• Korean Journal of Optics and Photonics
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• v.20 no.1
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• pp.16-22
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• 2009

We propose a method to convert a two-dimensional movie to a three-dimensional movie using normalized cut and optical flow. In this paper, we segment an image of a two-dimensional movie to objects first, and then estimate the depth of each object. Normalized cut is one of the image segmentation algorithms. For improving speed and accuracy of normalized cut, we used a watershed algorithm and a weight function using optical flow. We estimate the depth of objects which are segmented by improved normalized cut using optical flow. Ordinal depth is estimated by the change of the segmented object label in an occluded region which is the difference of absolute values of optical flow. For compensating ordinal depth, we generate the relational depth which is the absolute value of optical flow as motion parallax. A final depth map is determined by multiplying ordinal depth by relational depth, then dividing by average optical flow. In this research, we propose the two-dimensional/three-dimensional movie conversion method which is applicable to all three-dimensional display devices and all two-dimensional movie formats. We present experimental results using sample two-dimensional movies.

• Journal of Life Science
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• v.27 no.6
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• pp.623-631
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• 2017

In the subventricular zone (SVZ) and the subgranular zone of the brain, neurogenesis occurs throughout one's lifespan. Neural stem cells (NSCs) in these regions divide to maintain their stem cell pools as well as differentiate into neurons and glial cells. To monitor cell division, a thymidine analogue such as 5-ethynyl-2'-deoxyuridine (EdU) has been used. In some cases, EdU was applied to label newly born neurons. Here, we report about the effects of EdU on the proliferation and differentiation of NSCs cultured from mouse SVZ. First, when NSCs were cultured in a proliferation medium containing EdU for 24 hr, they did not generate any neurons under the following differentiation conditions. When EdU was applied to the proliferating NSCs for 1 hr prior to differentiation, neurogenesis was still substantially reduced. Second, EdU decreased cell proliferation of NSCs in dose- and time-dependent manners. Finally, EdU inhibited differentiation into oligodendrocyte lineage, while the number of glial fibrillary acidic protein (GFAP)-positive astrocytes increased. To our knowledge, these findings are the first to show the effects of EdU on the differentiation of SVZ NSCs and suggest that cell division is necessary for differentiation into neurons and oligodendrocytes.

• The Korean Journal of Applied Statistics
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• v.37 no.4
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• pp.395-410
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• 2024

Text data is usually made up of a wide variety of unique words. Even in standard text data, it is common to find tens of thousands of different words. In text data analysis, usually, each unique word is treated as a variable. Thus, text data can be regarded as a dataset with a large number of variables. On the other hand, in text data classification, we often encounter class label imbalance problems. In the cases of substantial imbalances, the performance of conventional classification models can be severely degraded. To improve the classification performance of support vector machines (SVM) for imbalanced data, algorithms such as the Synthetic Minority Over-sampling Technique (SMOTE) can be used. The SMOTE algorithm synthetically generates new observations for the minority class based on the k-Nearest Neighbors (kNN) algorithm. However, in datasets with a large number of variables, such as text data, errors may accumulate. This can potentially impact the performance of the kNN algorithm. In this study, we propose a method for enhancing prediction performance for the minority class of imbalanced text data. Our approach involves employing variable selection to generate new synthetic observations in a reduced space, thereby improving the overall classification performance of SVM.

• Korean Journal of Microbiology
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• v.38 no.2
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• pp.86-95
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• 2002

As a result of genome projects, the research to elucidate the function of a protein of interest has recently been well-recognized. In order to facilitate functional genomics, a useful mammalian gene expression vector is required. Using an infectious CDNA clone of BVDV pNADLclns-, we have developed a mammalian gene expression vector. In this study, a replication-competent full-length infectious CDNA clone containing puremycin acetyltransferase (pac) gene (pNADLclns-/pac) was successfully generated. The viral RNA replication and viral protein NS3 synthesis were examined by detecting metabollically $^{32}P$-labelled genomic viral RNA and immunoblotting with a mouse anti-NS3 antibody. To generate viral replicon as an expression vector, we examine if the viral structural genes (C, E0, El, E2) are required for viral replication by deletion analysis. As a result, all of the structural proteins are dispensable for viral replication per se, but essential for infectious viral particle formation. Based on our deletion analysis, we have generated a replication-competent BVDV viral replicon (pNADLclns-/pac/${\Delta}S$), whose structural genes are all deleted. In addition to NADLclns- /pac/${\Delta}S$, NADLclns-/ luc/${\Delta}S$ viral replicon containing luciferase gene as a reporter was constructed and fecund to be replication-compotent in HeLa and BHK cells as well as MDBK cells. Therefore, BVDV viral replicon developed in our study will be a useful tool to express a protein of interest in various mammalian cells.