• Journal of Plant Biotechnology
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• v.34 no.4
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• pp.285-291
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• 2007

This study describes conditions for the mass production of activation-tagged mutant hairy root lines of ginseng by cocultivation with Agrobacterium rhizogenes. Because it is not currently possible to produce progeny from transgenic ginseng, a loss-of-function approach for functional genomics cannot be appliable to this species. A gain-of-function approach is alternatively the choice and hairy root production by cocultivation of A. rhizogenes would be most practical to obtain a large number of mutants. Various sources of explants were subjected to genetic transformation with various strains of A. rhizogenes harboring the activation-tagging vector pKH01 to determine optimum conditions for the highest frequency of hairy root formation on explants. Petiole explants cocultivated with A. rhizogenes R1000 produced hairy roots at a frequency of 85.9% after 4 weeks of culture. Conditions for maximum growth or branching rate of hairy roots were also investigated by using various culture media. Petiole explants cultured on half strength Schenk and Hildebrandt medium produced vigorously growing branched roots at a rate of 2.6 after 4 weeks of culture. A total of 1,989 lines of hairy root mutants were established in this study. These hairy root lines will be useful to determine functions of genes for biosynthesis of ginsenosides.

• School Mathematics
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• v.5 no.4
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• pp.421-440
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• 2003

It is difficult for the learner to understand completely the ratio concept which forms a basis of proportional reasoning. And proportional reasoning is, on the one hand, the capstone of children's elementary school arithmetic and, the other hand, it is the cornerstone of all that is to follow. But school mathematics has centered on the teachings of algorithm without dealing with its essence and meaning. The purpose of this study is to analyze the essence of ratio concept from multidimensional viewpoint. In addition, this study will show the direction for improvement of ratio concept. For this purpose, I tried to analyze the historical development of ratio concept. Most mathematicians today consider ratio as fraction and, in effect, identify ratios with what mathematicians called the denominations of ratios. But Euclid did not. In line with Euclid's theory, ratio should not have been represented in the same way as fraction, and proportion should not have been represented as equation, but in line with the other's theory they might be. The two theories of ratios were running alongside each other, but the differences between them were not always clearly stated. Ratio can be interpreted as a function of an ordered pair of numbers or magnitude values. A ratio is a numerical expression of how much there is of one quantity in relation to another quantity. So ratio can be interpreted as a binary vector which differentiates between the absolute aspect of a vector -its size- and the comparative aspect-its slope. Analysis on ratio concept shows that its basic structure implies 'proportionality' and it is formalized through transmission from the understanding of the invariance of internal ratio to the understanding of constancy of external ratio. In the study, a fittingness(or comparison) and a covariation were examined as the intuitive origins of proportion and proportional reasoning. These form the basis of the protoquantitative knowledge. The development of sequences of proportional reasoning was examined. The first attempts at quantifying the relationships are usually additive reasoning. Additive reasoning appears as a precursor to proportional reasoning. Preproportions are followed by logical proportions which refer to the understanding of the logical relationships between the four terms of a proportion. Even though developmental psychologists often speak of proportional reasoning as though it were a global ability, other psychologists insist that the evolution of proportional reasoning is characterized by a gradual increase in local competence.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.647-660
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• 2022

To prepare an atmospheric correction model suitable for CAS500-4 (Compact Advanced Satellite 500-4), this letter examined an atmospheric correction experiment using Sentinel-2 images having similar spectral characteristics to CAS500-4. Studies to compare the atmospheric correction results depending on different Aerosol Optical Depth (AOD) data are rarely found. We conducted a comparison of Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH), Sen2Cor, and Second Simulation of the Satellite Signal in the Solar Spectrum - Vector (6SV) version 1.1 and 2.1, using Geo-Kompsat 2A (GK2A) Advanced Meteorological Imager (AMI) and Aerosol Robotic Network (AERONET) AOD data. In this experiment, 6SV2.1 seemed more stable than others when considering the correlation matrices and the output images for each band and Normalized Difference Vegetation Index (NDVI).

