• Title/Summary/Keyword: (2D)2PCA

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Application of Principal Component Analysis and Self-organizing Map to the Analysis of 2D Fluorescence Spectra and the Monitoring of Fermentation Processes

  • Rhee, Jong-Il;Kang, Tae-Hyoung;Lee, Kum-Il;Sohn, Ok-Jae;Kim, Sun-Yong;Chung, Sang-Wook
    • Biotechnology and Bioprocess Engineering:BBE
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    • v.11 no.5
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    • pp.432-441
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    • 2006
  • 2D fluorescence sensors produce a great deal of spectral data during fermentation processes, which can be analyzed using a variety of statistical techniques. Principal component analysis (PCA) and a self-organizing map (SOM) were used to analyze these 2D fluorescence spectra and to extract useful information from them. PCA resulted in scores and loadings that were visualized in the score-loading plots and used to monitor various fermentation processes with recombinant Escherichia coli and Saccharomyces cerevisiae. The SOM was found to be a useful and interpretative method of classifying the entire gamut of 2D fluorescence spectra and of selecting some significant combinations of excitation and emission wavelengths. The results, including the normalized weights and variances, indicated that the SOM network is capable of being used to interpret the fermentation processes monitored by a 2D fluorescence sensor.

Automatic Denoising in 2D Color Face Images Using Recursive PCA Reconstruction (2D 칼라 얼굴 영상에서 반복적인 PCA 재구성을 이용한 자동적인 잡음 제거)

  • Park, Hyun;Moon, Young-Shik
    • Proceedings of the IEEK Conference
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    • 2005.11a
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    • pp.1157-1160
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    • 2005
  • The denoising and reconstruction of color images are increasingly studied in the field of computer vision and image processing. Especially, the denoising and reconstruction of color face images are more difficult than those of natural images because of the structural characteristics of human faces as well as the subtleties of color interactions. In this paper, we propose a denoising method based on PCA reconstruction for removing complex color noises on human faces, which is not easy to remove by using vectorial color filters. The proposed method is composed of the following five steps; training of canonical eigenface space using PCA, automatic extracting of face features using active appearance model, relighing of reconstructed color image using bilateral filter, extraction of noise regions using the variance of training data, and reconstruction using partial information of input images (except the noise regions) and blending of the reconstructed image with the original image. Experimental results show that the proposed denosing method efficiently removes complex color noises on input face images.

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Performance evaluation study of a commercially available smart patient-controlled analgesia pump with the microbalance method and an infusion analyzer

  • Park, Jinsoo;Jung, Bongsu
    • Journal of Dental Anesthesia and Pain Medicine
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    • v.22 no.2
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    • pp.129-143
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    • 2022
  • Background: Patient-controlled analgesia (PCA) has been widely used as an effective medical treatment for pain and for postoperative analgesia. However, improper dose errors in intravenous (IV) administration of narcotic analgesics from a PCA infusion pump can cause patient harm. Furthermore, opioid overdose is considered one of the highest risk factors for patients receiving pain medications. Therefore, accurate delivery of opioid analgesics is a critical function of PCA infusion pumps. Methods: We designed a microbalance method that consisted of a closed acrylic chamber containing a layer and an oil layer with an electronic balance. A commercially available infusion analyzer (IDA-5, Fluke Co., Everett, WA, USA) was used to measure the accuracy of the infusion flow rate from a commercially available smart PCA infusion pump (PS-1000, UNIMEDICS, Co., Ltd., Seoul, Korea) and compared with the results of the microbalance method. We evaluated the uncertainty of the flow rate measurement using the ISO guide (GUM:1995 part3). The battery life, delay time of the occlusion alarm, and bolus function of the PCA pump were also tested. Results: The microbalance method was good in the short-term 2 h measurement, and IDA-5 was good in the long-term 24 h measurement. The two measurement systems can complement each other in the case of the measurement time. Regarding battery performance, PS-1000 lasted approximately 5 days in a 1 ml/hr flow rate condition without recharging the battery. The occlusion pressure alarm delays of PS-1000 satisfied the conventional alarm threshold of occlusion pressure (300-800 mmHg). Average accuracy bolus volume was measured as 63%, 95%, and 98.5% with 0.1 ml, 1 ml, and 2 ml bolus volume presets, respectively. A 1 ml/hr flow rate measurement was evaluated as 2.08% of expanded uncertainty, with a 95% confidence level. Conclusion: PS-1000 showed a flow accuracy to be within the infusion pump standard, which is ± 5% of flow accuracy. Occlusion alarm of PS-1000 was quickly transmitted, resulting in better safety for patients receiving IV infusion of opioids. PS-1000 is sufficient for a portable smart PCA infusion pump.

