• KSCE Journal of Civil and Environmental Engineering Research
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• v.8 no.1
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• pp.159-164
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• 1988

The directions of the principal strain increment, stress, and stress increment during rotation of the principal stress axes at any stress level was studied for $K_0$-consolidated clay using torsion shear apparatus with individual control of the vertical stress, the confining pressure, and the shear stress on hollow cylinder specimens under undrained and drained condition. The torsion shear tests were performed according to predetermined stress-paths, which were chosen to cover over the full range of rotation of principal stress axes. The test results indicated that the strain increment vectors at failure coincided with the stress vectors. That is, the direction of strain increment coincided with the direction of stress increment at small stress levels and with the direction of stress at higher stress levels, which indicated that the behavior of clay was transfered from elastic to plastic as the stress level was increased. The applicability of the elastoplastic theory for modeling of the behavior of clay during rotation of the principal stress axes was given.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.485-490
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• 1999

Wind vector information over the ocean is currently obtained using multiple beam scatterometer data. The scatterometers on ERS-1/2 generate wind vector information with a spatial resolution of 50km and accuracies of $\pm$2m/s in wind speed and $\pm$20$^{\circ}$ in wind direction. Synthetic aperture radar (SAR) data over the ocean have the potential of providing wind vector information independent of weather conditions with finer resolution. Finer resolution wind vector information can often be useful particularly in coastal regions where the scatterometer wind information is often corrupted because of the lower resolution system characteristics which is often contaminated by the signal returns from the coastal areas or ice in the case of arctic environments. In this paper we tested CMOD_4 and CMOD_IFR2 algorithms for extracting the wind vector from SAR data. These algorithms require precise estimation of normalized radar cross-section and wind direction from the SAR data and the local incidence angle. The CMOD series algorithms were developed for the C-band, VV-Polarized SAR data, typically for the ERS SAR data. Since RADARSAT operates at the same C-band but with HH-Polarization, the CMOD series algorithms should not be used directly. As a preliminary approach of resolving with this problem, we applied the polarization ratio between the HH and VV polarizations in the wind vectors estimation. Two test areas, one in front of Inchon and several sites around Jeju island were selected and investigated for wind vector estimation. The new results were compared with the wind vectors obtained from CMOD algorithms. The wind vector results agree well with the observed wind speed data. However the estimation of wind direction agree with the observed wind direction only when the wind speed is greater than approximately 3.0m/s.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.2
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• pp.207-216
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• 2000

This paper introduces an effective system design method to develop a customer oriented product using a design optimization process and to select a set of critical design paramenters,. The process results in the development of a successful product satisfying customer needs and reducing development risk. The proposed scheme adopted a five step QFD(Quality Function Deployment) in order to extract design parameters from customer needs and evaluated their priority using risk factors for extracted design parameters. In this process we determine critical design parameters and allocate them to subsystem designers. Subsequently design engineers develop and test the product based on these parameters. These design parameters capture the characteristics of customer needs in terms of performance cost and schedule in the process of QFD, The subsequent risk management task ensures the minimum risk approach in the presence of design parameter uncertainty. An application of this approach was demonstrated in the development of weld quality monitoring system. Dominant design parameters affect linearity characteristics of weld defect feature vectors. Therefore it simplifies the algorithm for adopting pattern classification of feature vectors and improves the accuracy of recognition rate of weld defect and the real time response of the defect detection in the performance. Additionally the development cost decreases by using DSP board for low speed because of reducing CPU's load adopting algorithm in classifying weld defects. It also reduces the cost by using the single sensor to measure weld defects. Furthermore the synergy effect derived from the critical design parameters improves the detection rate of weld defects by 15% when compared with the implementation using the non-critical design parameters. It also result in 30% saving in development cost./ The overall results are close to 95% customer level showing the effectiveness of the proposed development approach.

• 전자공학회논문지 IE
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• v.43 no.2
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• pp.22-29
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• 2006

Recently the use of whispered speech has increased due to mobile phone and the necessity of whispered speech recognition is increasing. So various feature vectors, which are mainly used for speech recognition, are applied to their HMMs, normal speech models, whispered speech models, and integrated models with normal speech and whispered speech so as to find out suitable recognition system for whispered speech. The experimental results of recognition test show that the recognition rate of whispered speech applied to normal speech models is too low to be used in practical applications, but separate whispered speech models recognize whispered speech with the highest rates at least 85%. And also integrated models with normal speech and whispered speech score acceptable recognition rate but more study is needed to increase recognition rate. MFCE and PLCC feature vectors score higher recognition rate when applied to separate whispered speech models, but PLCC is the best when a lied to integrated models with normal speech and whispered speech.

• The Journal of the Korea Contents Association
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• v.9 no.3
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• pp.1-8
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• 2009

This paper proposes a new document clustering system using fuzzy logic-based genetic algorithm (GA) and semantic vector expansion technology. It has been known in many GA papers that the success depends on two factors, the diversity of the population and the capability to convergence. We use the fuzzy logic-based operators to adaptively adjust the influence between these two factors. In traditional document clustering, the most popular and straightforward approach to represent the document is vector space model (VSM). However, this approach not only leads to a high dimensional feature space, but also ignores the semantic relationships between some important words, which would affect the accuracy of clustering. In this paper we use latent semantic analysis (LSA)to expand the documents to corresponding semantic vectors conceptually, rather than the individual terms. Meanwhile, the sizes of the vectors can be reduced drastically. We test our clustering algorithm on 20 news groups and Reuter collection data sets. The results show that our method outperforms the conventional GA in various document representation environments.