• Geophysics and Geophysical Exploration
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• v.26 no.2
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• pp.77-83
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• 2023

In this study, the expressions of magnetic vector and magnetic gradient tensor due to an elliptical cylinder were derived. Igneous intrusions and kimberlite structures are often shaped like elliptical cylinders with axial symmetry and different radii in the strike and perpendicular directions. The expressions of magnetic fields due to this elliptical cylinder were derived from the Poisson relation, which includes the direction of magnetization in the gravity gradient tensor. The magnetic gradient tensor due to an elliptical cylinder is derived by differentiating the magnetic fields. This method involves obtaining a total of 10 triple derivative functions acquired by differentiating the gravitational potential of the elliptical cylinder three times in each axis direction. As the order of differentiation and integration can be exchanged, the magnetic gradient tensor was derived by differentiating the gravitational potential of the elliptical cylinder three times in each direction, followed by integration in the depth direction. The remaining double integration was converted to a complex line integral along the closed boundary curve of the elliptical cylinder in the complex plane. The expressions of the magnetic field and magnetic gradient tensor derived from the complex line integral in the complex plane were shown to be perfectly consistent with those of the circular cylinder derived by the Lipschitz-Hankel integral.

• Horticultural Science & Technology
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• v.32 no.1
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• pp.91-99
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• 2014

The objective of this study is to identify cold-tolerance genes in Brassica rapa. In order to acheive this goal, we analyzed a KBGP-24K oligo chip data [BrEMD (B. rapa EST and Microarray Database)] using B. rapa ssp. pekinensis inbred line 'Chiifu' under cold stress condition ($4^{\circ}C$). Among 23,929 unigenes of B. rapa, 417 genes (1.7%) were primarily identified as cold responsive genes that were expressed over 5-fold higher than those of wild type control, and then a gene which has unknown function and has full length sequence was selected. It was named BrCSR (B. rapa Cold Stress Resistance). BrCSR was transformed using expression vector pSL101 to confirm whether BrCSR can enhance cold tolerance in tobacco plants. $T_1$ transgenic tobacco plants expressing BrCSR were selected by PCR and Southern hybridization analyses, and the function of BrCSR was characterized by expression level analysis and phenotype observation under cold stress condition. The expression level of BrCSR in transgenic tobacco plants increased up to about two folds in quantitative real-time RT-PCR assay and this was very similar to Northern blot hybridization analysis. Analysis of phenotypic characteristics clearly elucidated that transgenic tobaccos expressing BrCSR were more cold tolerant than wild type control under $4^{\circ}C$ treatment. Based on these results, we conclude that the over-expression of BrCSR might be closely related to the enhancement of cold tolerance.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.11
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• pp.5551-5556
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• 2012

Cytological examination is widely used as a diagnostic tool because of the ease of collecting cells from the involved area. However, the diagnostic yield of cytological examination is unsatisfactory; the reasons include sampling error, poorly prepared samples, small numbers of malignant cells, and low grades of cellular atypia. In this study, we focused on the high infectivity of adenovirus towards epithelial cells and applied the luciferase-expressing adenoviral vector to a new cancer cell detection tool. In addition, adenoviral infectivity was enhanced by modifying viral fiber proteins. The sensitivity of the diagnostic tool was tested using the NCI-H1299 lung cancer cell line, and validated in body fluid samples from cancer patients with a variety of etiology. Results showed that the adenovirus efficiently transfected NCI-H1299 with high sensitivity. Only 10 cancer cells were sufficient for detection of luciferase signals. In body fluid samples, the adenovirus confirmed the diagnosis for malignant and benign cancer, but not in non-epithelial cell derived samples. This study provides proof-of-concept for a more reliable and sensitive diagnostic tool for epithelium-derived cancer.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.2
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• pp.185-195
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• 2018

As machines have been automated in the field of industries in recent years, it is a paramount importance to manage and maintain the automation machines. When a fault occurs in sensors attached to the machine, the machine may malfunction and further, a huge damage will be caused in the process line. To prevent the situation, the fault of sensors should be monitored, diagnosed and classified in a proper way. In the paper, we propose a sensor fault detection scheme based on SVM and CNN to detect and classify typical sensor errors such as erratic, drift, hard-over, spike, and stuck faults. Time-domain statistical features are utilized for the learning and testing in the proposed scheme, and the genetic algorithm is utilized to select the subset of optimal features. To classify multiple sensor faults, a multi-layer SVM is utilized, and ensemble technique is used for CNN. As a result, the SVM that utilizes a subset of features selected by the genetic algorithm provides better performance than the SVM that utilizes all the features. However, the performance of CNN is superior to that of the SVM.

