• Communications of the Korean Mathematical Society
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• v.32 no.4
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• pp.933-957
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• 2017

In this paper, we prove some existence results of solutions for a new class of generalized bi-quasi-variational-like inequalities (GBQVLI) for (${\eta}-h$)-quasi-pseudo-monotone type I and strongly (${\eta}-h$)-quasi-pseudo-monotone type I operators defined on non-compact sets in locally convex Hausdorff topological vector spaces. To obtain our results on GBQVLI for (${\eta}-h$)-quasi-pseudo-monotone type I and strongly (${\eta}-h$)-quasi-pseudo-monotone type I operators, we use Chowdhury and Tan's generalized version of Ky Fan's minimax inequality as the main tool.

• Reproductive and Developmental Biology
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• v.35 no.4
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• pp.449-455
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• 2011

Induced pluripotent stem (iPS) cells have been generated from mouse and human somatic cells by etopic expression of transcription factors. iPS cells are indistinguishable from ES cells in terms of morphology and stem cell marker expression. Moreover, mouse iPS cells give rise to chimeric mice that are competent for germline transmission. However, mice derived from iPS cells often develop tumors. Furthermore, the low efficiency of iPS cell generation is a big disadvantage for mechanistic studies. Nonviral plasmid.based vectors are free of many of the drawbacks that constrain viral vectors. The histone deacetylase inhibitor valproic acid (VPA) has been shown to improve the efficiency of mouse and human iPS cell generation, and vitamin C (Vc) accelerates gene expression changes and establishment of the fully reprogrammed state. The MEK inhibitor PD0325901 (Stemgent) has been shown to increase the efficiency of the reprogramming of human primary fibroblasts into iPS cells. In this report, we described the generation of mouse iPS cells devoid of exogenous DNA by the simple transient transfection of a nonviral vector carrying 2A-peptide-linked reprogramming factors. We used VPA, Vc, and the MEK inhibitor PD0325901 to increase the reprogramming efficiency. The reprogrammed somatic cells expressed pluripotency markers and formed EBs.

• Journal of the Korean Data and Information Science Society
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• v.17 no.4
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• pp.1151-1160
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• 2006

The similarity weight, the pearson's correlation coefficient, which is used in the recommender system has a weak point that it cannot predict all of the prediction value. The similarity weight, the vector similarity, has a weak point of the high MAE although the prediction coverage using the vector similarity is higher than that using the pearson's correlation coefficient. The purpose of this study is to suggest how to raise the prediction coverage. Also, the MAE using the suggested method in this study was compared both with the MAE using the pearson's correlation coefficient and with the MAE using the vector similarity, so was the prediction coverage. As a result, it was found that the low of the MAE in the case of using the suggested method was higher than that using the pearson's correlation coefficient. However, it was also shown that it was lower than that using the vector similarity. In terms of the prediction coverage, when the suggested method was compared with two similarity weights as I mentioned above, it was found that its prediction coverage was higher than that pearson's correlation coefficient as well as vector similarity.

• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1347-1351
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• 1987

This thesis aims at studying laplacian pyramid vector quantization which keeps a simple compression algorithm and stability against various kinds of image data. To this end, images are devied into two groups according to their statistical characteristics. At 0.860 bits/pixel and 0.360 bits/pixel respectively, laplacian pyramid vector quantization is compared to the existing spatial domain vector quantization and transform coding under the same condition in both objective and subjective value. The laplacian pyramid vector quantization is much more stable against the statistical characteristics of images than the existing vector quantization and transform coding.

• The Journal of the Acoustical Society of Korea
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• v.36 no.6
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• pp.401-406
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• 2017

This paper presents the performance assessment of several key algorithms conducted for amphibian species sound classification. Firstly, 9 target species including endangered species are defined and a database of their sounds is built. For performance assessment, three feature vectors such as MFCC (Mel Frequency Cepstral Coefficient), RCGCC (Robust Compressive Gammachirp filterbank Cepstral Coefficient), and SPCC (Subspace Projection Cepstral Coefficient), and three classifiers such as GMM(Gaussian Mixture Model), SVM(Support Vector Machine), DBN-DNN(Deep Belief Network - Deep Neural Network) are considered. In addition, i-vector based classification system which is widely used for speaker recognition, is used to assess for this task. Experimental results indicate that, SPCC-SVM achieved the best performance with 98.81 % while other methods also attained good performance with above 90 %.