A Study on Hand Shape Recognition using Edge Orientation Histogram and PCA (에지 방향성 히스토그램과 주성분 분석을 이용한 손 형상 인식에 관한 연구)

  • Kim, Jong-Min;Kang, Myung-A
    • Journal of Digital Contents Society
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    • v.10 no.2
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    • pp.319-326
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    • 2009
  • In this paper, we present an algorithm which recognize hand shape in real time using only image without adhering separate sensor. Hand recognizes using edge orientation histogram, which comes under a constant quantity of 2D appearances because hand shape is intricate. This method suit hand pose recognition in real time because it extracts hand space accurately, has little computation quantity, and is less sensitive to lighting change using color information in complicated background. Method which reduces recognition error using principal component analysis(PCA) method to can recognize through hand shape presentation direction change is explained. A case that hand shape changes by turning 3D also by using this method is possible to recognize. Human interface system manufacture technique, which controls a home electric appliance or game using, suggested method at experience could be applied.

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Structure Analysis of pmcABCDEFT Gene Cluster for Degradation of Protocatechuate from Comamonas sp. Strain DJ-12 (Comamonas sp. Strain DJ-12로부터 Protocatechuate의 분해에 관여하는 pmcABCDEFT 유전자군의 구조 분석)

  • Kang Cheol-Hee;Lee Sang-Mhan;Lee Kyoung;Lee Dong-Hun;Kim Chi-Kyung
    • 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.

Face Representation Based on Non-Alpha Weberface and Histogram Equalization for Face Recognition Under Varying Illumination Conditions (조명 변화 환경에서 얼굴 인식을 위한 Non-Alpha Weberface 및 히스토그램 평활화 기반 얼굴 표현)

  • Kim, Ha-Young;Lee, Hee-Jae;Lee, Sang-Goog
    • Journal of KIISE
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    • v.44 no.3
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    • pp.295-305
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    • 2017
  • Facial appearance is greatly influenced by illumination conditions, and therefore illumination variation is one of the factors that degrades performance of face recognition systems. In this paper, we propose a robust method for face representation under varying illumination conditions, combining non-alpha Weberface (non-alpha WF) and histogram equalization. We propose a two-step method: (1) for a given face image, non-alpha WF, which is not applied a parameter for adjusting the intensity difference between neighboring pixels in WF, is computed; (2) histogram equalization is performed to non-alpha WF, to make a uniform histogram distribution globally and to enhance the contrast. $(2D)^2PCA$ is applied to extract low-dimensional discriminating features from the preprocessed face image. Experimental results on the extended Yale B face database and the CMU PIE face database show that the proposed method yielded better recognition rates than several illumination processing methods as well as the conventional WF, achieving average recognition rates of 93.31% and 97.25%, respectively.

UAV Conflict Detection and Resolution Based on Geometric Approach

  • Park, Jung-Woo;Oh, Hyon-Dong;Tahk, Min-Jea
    • 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.

Aroma Pattern Analysis of Hanwoo Beef (M. longissimus) using Electronic Nose during Refrigerated Storage (전자 코를 이용한 한우 등심육의 냉장저장 중 향기 패턴 분석)

  • Lee Sung Ki;Kim Ju Yong;Kim Yong Sun
    • Food Science of Animal Resources
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    • v.24 no.3
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    • pp.260-265
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    • 2004
  • This study was carried out to investigate aroma patterns of Hanwoo (Korean cattle) beef using electronic nose during refrigerated storage, and to compare these results with chemical quality (pH, TBARS). The M. longissimus muscle from Hanwoo carcasses after 24 hrs postmortem was obtained and stored at 5${\pm}$1$^{\circ}C$ for 7 days. Sensitivity (dR/RO) values among electronic nose data were changed differently during refrigerated storage, and showed significant difference on the 7th day of storage (p<0.01). The dR/RO from SY/G, SY/AA, SY/Gh, SY/gCTl, SY/gCT decreased but those from SY/LG, T30/1, P10/1, P10/2, P40/1, T70/2, PA2 increased during storage for 7 days. Mapping these data using PCA (principal component analysis) showed that the 1st day data were present in the middle of the right side, the 3rd day data were present in bottom part of this area and the 7th day data spread out more widely on the left side. In case of DFA (discriminant factor analysis), the flock clustered round and located in different side clearly comparing with PCA plot. In analysis of correlation coefficients among electronic nose data and chemical quality data, there was significant correlation among sensor data (p<0.001). But pH and TBARS were not significantly correlated with electronic nose data. Consequently, PCA and DFA plot by electronic nose data showed difference during refrigerated storage and there were significant correlations among sensors. Therefore it will be possible to detect separate aroma patterns of Hanwoo beef using electronic nose.

