• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.806-811
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• 2007

In this study, we propose a more systematic design process for the structure-borne noise. The proposed way consists of 4 steps: Problem definition, Cause analysis, Development of counter-measure and Validation. Especially, we improved the second step: Cause analysis. According to the PCA(Panel Contribution Analysis), a reduction in vibration of the panels of which panel contribution is positive and larger, results in a reduction in structure-borne noise. We have, however, met the case in which the concept of PCA is no valid in a few vehicle tests. In order to understand this phenomenon, we compared the major panels selected by PCA with the one chosen by DSA(Design Sensitivity Analysis). After investigating the difference between the two results, a more improved process is suggested. The proposed one for the second step in the design process consists of not only the previous way: PCA with deformation analysis results but also DSA. It is finally validated that the proposed design process decreases the sound pressure of the concerned noise transfer function more than 3.5 dB.

• Bulletin of the Korean Mathematical Society
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• v.55 no.4
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• pp.1303-1315
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• 2018

For principal component analysis (PCA) to efficiently analyze large scale matrices, it is crucial to find a few singular vectors in cheaper computational cost and under lower memory requirement. To compute those in a fast and robust way, we propose a new stochastic method. Especially, we adopt the stochastic variance reduced gradient (SVRG) method [11] to avoid asymptotically slow convergence in stochastic gradient descent methods. For that purpose, we reformulate the PCA problem as a unconstrained optimization problem using a quadratic penalty. In general, increasing the penalty parameter to infinity is needed for the equivalence of the two problems. However, in this case, exact penalization is guaranteed by applying the analysis in [24]. We establish the convergence rate of the proposed method to a stationary point and numerical experiments illustrate the validity and efficiency of the proposed method.

• The KIPS Transactions:PartB
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• v.13B no.3 s.106
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• pp.329-336
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• 2006

In this paper, we propose a method of significant term extraction within a document. The technique used is Principal Component Analysis(PCA) which is one of the multivariate analysis methods. PCA can sufficiently use term-term relationships within a document by term-term correlations. We use a correlation matrix instead of a covariance matrix between terms for performing PCA. We also try to find out thresholds of both the number of components to be selected and correlation coefficients between selected components and terms. The experimental results on 283 Korean newspaper articles show that the condition of the first six components with correlation coefficients of |0.4| is the best for extracting sentence based on the significant selected terms.

• Toxicological Research
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• v.12 no.1
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• pp.81-86
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• 1996

Antigenicity of recombinant human interferon $\beta$(LB00013), a newly developed drug for anti-cancer and anti-viral therapeutic use, was investigated in mice and guinea pigs. The following results were obtained: 1. Mice showed no production of antibodies against LB00013 sensitized with aluminum hydroxide gel (Alum) as an adjuvant, when judged by the heterologous passive cutaneous anaphylaxis (PCA) test in rats. Meanwhile, antibodies against ovalbumin (OVA) sensitized with Alum were clearly detected. 2. In guinea pigs, the sensitization of neither LB00013 only nor LB00013 with complete Freund's adjuvant (CFA) produced positive reactions in the homologous active systemic anaphylaxis (ASA) and the PCA tests. Meanwhile, the sensitization of OVA with CFA produced positive reactions in both PCA and ASA. 3. A LB00013-specific reaction was not observed in an indirect hemagglutination(IHA) assay using sera isolated from LB00013 sensitized mice. The present results suggested that LB00013 may have no antigenic potential in mice and guinea pigs.

• Korean Journal of Microbiology
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• v.41 no.3
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• pp.195-200
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• 2005

Comamonas sp. strain DJ-12 is a bacterial isolate capable of degrading of 4-chlorobiphenyl (4CB) as a carbon and energy source. The degradation pathway was characterized as being conducted by consecutive reactions of the meta-degradation of 4CB, hydrolytic dechlorination of 4-chlorobenzoate (4CBA), hydroxylation of 4-hydroxybenzoate, and meta-degradation of protocatechuate to product TCA metabolites. The 6.8 kb fragment from the chromosomal DNA of Comamonas sp. strain DJ-12 included the genes encoding for the meta-degradation of PCA; the genes of protocatechuate 4,5-dioxygenase alpha and beta subunits (pmcA and pmcB), 4-carboxy-2-hydroxymuconate-6-semialdehyde dehydrogenase (pmcC), 2-pyrone-4,6-dicarboxylate hydrolase (pmcD), 4-oxalomesaconate (OMA) hydratase(pmcE), 4-oxalocitramalate (OCM) aldolase (pmcF), and transporter gene (pmcT). They were organized in the order of pmcT-pmcE-pmcF-pmcD-pmcA-pmcB-pmcC. The amino acid sequences deduced from the nucleotide sequences of pmcABCDEFT genes from Comamonas sp. strain DJ-12 exhibited 94 to $98\%$ homologies with those of Comamonas testosteroni BR6020 and Pseudomonas ochraceae NGJ1, but only 52 to $74\%$ with homologies Sphingomonas paucimobilis SYK-6, Sphingomonas sp. LB126, and Arthrobacter keyseri 12B.

