• Proceedings of the Korean Information Science Society Conference
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• 2001.10b
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• pp.304-306
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• 2001

Various methods for blind source separation (BSS) are based on independent component analysis (ICA) which can be viewed as a nonlinear extension of principal component analysis (PCA). Most existing ICA methods require certain nonlinear functions, the shapes of which depend on the probability distributions of sources (which is not known in advance), whereas FCA is a linear learning method based on only second-order statistics. In this paper we show how BSS can be achieved by FCA, provided that sources are spatially uncorrelated but temporally correlated.

• The KIPS Transactions:PartB
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• v.16B no.5
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• pp.377-384
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• 2009

A new algorithm in order to classify various contents in the image documents, such as text, figure, graph, table, etc. is proposed in this paper by classifying contents using texture-based PCA, and by segmenting document images using local entropy-based histogram. Local entropy and histogram made the binarization of image document not only robust to various transformation and noise, but also easy and less time-consuming. And texture-based PCA algorithm for each segmented region was taken notice of each content in the image documents having different texture information. Through this, it was not necessary to establish any pre-defined structural information, and advantages were found from the fact of fast and efficient classification. The result demonstrated that the proposed method had shown better performances of segmentation and classification for various images, and is also found superior to previous methods by its efficiency.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.11B
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• pp.1339-1345
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• 2011

Red tide is a natural phenomenon that change sea color by harmful algal blooms. There have been many studies on red tide due to increasing of red tide damage. However, to automatically classify the red tide algae is not enough. Recognition of red tide algae is difficult because they do not have matching center features for recognizing algae image object. Previously studies are used a few type of red tide algae for classification. In this paper, we proposed the red tide algae recognition method using PCA and roundness of image objects.

• The Korean Journal of Nuclear Medicine Technology
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• v.19 no.1
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• pp.12-16
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• 2015

Purpose Principal component analysis (PCA) is a method often used in the neuroimagre analysis as a multivariate analysis technique for describing the structure of high dimensional correlation as the structure of lower dimensional space. PCA is a statistical procedure that uses an orthogonal transformation to convert a set of observations of correlated variables into a set of values of linearly independent variables called principal components. In this study, in order to investigate the usefulness of PCA in the brain PET image analysis, we tried to analyze C[11]-PIB PET image as a representative case. Materials and Methods Nineteen subjects were included in this study (normal = 9, AD/MCI = 10). For C[11]-PIB, PET scan were acquired for 20 min starting 40 min after intravenous injection of 9.6 MBq/kg C[11]-PIB. All emission recordings were acquired with the Biograph 6 Hi-Rez (Siemens-CTI, Knoxville, TN) in three-dimensional acquisition mode. Transmission map for attenuation-correction was acquired using the CT emission scans (130 kVp, 240 mA). Standardized uptake values (SUVs) of C[11]-PIB calculated from PET/CT. In normal subjects, 3T MRI T1-weighted images were obtained to create a C[11]-PIB template. Spatial normalization and smoothing were conducted as a pre-processing for PCA using SPM8 and PCA was conducted using Matlab2012b. Results Through the PCA, we obtained linearly uncorrelated independent principal component images. Principal component images obtained through the PCA can simplify the variation of whole C[11]-PIB images into several principal components including the variation of neocortex and white matter and the variation of deep brain structure such as pons. Conclusion PCA is useful to analyze and extract the main pattern of C[11]-PIB image. PCA, as a method of multivariate analysis, might be useful for pattern recognition of neuroimages such as FDG-PET or fMRI as well as C[11]-PIB image.

