\;,{{Cu_{18}{O_{55}}^{68-}\;,{{Cu_{24}{O_{70}}^{84-}\;and\;{{Cu_{27}{O_{78}}^{93-}$ for high-$T_c$ superconductor $YBa_2Cu_3O_7$: ${{Cu_6}{O_{18}}^{22-}\;,{{Cu_9}{O_{26}}^{31-}}\;,{{Cu_{12}{O_{32}}^{36-}\;,{{Cu_{15}{O_{42}}^{49-}\;,{{Cu_{18}{O_{46}}^{50-}\;,{{Cu_{24}{O_{60}}^{64-}\;and\;{{Cu_{27}{O_{66}}^{69-}$ for insulator $YBa_2Cu_3O_6$. The results show that the electronic structures and properties of the charged model clusters relating to high-$T_c$ superconductor are very sensitive to the size change of the clusters with various environmental effects, wherease those of the charged model clusters for insulator $YBa_2Cu_3O_6$ are monotonous to the size change. The $CuO_3$ chains along the b-direction may yield cooperative electronic coupling with the $CuO_2$ layers in determining both conducting and superconducting properties of $YBa_2Cu_3O_{7-x}$ system.

• Journal of Microbiology and Biotechnology
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• v.29 no.5
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• pp.794-808
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• 2019

Bacillus velezensis strain WRN014 was isolated from banana fields in Hainan, China. Bacillus velezensis is an important member of the plant growth-promoting rhizobacteria (PGPR) which can enhance plant growth and control soil-borne disease. The complete genome of Bacillus velezensis WRN014 was sequenced by combining Illumina Hiseq 2500 system and Pacific Biosciences SMRT high-throughput sequencing technologies. Then, the genome of Bacillus velezensis WRN014, together with 45 other completed genome sequences of the Bacillus velezensis strains, were comparatively studied. The genome of Bacillus velezensis WRN014 was 4,063,541bp in length and contained 4,062 coding sequences, 9 genomic islands and 13 gene clusters. The results of comparative genomic analysis provide evidence that (i) The 46 Bacillus velezensis strains formed 2 obviously closely related clades in phylogenetic trees. (ii) The pangenome in this study is open and is increasing with the addition of new sequenced genomes. (iii) Analysis of single nucleotide polymorphisms (SNPs) revealed local diversification of the 46 Bacillus velezensis genomes. Surprisingly, SNPs were not evenly distributed throughout the whole genome. (iv) Analysis of gene clusters revealed that rich gene clusters spread over Bacillus velezensis strains and some gene clusters are conserved in different strains. This study reveals that the strain WRN014 and other Bacillus velezensis strains have potential to be used as PGPR and biopesticide.

• Journal of Microbiology and Biotechnology
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• v.31 no.1
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• pp.8-15
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• 2021

More and more available fungal genome sequence data reveal a large amount of secondary metabolite (SM) biosynthetic 'dark matter' to be discovered. Heterogeneous expression is one of the most effective approaches to exploit these novel natural products, but it is limited by having to clone entire biosynthetic gene clusters (BGCs) without errors. So far, few effective technologies have been developed to manipulate the specific large DNA fragments in filamentous fungi. Here, we developed a fungal BGC-capturing system based on CRISPR/Cas9 cleavage in vitro. In our system, Cas9 protein was purified and CRISPR guide sequences in combination with in vivo yeast assembly were rationally designed. Using targeted cleavages of plasmid DNAs with linear (8.5 kb) or circular (8.5 kb and 28 kb) states, we were able to cleave the plasmids precisely, demonstrating the high efficiency of this system. Furthermore, we successfully captured the entire Nrc gene cluster from the genomic DNA of Neosartorya fischeri. Our results provide an easy and efficient approach to manipulate fungal genomic DNA based on the in vitro application of Cas9 endonuclease. Our methodology will lay a foundation for capturing entire groups of BGCs in filamentous fungi and accelerate fungal SMs mining.

• Journal of Korea Multimedia Society
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• v.8 no.12
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• pp.1623-1630
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• 2005

Adaptive modulation and coding (AMC), which has a number of variation levels in accordance with the fading channel variation, is a promising technique for communication systems. In this paper, we present an AMC method using the cluster in OFDM system for bandwidth efficiency and performance improvement. The AMC schemes applied into each cluster or some clusters are determined by the minimum or the average SNR value among all the sub carriers within the corresponding cluster. It is important to find the optimal information on cluster because AMC performance can be varied according to the number and position of cluster. It is shown by computer simulation that the AMC method outperforms the fixed modulation in terms of bandwidth efficiency and its performance can be determined by the position and number of clusters.

• Journal of Communications and Networks
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• v.16 no.3
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• pp.305-310
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• 2014

Optimal position of access point (AP) is important for multi-gigabit wireless transmission in terahertz (THz) wireless local area network (WLAN)-type applications, where there exist the THz characteristic multiple clusters in channel propagation. By considering the multiple clusters in THz indoor communications, this paper investigates the optimal AP position when two APs are issued for increasing the system capacity. Numerical results reveal that the central position of each AP within each half service region, which offers the shortest cumulated path length for line-of-sight paths, is optimal to achieve the maximal system capacity.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.3
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• pp.472-478
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• 2012

The inspection machine in PCB (printed circuit board) assembly line checks assembly errors by inspecting the images inside of the component inspection region. The component inspection region consists of region of component package and region of soldering. It is necessary to extract the regions automatically for auto-teaching system of the inspection machine. We propose an image segmentation method to extract the component inspection regions automatically from images of PCB. The acquired image is transformed to HSI color model, and then segmented by several regions by clustering method. We develop a modified K-means algorithm to increase the accuracy of extraction. The heuristics generating the initial clusters and merging the final clusters are newly proposed. The vertical and horizontal projection is also developed to distinguish the region of component package and region of soldering. The experimental results are presented to verify the usefulness of the proposed method.