• Journal of the Korean Data and Information Science Society
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• v.14 no.1
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• pp.67-74
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• 2003

Median regression analysis has robustness properties which make it an attractive alternative to regression based on the mean. Support vector machine (SVM) is used widely in real-world regression tasks. In this paper, we propose a new SV median regression based on check function. And we illustrate how this proposed SVM performs and compare this with the SVM based on absolute deviation loss function.

• Journal of Information Technology Services
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• v.8 no.4
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• pp.129-140
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• 2009

The accurate estimation of software reliability is important to a successful development in software engineering. Until recent days, the models using regression analysis based on statistical algorithm and machine learning method have been used. However, this paper estimates the software reliability using support vector regression, a sort of machine learning technique. Also, it finds the best set of optimized parameters applying immune algorithm, changing the number of generations, memory cells, and allele. The proposed IA-SVR model outperforms some recent results reported in the literature.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.1
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• pp.150-156
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• 2001

This paper proposed a speed estimator using MRAC(Model Reference Adaptive Control) for sensorless vector control. It is robust for parameter variation or disturbance and the estimated speed is used as feedback in a vector control system. Experiment is presented to confirm the theoretical analysis.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.207-210
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• 1995

In this paper, two representative schemes for vector control of induction motor without speed sensor are studied. First, the two sensorless systems which are implemented by voltage and current source are presented with new ideas and interpretations. Then a linear model around an operating point is proposed. Finally, the stability improvement of these systems are studied and evaluated by computing the trajectories of poles and zeros.

• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.6
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• pp.672-679
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• 1988

In this paper, attempts have been made to code images employing a separating mean vector quantizer(SMVQ). Then we analyzed the performance of the SMVQ experimentally as well as analytically. The results of simulation with natural images are presented. But, conclusively the performance of the SMVQ technique is not better than that of the conventional vector quantizer. In this paper, a brief analysis in which we revealed that the performance, based on the mean square error measure, of the SMVQ is not favorable is favorable is discussed.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2164-2167
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• 2003

In this paper we propose effective speech recognizer through recognition experiments for three feature parameters(PCA, ICA and MFCC) using SVM(Support Vector Machine) classifier In general, SVM is classification method which classify two class set by finding voluntary nonlinear boundary in vector space and possesses high classification performance under few training data number. In this paper we compare recognition result for each feature parameter and propose ICA feature as the most effective parameter

• 한국정보디스플레이학회:학술대회논문집
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• 2007.08a
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• pp.517-519
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• 2007

We report our study on the implementation of Q tensor approach into three-dimensional finite element method (FEM) numerical solver. The comparative simulation results demonstrated the possibility of a different director configuration in between Q tensor method and vector method. The comparative study confirmed that Q Tensor implementation is more appropriate for OCB analysis than the vector method.

• Computers and Concrete
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• v.20 no.5
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• pp.555-562
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• 2017

The accuracy and integrity of stress data acquired by bridge heath monitoring system is of significant importance for bridge safety assessment. However, the missing and abnormal data are inevitably existed in a realistic monitoring system. This paper presents a data reconstruction approach for bridge heath monitoring based on the wavelet multi-resolution analysis and support vector machine (SVM). The proposed method has been applied for data imputation based on the recorded data by the structural health monitoring (SHM) system instrumented on a prestressed concrete cable-stayed bridge. The effectiveness and accuracy of the proposed wavelet-based SVM prediction method is examined by comparing with the traditional autoregression moving average (ARMA) method and SVM prediction method without wavelet multi-resolution analysis in accordance with the prediction errors. The data reconstruction analysis based on 5-day and 1-day continuous stress history data with obvious preternatural signals is performed to examine the effect of sample size on the accuracy of data reconstruction. The results indicate that the proposed data reconstruction approach based on wavelet multi-resolution analysis and SVM is an effective tool for missing data imputation or preternatural signal replacement, which can serve as a solid foundation for the purpose of accurately evaluating the safety of bridge structures.

• Journal of Life Science
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• v.23 no.2
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• pp.290-298
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• 2013

The genus Mycobacterium includes crucial animal and human pathogens such as Mycobacterium tuberculosis, Mycobacterium leprae, and Mycobacterium bovis. Although it is important to understand the genetic basis for their virulence and persistence in host, genetic analysis in mycobacteria was hampered by a lack of sufficient genetic tools. Therefore, many functional vectors as molecular genetic tools have been designed for understanding mycobacterial biology, and the application of these tools to mycobacteria has accelerated the study of mechanisms involved in virulence and gene expression. To overcome the pre-existing problems in genetic manipulation of mycobacteria, this paper reports new vector systems as effective genetic tools in Mycobacterium smegmatis. Three vectors were developed; pKOTs is a suicide vector for mutagenesis containing a temperature-sensitive replication origin (TSRO) and the sacB gene encoding levansucrase as a counterselectable marker. pMV306lacZ is an integrative lacZ transcriptional fusion vector that can be inserted into chromosomal DNA by site-specific recombination. pTnMod-OKmTs is a minitransposon vector harboring the TSRO that can be used in random mutagenesis. It was demonstrated in this study that these vectors effectively worked in M. smegmatis. The vector systems reported here are expected to successfully applicable to future research of mycobacterial molecular genetics.

• Journal of Korean Society for Geospatial Information Science
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• v.11 no.2 s.25
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• pp.47-52
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• 2003

Change detection and analysis is a powerful application of remote sensing, in that the spectral resolution of multi-band sensors can be used to advantage in monitoring both significant and subtle land cover changes over time. In this study, the LANDSAT TM data was used to detect the change areas affected by flood from a heavy rainfall. The study area is the Nakdong River located in the Korea peninsular. Among the several change detection techniques, change vector analysis(CVA), principle component analysis(PCA) and image difference approach are utilized in this paper. CVA uses any number of spectral bands from multi-date satellite data to produce change image that yield information of the magnitude and direction of differences pixel values. And accuracy assessment was carried out with a change image produced from three techniques. In result, CVA was found to be the most accurate for detecting areas affected by flood. CVA with the overall accuracy and Kappa coefficient of 97.27 percent and 94.45 percent, respectively.