• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.1
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• pp.1-8
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• 2004

According to the development of the Internet and the pervasion of Data Base, it is not easy to search for necessary information from the huge amounts of data. In order to do efficient analysis of a large amounts of data, this paper proposes a method for pattern classification based on the effective strategy for dimension reduction for narrowing down the whole data to what users wants to search for. To analyze data effectively, Radial Basis Function Networks based on VC-dimension of Support Vector Machine, a model of statistical teaming, is proposed in this paper. The model of Radial Basis Function Networks currently used performed the preprocessing of Perceptron model whereas the model proposed in this paper, performing independent analysis on VD-dimension, classifies each datum putting precise labels on it. The comparison and estimation of various models by using Machine Learning Data shows that the model proposed in this paper proves to be more efficient than various sorts of algorithm previously used.

• Journal of Plant Biology
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• v.37 no.1
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• pp.77-83
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• 1994

DNA uptake in dry embryos of rice by DNA imbibition was detected by monitoring the expression of chimeric vectors. The selective markers of expression vectors used were ${\beta}-glucuronidase$ ronidase (GUS) and hygromycin phosphotransferase (HPT) genes under the control of CaMV35 S promoter. Frequency of transient expression of the foreign gene was generally 30-50% varying according to the types of vectors and rice cultivars. Dot blot analysis and DNA sequence analysis of inverse polymerase chain reaction products showed that selected rice in hygromycin B (HmB) medium had HPT gene and CaMV35S promoter DNA sequence in genomic DNA of rice. To investigate what ratio of rice having two marker genes simultaneously as rice embryos imbibed the vector DNA having two HPT and GUS gene, transform ants selected in lImB medium were subjected to PCR for GUS gene. It was shown that about 90 percentage of surviving ones in HmB medium had GUS gene.S gene.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.8
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• pp.967-975
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• 2012

This paper presents a method to measure reflection coefficients of microwave devices or antennas based on time domain analysis with sampling oscilloscopes. The reflection coefficients were extracted by the Fourier transformation of echo pulses from devices with respect to the 20 GHz incident pulse signals. The three-error terms, which are commonly used for the correction of a microwave network, were determined using a 3.5 mm calibration kit. In addition, a modified error-correction model associated with a directional coupler for reflection coefficient measurements is introduced. The results were compared with those of measured with a commercial vector network analyzer.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.514-517
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• 2017

In solar photovoltaic systems, power generation is greatly affected by the weather conditions, so it is essential to predict solar energy for stable load operation. Therefore, data on weather conditions are needed as inputs to machine learning algorithms for solar energy prediction. In this paper, we use 15 kinds of weather data such as the precipitation accumulated during the 3 hours of the surface, upward and downward longwave radiation average, upward and downward shortwave radiation average, the temperature during the past 3 hours at 2 m above from the ground and temperature from the ground surface as input data to the algorithm. We analyzed the statistical characteristics and correlations of weather data and extracted the downward and upward shortwave radiation averages as a major elements of a feature vector with high correlation of 70% or more with solar energy.

• The Korean Journal of Applied Statistics
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• v.28 no.1
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• pp.9-21
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• 2015

The support vector machine has been successfully applied to various classification areas due to its flexibility and a high level of classification accuracy. However, when analyzing imbalanced data with uneven class sizes, the classification accuracy of SVM may drop significantly in predicting minority class because the SVM classifiers are undesirably biased toward the majority class. The weighted $L_2$-norm SVM was developed for the analysis of imbalanced data; however, it cannot identify irrelevant input variables due to the characteristics of the ridge penalty. Therefore, we propose the weighted $L_1$-norm SVM, which uses lasso penalty to select important input variables and weights to differentiate the misclassification of data points between classes. We demonstrate the satisfactory performance of the proposed method through simulation studies and a real data analysis.

• Journal of Microbiology
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• v.43 no.4
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• pp.354-360
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• 2005

Heat-labile enterotoxin B subunit (LTB) of enterotoxigenic Escherichia coli (ETEC) is both a strong mucosal adjuvant and immunogen. It is a subunit vaccine candidate to be used against ETEC-induced diarrhea. It has already been expressed in several bacterial and plant systems. In order to construct yeast expressing vector for the LTB protein, the eltB gene encoding LTB was amplified from a human origin enterotoxigenic E. coli DNA by PCR. The expression plasmid pLTB83 was constructed by inserting the eltB gene into the pYES2 shuttle vector immediately downstream of the GAL1 promoter. The recombinant vector was transformed into S. cerevisiae and was then induced by galactose. The LTB protein was detected in the total soluble protein of the yeast by SDS-PAGE analysis. Quantitative ELISA showed that the maximum amount of LTB protein expressed in the yeast was approximately $1.9\%$ of the total soluble protein. Immunoblotting analysis showed the yeast-derived LTB protein was antigenically indistinguishable from bacterial LTB protein. Since the whole-recombinant yeast has been introduced as a new vaccine formulation the expression of LTB in S. cerevisiae can offer an inexpensive yet effective strategy to protect against ETEC, especially in developing countries where it is needed most.