• Journal of Korean Medical Science
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• v.33 no.47
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• pp.303.1-303.10
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• 2018

Background: Cell division cycle 6 (CDC6) is an essential regulator of DNA replication and plays important roles in the activation and maintenance of the checkpoint mechanisms in the cell cycle. CDC6 has been associated with oncogenic activities in human cancers; however, the clinical significance of CDC6 in prostate cancer (PCa) remains unclear. Therefore, we investigated whether the CDC6 mRNA expression level is a diagnostic and prognostic marker in PCa. Methods: The study subjects included 121 PCa patients and 66 age-matched benign prostatic hyperplasia (BPH) patients. CDC6 expression was evaluated using real-time polymerase chain reaction and immunohistochemical (IH) staining, and then compared according to the clinicopathological characteristics of PCa. Results: CDC6 mRNA expression was significantly higher in PCa tissues than in BPH control tissues (P = 0.005). In addition, CDC6 expression was significantly higher in patients with elevated prostate-specific antigen (PSA) levels (> 20 ng/mL), a high Gleason score, and advanced stage than in those with low PSA levels, a low Gleason score, and earlier stage, respectively. Multivariate logistic regression analysis showed that high expression of CDC6 was significantly associated with advanced stage (${\geq}T3b$) (odds ratio [OR], 3.005; confidence interval [CI], 1.212-7.450; P = 0.018) and metastasis (OR, 4.192; CI, 1.079-16.286; P = 0.038). Intense IH staining for CDC6 was significantly associated with a high Gleason score and advanced tumor stage including lymph node metastasis stage (linear-by-linear association, P = 0.044 and P = 0.003, respectively). Conclusion: CDC6 expression is associated with aggressive clinicopathological characteristics in PCa. CDC6 may be a potential diagnostic and prognostic marker in PCa patients.

• Biomolecules & Therapeutics
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• v.2 no.2
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• pp.108-113
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• 1994

Toxicity study of recombinant hepatitis B vaccine (LBD-008), a newly developed drug for acute and chronic hepatitis, was investigated in mice and guinea pigs. 1. Mice showed no production of antibodies against LBD-008 inoculated with aluminum hydroxide gel (Alum) as an adjuvant, judged by the heterologous anaphylaxis (PCA) test using rats. On the other hand, antibodies against ovalbumin (OVA) inoculated with alum were definitely detected. 2. In the studies with guinea pigs, both the inoculation of LBD-008 only and of LBD-008 with complete Freund's adjuvant (CFA) as an adjuvant did not produce positive reactions in any of homologous active systemic anaphylaxis (ASA). On the other hand, the inoculation of ovalbumin with complete Freund's adjuvant (CFA) produced positive reaction in both of PCA and ASA. 3. These findings suggested that LBD-008 has no antigenic potential in mice or guinea pigs.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.12
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• pp.6273-6276
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• 2012

Background/Aim: Six prostate cancer (PCa) susceptibility loci were identified in a genome-wide association study (GWAS) in populations of European decent. However, the associations of these 6 single-nucleotide polymorphisms (SNPs) with PCa has remained tobe clarified in men in Northern China. This study aimed to explore the loci associated with PCa risk in a Northern Chinese population. Methods: Blood samples and clinical information of 289 PCa patients and 288 controls from Beijing and Tianjin were collected. All risk SNPs were genotyped using polymerase chain reaction (PCR)-high resolution melting curve technology and gene sequencing. Associations between PCa and clinical covariates (age at diagnosis, prostate-specific antigen [PSA], Gleason score, tumor stage, and level of aggressiveness) and frequencies of alleles and genotypes of these SNPs were analyzed using genetic statistics. Results: Among the candidate SNPs, 11p15 (rs7127900, A) was associated with PCa risk (P = 0.02, odds ratio [OR] = 1.64, 95% confidence interval [CI] = 1.09-2.46). Genotypes showed differences between cases and controls on 11p15 (rs7127900, A), 11q13 (rs7931342, T), and HNF1B (rs4430796, A) (P = 0.03, P = 0.01, and P = 0.04, respectively). The genotype TG on 11q13 (rs7931342, T) was positively associated with an increased Gleason score (P = 0.04, OR = 2.15, 95% CI = 1.02-4.55). Patients carrying TG on 17q24 (rs1859962, G) were negatively associated with an increased body mass index (BMI) (P = 0.03, OR = 0.44, 95% CI = 0.21-0.92) while those with AG on HNF1B (rs4430796, A) were more likely to have PSA increase (P = 0.002). Conclusion: Our study suggests that 11p15 (rs7127900, A) could be a susceptibility locus associated with PCa in Northern Chinese. Genotype TG on 11q13 (rs7931342, T) could be related to an increased Gleason score, AG on HNF1B (rs4430796, A) could be associated with PSA increase, and TG on 17q24 (rs1859962, G) could be negatively associated with an increased BMI in Chinese men with PCa.