• Journal of Life Science
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• v.18 no.12
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• pp.1651-1656
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• 2008

Redox factor-1 (Ref-1) is essential for repair of oxidatively damaged DNA and also govern the reductive activation of many transcription factors. In this study, we examined the effect of overexpressed Ref-1 on AKT activation for nitric oxide (NO) production in mouse aortic endothelial (MAE) cells. Adenoviral-mediated overexpression of Ref-1 enhanced NO production in unstimulated- as well as bradykinin-stimulated MAE cells. Importantly, forced overexpression of Ref-1 induced direct phosphorylation of AKT in cells. And, a PI3K inhibitor wortmannin completely abolished the increase in AKT phosphorylation by stimulation of bradykinin and/or overexpressed Ref-1. In addition, inhibition of AKT activity with HA-tagged activation-deficient AKT suppressed Ref-1-induced endothelial NO synthase (eNOS) phosphorylation and resulted in a corresponding inhibition of unstimulated- and bradykinin-stimulated NO production. These results suggest that Ref-1 stimulates direct phosphorylation of AKT for eNOS enzyme activity in murine endothelial cells.

• Proceedings of the Acoustical Society of Korea Conference
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• spring
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• pp.115-118
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• 2002

Parameters used in a speaker recognition system are desirable expressing speaker's characteristics filly and have in a speech. That is to say, if inter-speaker than intra-speaker variance a big characteristic, it is useful to distinguish between speakers. Also, to make minimum error between speakers, it is required the improved recognition technology as well as the distinguishing characteristics. When we see the result of recent simulation performance, we obtain more exact performance by using dynamic characteristics and constant characteristics by a speaking habit. Therefore we suggest it to solve this problem as followings. The prosodic information is used by a characteristic vector of speech. Characteristics vector generally using in speaker recognition system is a modeling spectrum information and is working for a high performance in non-noise circumstance. However, it is found a problem that characteristic vector is distorted in noise circumstance and it makes a reduction of recognition rate. In this paper, we change pitch line divided by segment which can estimate a dynamic characteristic and it is used as a recognition characteristic. we confirmed that the dynamic characteristic is very robust in noise circumstance with a simulation. We make a decision of acceptance or rejection by comparing test pattern and recognition rate using the proposed algorithm has more improvement than using spectrum and prosodic information. Especially stational recognition rate can be obtained in noise circumstance through the simulation.

• Journal of the Korea Society for Simulation
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• v.18 no.3
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• pp.103-112
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• 2009

In a nuclear power plant (NPP), periodic sensor calibrations are required to assure sensors are operating correctly. However, only a few faulty sensors are found to be calibrated. For the safe operation of an NPP and the reduction of unnecessary calibration, on-line calibration monitoring is needed. In this paper, principal component-based Auto-Associative support vector regression (PCSVR) was proposed for the sensor signal validation of the NPP. It utilizes the attractive merits of principal component analysis (PCA) for extracting predominant feature vectors and AASVR because it easily represents complicated processes that are difficult to model with analytical and mechanistic models. With the use of real plant startup data from the Kori Nuclear Power Plant Unit 3, SVR hyperparameters were optimized by the response surface methodology (RSM). Moreover the statistical techniques are integrated with PCSVR for the failure detection. The residuals between the estimated signals and the measured signals are tested by the Shewhart Control Chart, Exponentially Weighted Moving Average (EWMA), Cumulative Sum (CUSUM) and generalized likelihood ratio test (GLRT) to detect whether the sensors are failed or not. This study shows the GLRT can be a candidate for the detection of sensor drift.