• Journal of Positioning, Navigation, and Timing
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• v.11 no.4
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• pp.287-295
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• 2022

The GNSS coordinate time series is used as important data for geophysical analysis such as terrestrial reference frame establishment, crustal deformation, Earth orientation parameter estimation, etc. However, various factors may cause discontinuity in the coordinate time series, which may lead to errors in the interpretation. In this paper, we describe the discontinuity in the coordinate time series due to the equipment replacement for domestic GNSS stations and discuss the change in movement magnitude and velocity vector difference in each direction before and after discontinuity correction. To do this, we used three years (2017-2019) of data from 40 GNSS stations. The average magnitude of the velocity vector in the north-south, east-west, and vertical directions before correction is -12.9±1.5, 28.0±1.9, and 4.2±7.6 mm/yr, respectively. After correction, the average moving speed in each direction was -13.0±1.0, 28.2±0.8, and 0.7±2.1 mm/yr, respectively. The average magnitudes of the horizontal GNSS velocity vectors before and after discontinuous correction was similar, but the deviation in movement size of stations decreased after correction. After equipment replacement, the change in the vertical movement occurred more than the horizontal movement variation. Moreover, the change in the magnitude of movement in each direction may also cause a change in the velocity vector, which may lead to errors in geophysical analysis.

• Proceedings of the Korean Society of Embryo Transfer Conference
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• 2002.11a
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• pp.99-99
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• 2002

The hormone resistin is associated with typeII diabetes mellitus in rodent model. Resistin impairs glucose tolerance and insulin action. A new class of anti-diabetic drugs were called thiazolidinediones (TZDs) downregulates a resistin which is induced during adipocyte differentiation. But the connection between increased adiposity and resistin remains unknown. The objectives of this study was to clone a mouse resistin cDNA and to generate transgenic mice overexpressing mouse resistin gene. The 555 bp of mouse resistin was amplified from mob cDNAS by polymerase chain reaction (PCR) and cloned into pCR$\^$(R)/ 2.1 TOPO T-vector. Mouse resistin mRNA on the basis of Genbank sequence (acession no. AF323080). Then, the PCR product was cloned into pTargeT$\^$TM/ mammalian expression vector that has pCMV promoter and chimeric intron. Restriction enzyme analysis with BamH I and Not I was carried out to determine an orientation of the insert in the vector. The pCMV-mus/resistin gene was prepared from previous recombinant pTargeT$\^$TM/-mus/resistin by digestion of Bgl II, and has used for microinjection into pronuclei of one cell embryos. The microinjected embryos were transfered to pseudopregnant foster-mother. Mouse resistin expression was detected in transgenic F1 mice by Reverse Transcriptase- Polymerase Chain Reaction (RT-PCR). Resistin gene expression mouse has heavier body weight which was measured higher level of plasma glucose than that of normal mouse. And in diet-induced experiments, the abdominal fat pads were isolated from each 24h starvation and re-feeding after fasting group mice that were assessed by RT-PCR analysis. In fasting group mice, resistin expression was higher than that of re-feeding group mice. This result suggests that the resistin gene overexpressing mice may be became to obesity and be useful as an animal disease model to be diabetes mellitus caused by insulin resistance of resistin.

• The Plant Pathology Journal
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• v.40 no.1
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• pp.59-72
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• 2024

A comprehensive survey of mungbean-growing areas was conducted to observe leaf spot disease caused by Alternaria alternata. Alternaria leaf spot symptoms were observed on the leaves. Diversity of 50 genotypes of mungbean was assessed against A. alternata and data on pathological traits was subjected to cluster analysis. The results showed that genotypes of mungbean were grouped into four clusters based on resistance parameters under the influence of disease. The principal component biplot demonstrated that all the disease-related parameters (% disease incidence, % disease intensity, lesion area, and % of infection) were strongly correlated with each other. Alt a 1 gene that is precisely found in Alternaria species and is responsible for virulence and pathogenicity. Alt a 1 gene was amplified using gene specific primers. The isolated pathogen produced similar symptoms when inoculated on mungbean and tobacco. The sequence analysis of the internal transcribed spacer (ITS) region, a 600 bp fragment amplified using specific primers, ITS1 and ITS2 showed 100% identity with A. alternata. Potato virus X (PVX) -based silencing vector expressing Alt a 1 gene was constructed to control this pathogen through RNA interference in tobacco. Out of 50 inoculated plants, 9 showed delayed onset of disease. Furthermore, to confirm our findings at molecular level semi-quantitative reverse transcriptase polymerase chain reaction was used. Both phenotypic and molecular investigation indicated that RNAi induced through the VIGS vector was efficacious in resisting the pathogen in the model host, Tobacco (Nicotiana tabacum). To the best of our knowledge, this study has been reported for the first time.

• Environmental and Resource Economics Review
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• v.33 no.2
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• pp.135-157
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• 2024

In this study, we analyzed the changes in copper consumption according to copper price fluctuations and identified the domestic copper price elasticity. A total of 408 time series data from January 1989 to December 2022 were analyzed using the vector autoregressive (VAR) model with net import volume, price, and production index as variables. In addition, to identify changes in the correlation between variables over time, the dynamic relationship between variables was identified using the time-varying vector autoregressive (TV-VAR) model. As a result of the analysis, it was confirmed that the negative price elasticity for copper is -0.1835. In addition, the interquartile range was -0.3130 ~ 0.0886, with no consistent trend over time, but mainly negative elasticity. This study can be used to quantify the expected impact of various policy proposals and changes related to minerals.