• Journal of the Institute of Convergence Signal Processing
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• v.8 no.4
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• pp.293-296
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• 2007

In this paper, we propose the systolic array architecture for the vector median filter. In the color image processing, the vector signal (i.e. the color) consists of three elements, red, green and blue. The vector median filter is very effective to utilize the correlation among red, green and blue elements. The computational complexity of the proposed architecture for computing the vector median of N vector signals is (N+2) clock periods compared to the (3N+1) clock periods in the previous method. In addition to, the input vector signals can be loaded in serial in the proposed architecture. In the previous method, N input vector signals should be loaded to the vector median filter in parallel at the first clock. The proposed architecture is implemented with FPGA.

• Korean Journal of Microbiology
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• v.30 no.4
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• pp.246-251
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• 1992

Molccular cloning of nod genes from Bradvrhizobium sp. SNU001, a nitrogen-fixing symbiont isolated from thc root nodules of soybean (Clycine trim) . was carried out. nod genes were found to be located on thc genome of the symbiont by gcnomic hybridization with 4.5 kb EcoRI/HndIII fragment (nod DABC) of Rhizohium meliloti as probe. Genomic library of this symbiont was constructed using h phage EMBL3-BanlHI vector. from which five nod positive clones were sclectcd by primary and secondary screening methods. The partial restriction map of inserted genomic DNA of h CNS-l(c1one 2) was constructed. and 3.9 kh Bun7HI fragment. which showed strong hybridization signal to the probe, was subcloned into pBS KS(+) plasmid vector. Partial restriction inap ot' a selected subclone (pBjCNS-I) was constructed and nod DABC was found to be located on the 1.8 kb KpnI/Sacl fragment of this subclone.

• Journal of KIISE:Software and Applications
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• v.33 no.10
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• pp.886-895
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• 2006

Fingerprint classification reduces the number of matches required in automated fingerprint identification systems by categorizing fingerprints into a predefined class. Support vector machines (SVMs), widely used in pattern classification, have produced a high accuracy rate when performing fingerprint classification. In order to effectively apply SVMs to multi-class fingerprint classification systems, we propose a novel method in which SVMs are generated with the one-vs-all (OVA) scheme and dynamically ordered with $na{\ddot{i}}ve$ Bayes classifiers. More specifically, it uses representative fingerprint features such as the FingerCode, singularities and pseudo ridges to train the OVA SVMs and $na{\ddot{i}}ve$ Bayes classifiers. The proposed method has been validated on the NIST-4 database and produced a classification accuracy of 90.8% for 5-class classification. Especially, it has effectively managed tie problems usually occurred in applying OVA SVMs to multi-class classification.

• Steel and Composite Structures
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• v.29 no.3
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• pp.309-318
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• 2018

Steel girders are the structural members often used for passing long spans. Mostly being subjected to patch loading, or concentrated loading, steel girders are likely to face sudden deformation or damage e.g., web breathing. Horizontal or vertical stiffeners are employed to overcome this phenomenon. This study aims at assessing the feasibility of a machine learning method, namely the support vector machines (SVM) in predicting the patch loading resistance of longitudinally stiffened webs. A database consisting of 162 test data is utilized to develop SVM models and the model with best performance is selected for further inspection. Existing formulations proposed by other researchers are also investigated for comparison. BS5400 and other existing models (model I, model II and model III) appear to yield underestimated predictions with a large scatter; i.e., mean experimental-to-predicted ratios of 1.517, 1.092, 1.155 and 1.256, respectively; whereas the selected SVM model has high prediction accuracy with significantly less scatter. Robust nature and accurate predictions of SVM confirms its feasibility of potential use in solving complex engineering problems.

• Proceedings of the KIEE Conference
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• 1990.11a
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• pp.347-351
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• 1990

In this paper voltage source inverter(VSI)-fed induction motor vector control system is controlled by a derived model tracking controller. The system analysis is discussed from the viewpoints of ideal vector control, adoption of model tracking controller and derivation of linear model. Furthermore, the result is obtained by the model-tracking control compare with that of P-I, I-P control.