Characterization of $\beta$-Ketoadipate Pathway from Multi-Drug Resistance Bacterium, Acinetobacter baumannii DU202 by Proteomic Approach

  • Park, Soon-Ho;Kim, Jae-Woo;Yun, Sung-Ho;Leem, Sun-Hee;Kahng, Hyung-Yeel;Kim, Seung-Il
    • Journal of Microbiology
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    • v.44 no.6
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    • pp.632-640
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    • 2006
  • In this study, the biodegradative activities of monocyclic aromatic compounds were determined from the multi-drug resistant (MDR) Acinetobacter baumannii, which were studied in the form of clinical isolates from a hospital in Korea. These bacteria were capable of biodegrading monocyclic aromatic compounds, such as benzoate and p-hydroxybenzoate. In order to determine which pathways are available for biodegradation in these stains, we conducted proteome analyses of benzoate, and p-hydroxybenzoate-cultured A. baumannii DU202, using 2-DE/MS analysis. As genome DB of A. baumannii was not yet available, MS/MS analysis or de novo sequencing methods were employed in the identification of induced proteins. Benzoate branch enzymes [catechol 1,2-dioxygenase (CatA) and benzoate dioxygenase $\alpha$ subunit (BenA)] of the $\beta$-ketoadipate pathway were identified under benzoate culture condition and p-hydroxybenzoate branch enzymes [protocatechuate 3,4-dioxygenas $\alpha$ subunit (PcaG) and 3-carboxy-cis,cis-muconate cycloisomerase (PcaR)] of the $\beta$-ketoadipate pathway were identified under p-hydroxybenzoate culture condition, respectively, thereby suggesting that strain DU202 utilized the $\beta$-ketoadipate pathway for the biodegradation of monocyclic aromatic compounds. The sequence analysis of two purified dioxygenases (CatA and PcaGH) indicated that CatA is closely associated with the CatA of Acinetobacter radiresistance, but PcaGH is only moderately associated with the PcaGH of Acinetobacter sp. ADPI. Interestingly, the fused form of PcaD and PcaC, carboxymuconolactone decarboxylase (PcaCD), was detected on benzoate-cultured A. baumannii DU202. These results indicate that A. baumannii DU202 exploits a different $\beta$-ketoadipate pathway from other Acinetobacter species.

ERS-1 AND CCRS C-SAR Data Integration For Look Direction Bias Correction Using Wavelet Transform

  • Won, J.S.;Moon, Woo-Il M.;Singhroy, Vern;Lowman, Paul-D.Jr.
    • Korean Journal of Remote Sensing
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    • v.10 no.2
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    • pp.49-62
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    • 1994
  • Look direction bias in a single look SAR image can often be misinterpreted in the geological application of radar data. This paper investigates digital processing techniques for SAR image data integration and compensation of the SAR data look direction bias. The two important approaches for reducing look direction bias and integration of multiple SAR data sets are (1) principal component analysis (PCA), and (2) wavelet transform(WT) integration techniques. These two methods were investigated and tested with the ERS-1 (VV-polarization) and CCRS*s airborne (HH-polarization) C-SAR image data sets recorded over the Sudbury test site, Canada. The PCA technique has been very effective for integration of more than two layers of digital image data. When there only two sets of SAR data are available, the PCA thchnique requires at least one more set of auxiliary data for proper rendition of the fine surface features. The WT processing approach of SAR data integration utilizes the property which decomposes images into approximated image ( low frequencies) characterizing the spatially large and relatively distinct structures, and detailed image (high frequencies) in which the information on detailed fine structures are preserved. The test results with the ERS-1and CCRS*s C-SAR data indicate that the new WT approach is more efficient and robust in enhancibng the fine details of the multiple SAR images than the PCA approach.