• Korean Journal of Acupuncture
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• v.25 no.1
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• pp.213-227
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• 2008

Objectives : We studied on anti-allergic effects of Semen Perillae Herbal Acupuncture(SPHA) and Semen Perillae Herbal Acupuncture Solution(SP). Methods : In vivo, Animals were herbal-acupunctured SPHA at both ST36 three times for 5 days. Then, we investigated compound 48/80-induced active systemic anaphylaxis (ASA) using ICR mice and anti-DNP IgE-induced passive cutaneous anaphylaxis (PCA) using Sprague Dawley rat. In vitro, we measured cell viability, b-hexosaminidase release, IL-4 and TNF-a from RBL-2H3 cells after treatment of SP of various concentrations. Results : In vivo, SPHA pretreatments at both ST36 inhibited compound 48/80-induced ASA. PCA was inhibited by SPHA pretreatments at both ST36 and optional points. In vitro, SP treatments were not affect on cell viability and inhibited b-hexosaminidase release, IL-4 and TNF-a. Conclusions : These results suggest that SPHA and SP may be beneficial in the inhibition of allergic inflammatory response.

• Korean Journal of Acupuncture
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• v.25 no.1
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• pp.197-211
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• 2008

Objectives : We studied on anti-allergic effects of Arctii Fructus Herbal Acupuncture(AFHA) and Arctii Fructus Herbal Acupuncture Solution(AF). Methods : In vivo, Animals were herbal-acupunctured AFHA at both ST36 three times for 5 days. Then, we investigated compound 48/80-induced active systemic anaphylaxis(ASA) using ICR mice and anti-DNP IgE-induced passive cutaneous anaphylaxis(PCA) using Sprague Dawley rat. In vitro, we measured cell viability, b-hexosaminidase, IL-4 and TNF-a release from RBL-2H3 cells after treatment of AF of various concentrations. Results : In vivo, AFHA pretreatments at both ST36 inhibited compound 48/80-induced ASA. PCA was inhibited by AFHA pretreatments at both ST36. In vitro, AF treatments were not affect on cell viability and inhibited b-hexosaminidase, IL-4 and TNF-a release. Conclusions : These results suggest that AFHA and AF may be beneficial in the inhibition of allergic inflammatory response.

• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.2
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• pp.111-119
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• 2013

Face recognition has recently become one of the most popular research areas in the fields of computer vision, machine learning, and pattern recognition because it spans numerous applications, such as access control, surveillance, security, credit-card verification, and criminal identification. In this paper, we propose a simple descriptor called an ECSP(Extended Center-Symmetric Pattern) for illumination-robust face recognition. The ECSP operator encodes the texture information of a local face region by emphasizing diagonal components of a previous CS-LBP(Center-Symmetric Local Binary Pattern). Here, the diagonal components are emphasized because facial textures along the diagonal direction contain much more information than those of other directions. The facial texture information of the ECSP operator is then used as the input image of an image covariance-based feature extraction algorithm such as 2D-PCA(Two-Dimensional Principal Component Analysis). Performance evaluation of the proposed approach was carried out using various binary pattern operators and recognition algorithms on the Yale B database. The experimental results demonstrated that the proposed approach achieved better recognition accuracy than other approaches, and we confirmed that the proposed approach is effective against illumination variation.