• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.8
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• pp.55-61
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• 2010

In this paper, we proposed selective extraction method of frequency information and PCA-ELM based diagnosis system for three-phase induction motors. As the first step for diagnosis procedure, DFT is performed to transform the acquired current signal into frequency domain. And then, frequency components are selected according to discriminate order calculated by variance As the next step, feature extraction is performed by principal component analysis (PCA). Finally, we used the classifier based on Extreme Learning Machine (ELM) with fast learning procedure. To show the effectiveness, the proposed diagnostic system has been intensively tested with the various data acquired under different electrical and mechanical faults with varying load.

• Convergence Security Journal
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• v.12 no.3
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• pp.3-10
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• 2012

This study aimed at making a way of securing the access by using PCA. We got our result through using Box-Plot and PCA with the access data of the area of security level A~E at K(IPS)center. In order to perform PCA, We confirmed the extracted value of commonality has no problem in performing PCA because VIF is below 2.902. Based on this result, We classified people into Green-list, Blue-list, Red-list, and Black-list in a standard of security level with 1.453, as the eigen value of 1 main element, 1.283, as eigen value of 2 main elementm, 1.142, as the eigen value of 3 main element.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.599-602
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• 2009

This paper presents a comparative analysis of five different fusion methods. The five different methods to merge multispectral images and panchromatic image are IHS, FIHS, PCA, BT and WT methods. The comparative analysis based on visual analysis and quantitative analysis are performed using the merged results. From the results the FIHS method provide good result, BT, PCA, IHS and WT method show the next order.

• Structural Monitoring and Maintenance
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• v.9 no.2
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• pp.179-200
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• 2022

This paper proposes a data-driven methodology for online early damage identification under changing environmental conditions. The proposed method relies on two data analysis methods: feature-based method and hybrid principal component analysis (PCA) and kernel PCA to separate damage from environmental influences. First, spectral sub-band features, namely, spectral sub-band centroids (SSCs) and log spectral sub-band energies (LSSEs), are proposed as damage-sensitive features to extract damage information from measured structural responses. Second, hybrid modeling by integrating PCA and kernel PCA is performed on the spectral sub-band feature matrix for data normalization to extract both linear and nonlinear features for nonlinear procedure monitoring. After feature normalization, suppressing environmental effects, the control charts (Hotelling T² and SPE statistics) is implemented to novelty detection and distinguish damage in structures. The hybrid PCA-KPCA technique is compared to KPCA by applying support vector machine (SVM) to evaluate the effectiveness of its performance in detecting damage. The proposed method is verified through numerical and full-scale studies (a Bridge Health Monitoring (BHM) Benchmark Problem and a cable-stayed bridge in China). The results demonstrate that the proposed method can detect the structural damage accurately and reduce false alarms by suppressing the effects and interference of environmental variations.

• Journal of East-West Nursing Research
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• v.16 no.1
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• pp.44-52
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• 2010

Purpose: The study examined the effects of preoperative patient controlled analgesia (PCA) education on postoperative pain, knowledge of PCA, and attitude toward pain medication. Methods: The participants were patients who underwent surgery in H University Hospital,and were assigned to PCA group (experiment group, n=30) or the control group (n=30). Results: Knowledge of PCA and positive attitude toward pain medication were higher in the experiment group than in the control group. Postoperative pain scores in the experiment group were significantly lower than those in the control group at 48 and 72 hr after surgery, but there was no significant difference at 24 hr after surgery. The experiment group had more positive attitudes on the medication than the control group. Conclusions: Preoperative PCA education could be an effective nursing intervention for pain management of patients after surgery.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2007.04a
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• pp.207-210
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• 2007

본 연구에서는 고해상도의 IKONOS panchromatic 영상과 multispectral 영상을 IHS와 PCA 방법으로 중합하고 그 결과를 비교하였다. 평가에 있어서는 중합된 영상들과 원영상간의 필셀 값에 대한 평균제곱근오차를 구하고 그 결과를 분석하였다. 분석 결과, multispectral band 1, 3, 4를 사용하는 IHS 방법, multispectral band 1, 2, 4를 사용하는 IHS 방법 및 multispectral band 1, 3, 4를 사용하는 PCA 방법이 원영상의 특성을 잘 보존하는 것으로 평가되었다.