• Journal of Microbiology and Biotechnology
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• v.27 no.11
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• pp.2060-2069
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• 2017

Newcastle disease is a serious infectious disease in the poultry industry. The commercial vaccines can only offer limited protection and some of them are expensive and need adjuvants. At present, DNA vaccines are widely used. However, the immune responses induced by DNA vaccines are too slow and low. Here, we constructed the transfer vectors with a different number of C3d as molecular adjuvants (n = 1, 2, 4, or 6), and the vectors were cloned into the optimal eukaryotic expression plasmid (pVAXI-optiF) that expressed the F gene of Newcastle disease virus (NDV), and named pVAXI-F(o)-C3d1, pVAXI -F(o)-C3d2, pVAXI-F(o)-C3d4, and pVAXI-F(o)-C3d6, respectively. Cell transfection test indicated that pVAXI-F(o)-C3d6 showed the highest expression. In vivo immunization showed that the chickens immunized with pVAXI-F(o)-C3d6 intramuscularly induced better immune responses than the chickens immunized with the other plasmids. The protective efficacy of pVAXI-F(o)-C3d6 was 80% after challenge with the highly virulent NDV strain F48E9. The results in this study showed that C3d6 could be used as a molecular adjuvant to quickly induce an effective immune response to control NDV.

• Journal of fish pathology
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• v.34 no.1
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• pp.23-29
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• 2021

Interferon regulatory factors (IRFs) are a family of transcription factors essential to the control of antiviral immune response, cell growth, differentiation and apoptosis. IRF10 of zebrafish (Danio rerio) was negative regulation of the interferonΦ1 and 3 response in vitro. In this study, we analyze the induction of in vivo immune response activation from the IRF10 gene of zebrafish and the protective effect against VHSV. As the results, the group inoculated with IRF10 expression vectors, there was no expression of IFNΦ1, suggestion that IRF10 may function as a negative regulator of IRF3, which binds to the IFNΦ1 promoter. And other types of interferon genes (IFNΦ2-4) are thought to have been activated, inducing to the expression of pro-inflammatory cytokine and Mx genes. As the results of challenge test performed at 14 days after inoculation of the expression vectors, the maximum survival rate [50% (1㎍ DNA) and 42.5% (10㎍ DNA)] for IRF10 group were recorded. Meanwhile, the survival rates of pcDNA3.1 and PBS as the control groups were 10% and 15%, respectively. This study suggests that the possibility that activation of IRF10 molecule could be exploited as a VHS control method.

• Journal of Korea Multimedia Society
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• v.17 no.3
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• pp.277-286
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• 2014

In this paper, we propose a texture feature-based language identification by fusion of Gabor, MDLC (multi-lag directional local correlation), and co-occurrence features. In the proposed method, for a test image, Gabor magnitude images are first obtained by Gabor transform followed by magnitude operator. Moments for the Gabor magniude images are then computed and vectorized. MDLC images are then obtained by MDLC operator and their moments are computed and vectorized. GLCM (gray-level co-occurrence matrix) is next calculated from the test image and co-occurrence features are computed using the GLCM, and the features are also vectorized. The three vectors of the Gabor, MDLC, and co-occurrence features are fused into a feature vector. In classification, the WPCA (whitened principal component analysis) classifier, which is usually adopted in the face identification, searches the training feature vector most similar to the test feature vector. We evaluate the performance of our method by examining averaged identification rates for a test document image DB obtained by scanning of documents with 15 languages. Experimental results show that the proposed method yields excellent language identification with rather low feature dimension for the test DB.

• Journal of Microbiology and Biotechnology
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• v.28 no.10
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• pp.1683-1690
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• 2018

Accurate and rapid diagnosis of influenza infection is essential to enable early antiviral treatment and reduce the mortality associated with seasonal and epidemic infections. Immunochromatography is one of the most common methods used for the diagnosis of seasonal human influenza; however, it is less effective in diagnosing pandemic influenza virus. Currently, rapid diagnostic kits for pandemic influenza virus rely on the detection of nucleoprotein (NP) or hemagglutinin (HA). NP detection shows higher specificity and is more sensitive than HA detection. In this study, we time-dependently screened expression conditions, and herein report optimal conditions for the expression of recombinant nucleoprotein (rNP), which was 48 h after infection. In addition, we report the use of the expressed rNP in a rapid influenza diagnostic test (SGT i-flex Influenza A&B Test). We constructed expression vectors that synthesized rNP (antigen) of influenza A and B in insect cells (Sf9 cells), employed the purified rNP to the immunoassay test kit, and clearly distinguished NPs of influenza A and influenza B using this rapid influenza diagnostic kit. This approach may improve the development of rapid test kits for influenza using NP.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.1
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• pp.97-104
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• 2015

An 'associative cube', a class of auto-associative memories, is revisited here, in which training data and hidden orthogonal basis functions such as wavelet packets or Fourier kernels, are combined in the weight cube. This weight cube has hidden units in its depth, represented by a three dimensional cubic structure. We develop an unsupervised incremental learning mechanism based upon the adaptive least squares method. Training data are mapped into orthogonal basis vectors in a least-squares sense by updating the weights which minimize an energy function. Therefore, a prescribed orthogonal kernel is incrementally assigned to an incoming data. Next, we show how a decoding procedure finds the closest one with a competitive network in the hidden layer. As noisy test data are applied to an associative cube, the nearest one among the original training data are restored in an optimal sense. The simulation results confirm robustness of associative cubes even if test data are heavily distorted by various types of noise.