• International Journal of Aeronautical and Space Sciences
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• v.10 no.1
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• pp.37-45
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• 2009

A method of conflict detection and resolution is described by using simple geometric approach. Two VAVs are dealt with and considered as point masses with constant velocity. This paper discusses en route aircraft which are assumed to be linked by real time data bases like ADS-B. With this data base, all DAVs share the information each other. Calculating PCA (Point of Closest Approach), we can evaluate the worst conflict condition between two VAVs. This paper proposes one resolution maneuvering logic, which can be called 'Vector Sharing Resolution'. In case of conflict, using miss distance vector in PCA, we can decide the directions for two VAVs to share the conflict region. With these directions, VAVs are going to maneuver cooperatively. First of all, this paper describes some '2-D' conflict scenarios and then extends to '3-D' conflict scenarios.

• The KIPS Transactions:PartB
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• v.13B no.4 s.107
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• pp.393-400
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• 2006

There are many feature extraction methods for face recognition. We need a new method to overcome the small sample problem that the number of feature variables is larger than the sample size for face image data. The paper considers partial least squares(PLS) as a new dimension reduction technique for feature vector. Principal Component Analysis(PCA), a conventional dimension reduction method, selects the components with maximum variability, irrespective of the class information. So, PCA does not necessarily extract features that are important for the discrimination of classes. PLS, on the other hand, constructs the components so that the correlation between the class variable and themselves is maximized. Therefore PLS components are more predictive than PCA components in classification. The experimental results on Manchester and ORL databases shows that PLS is to be preferred over PCA when classification is the goal and dimension reduction is needed.

• Korean Journal of Radiology
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• v.24 no.11
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• pp.1102-1113
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• 2023

Objective: To elucidate the use of radiological studies, including nuclear medicine, and biopsy for the diagnosis and staging of prostate cancer (PCA) in clinical practice and understand the current status of PCA in Asian countries via an international survey. Materials and Methods: The Asian Prostate Imaging Working Group designed a survey questionnaire with four domains focused on prostate magnetic resonance imaging (MRI), other prostate imaging, prostate biopsy, and PCA backgrounds. The questionnaire was sent to 111 members of professional affiliations in Korea, Japan, Singapore, and Taiwan who were representatives of their working hospitals, and their responses were analyzed. Results: This survey had a response rate of 97.3% (108/111). The rates of using 3T scanners, antispasmodic agents, laxative drugs, and prostate imaging-reporting and data system reporting for prostate MRI were 21.6%-78.9%, 22.2%-84.2%, 2.3%-26.3%, and 59.5%-100%, respectively. Respondents reported using the highest b-values of 800-2000 sec/mm² and fields of view of 9-30 cm. The prostate MRI examinations per month ranged from 1 to 600, and they were most commonly indicated for biopsy-naïve patients suspected of PCA in Japan and Singapore and staging of proven PCA in Korea and Taiwan. The most commonly used radiotracers for prostate positron emission tomography are prostate-specific membrane antigen in Singapore and fluorodeoxyglucose in three other countries. The most common timing for prostate MRI was before biopsy (29.9%). Prostate-targeted biopsies were performed in 63.8% of hospitals, usually by MRI-ultrasound fusion approach. The most common presentation was localized PCA in all four countries, and it was usually treated with radical prostatectomy. Conclusion: This survey showed the diverse technical details and the availability of imaging and biopsy in the evaluation of PCA. This suggests the need for an educational program for Asian radiologists to promote standardized evidence-based imaging approaches for the diagnosis and staging of PCA.

• 보존과학연구
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• s.6
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• pp.111-120
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• 1985

Data on the concentration of Na, K, Sc, Cr, Fe, Co, Cu, Ga, Rb, Cs, Ba, La,Ce, Sm, Eu, Tb, Lu, Hf, Ta and Th obtained by Neutron Activation Analysishave been used to characterise Korean porcelainsherds by multivariate analysis. The mathematical approaches employed is Principal Component Analysis(PCA).PCA was found to be helpful for dimensionality reduction and for obtaining information regarding (a) the number of independent causal variables required to account for the variability in the overall data set, (b) the extent to which agiven variable contributes to a component and(c) the number of causalvariables required to explain the total variability of each measured variable.

• The KIPS Transactions:PartB
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• v.12B no.6 s.102
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• pp.715-720
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• 2005

This paper presents a hybrid recognition method of first moment of face image and principal component analysis(PCA). First moment is applied to reduce the dimension by shifting to the centroid of image, which is to exclude the needless backgrounds in the face recognitions. PCA is implemented by single layer neural network which has a teaming rule of Foldiak algorithm. It has been used as an alternative method for numerical PCA. PCA is to derive an orthonormal basis which directly leads to dimensionality reduction and possibly to feature extraction of face image. The proposed method has been applied to the problems for recognizing the 48 face images(12 Persons $\ast$ 4 scenes) of 64$\ast$64 pixels. The 3 distances such as city-block, Euclidean, negative angle are used as measures when match the probe images to the nearest gallery images. The experimental results show that the proposed method has a superior recognition performances(speed, rate). The negative angle has been relatively achieved more an accurate similarity than city-block or Euclidean.