• Proceedings of the Korean Information Science Society Conference
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• 2002.10d
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• pp.538-540
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• 2002

본 논문에서는 실시간 카메라 입력 영상에 적합한 얼굴 검출을 위해 다양한 외부적 환경에 덜 민감한 새로운 알고리즘을 제안한다. 빛이나 조명의 영향에 의한 오류를 방지하기 위해 전처리 과정을 포함시키고 형판 정합방법의 단점을 개선하기 위해 얼굴 인식에서 주로 쓰이는 방법인 주성분 분석(PCA :Principal Component Analyses) 변환을 적용하고. 생성된 주성분(Principal Component)을 선형 판별 분석(LDA: Linear Discriminant Analysis)의 입력으로 사용하는 방법을 통해 얼굴을 검출하도록 하였다. 실험을 위해 실제 환경과 같은 6개 카테고리의 동영상을 중심으로 실험한 결과, 본 논문에서 제안하는 방법이 기존의 PCA만을 이용한 방법보다 좋은 성능을 보여줌을 알 수 있었다.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.6
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• pp.642-653
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• 2008

This study deals with modeling of head-related transfer functions(HRTFs) using principal components analysis(PCA) in the time and frequency domains. Four PCA models based on head-related impulse responses(HRIRs), complex-valued HRTFs, augmented HRTFs, and log-magnitudes of HRTFs are investigated. The objective of this study is to compare modeling performances of the PCA models in the least-squares sense and to show the theoretical relationship between the PCA models. In terms of the number of principal components needed for modeling, the PCA model based on HRIR or augmented HRTFs showed more efficient modeling performance than the PCA model based on complex-valued HRTFs. The PCA model based on HRIRs in the time domain and that based on augmented HRTFs in the frequency domain are shown to be theoretically equivalent. Modeling performance of the PCA model based on log-magnitudes of HRTFs cannot be compared with that of other PCA models because the PCA model deals with log-scaled magnitude components only, whereas the other PCA models consider both magnitude and phase components in linear scale.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.11
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• pp.6733-6738
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• 2013

Multiple genetic studies have confirmed association of 8q24 variants with susceptibility to prostate cancer (PCa). As PCa risk SNPs may also influence disease outcome, we studied here eight 8q24 risk alleles, and evaluated their role in PCa clinical covariates in northern Chinese men. Blood samples and clinical information were collected from ethnically Chinese men from Northern China with histologically-confirmed PCa (n=289) and from age-matched normal controls (n=288). Eight 8q24 SNPs were genotyped by polymerase chain reaction-high- resolution melting analysis in 577 subjects. We examined the prevalence distribution of 8q24 risk alleles and analyzed the associations between the risk allele and PCa and clinical covariates to infer their impact on aggressive PCa. Three of the eight SNPs were associated with PCa risk in northern Chinese men, including rs16901966 (OR 1.31, 95% CI 1.01-1.70, p=0.042), rs1447295 (OR 1.47, 95% CI 1.09-1.98, p=0.011) and rs10090154 (OR 1.55, 95% CI 1.14-2.12, p=0.005). Haplotype analysis based association with the risk alleles revealed significant differences between cases and controls (OR 1.43, 95%CI 0.99-2.06, p=0.049). The risk alleles rs16901966, rs1447295 and rs10090154 were associated with age at diagnosis and tumor stage as compared with controls, while rs16901966 was associated with aggressive PCa (OR 1.43, 95% CI 1.01-2.03, p=0.042). The evidence for 8q24 SNPs with PCa risk in northern Chinese men showed rs16901966, rs1447295 and rs10090154 at 8q24 (region 1, region 2) to be strongly associated with PCa and clinical covariates. The three SNPs at 8q24 could be PCa susceptible genetic markers in northern Chinese men.

• Korean Journal of Plant Resources
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• v.27 no.4
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• pp.271-278
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• 2014

Rubus coreanus has been used as a traditional medicine in Asia because of its various pharmacological properties. This study examined the effects of protocatechuic acid (PCA), one of phenolic compounds derived from R. coreanus on the lipid metabolism in high cholesterol diet-induced mice. A total of 30 male C57BL/6 mice were divided into 5 groups with 6 mice in each group as follows: (1) Control mice received normal diet (ND). (2) Mice received high-cholesterol diet (HCD) plus water, 10% sucrose solution and treated daily oral phosphate-buffered-saline (PBS) of equal volumes through gavage. (3) Mice received HCD and treated daily with 25 mg/kg b.w./day of PCA (4) with 50 mg/kg b.w./day or (5) with 10 mg/kg b.w./day of simvastatin via oral gavage for 12 weeks. Body weights were measured weekly for a period of experiment. After treatment, liver, thymus, spleen and kidney were harvested and weighed, and the lipid metabolite profiles (total cholesterol, triglyceride (TG), HDL-cholesterol (HDL-c), LDL-cholesterol (LDL-c) and liver-damaging markers (GOT and GPT) in serum were examined. PCA significantly reduced the total cholesterol, TG, LDL-c level and increased the HDL-c level. PCA administration also significantly reduced the levels of GOT and GPT. These results indicate that the PCA could be used as a functional material for lowering lipid and an adjuvant for the treatment of hyperlipemia.