• Biotechnology and Bioprocess Engineering:BBE
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• 제11권5호
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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.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2005년도 추계종합학술대회
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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.

• Journal of Dental Anesthesia and Pain Medicine
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• 제22권2호
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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.

• 디지털콘텐츠학회 논문지
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• 제10권2호
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• pp.319-326
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• 2009

본 논문에서는 별도의 센서를 부착하지 않고 영상만을 이용하여 실시간으로 손 형상을 인식하는 알고리즘에 대해 기술한다. 손은 형상이 매우 복잡하기 때문에 2차원 형상의 불변량에 해당하는 에지의 방향성 히스토그램을 이용하여 인식을 행한다. 이 방법은 복잡한 배경에서 피부색을 지닌 손 영역이 정확히 추출되며 손 형상을 인식하는데 있어서 수행속도가 빠르고 조명변화에 덜 민감하기 때문에 실시간 손 형상 인식에 적합하다. 본 논문에서는 손의 형상에서 방향이 틀어지는 경우에도 인식을 가능하게 하기위해 주성분 분석법을 사용하여 인식오차를 줄이는 방법을 기술한다. 이 방법을 사용함으로써 손 영상이 3차원적으로 회전에 의해 변하는 경우도 인식가능하게 되었다. 본 논문에서 제안하는 방법은 가정용 가전제품이나 게임을 제어하는 실시간 휴먼 인터페이스 제작에 사용 할 수 있다.

• 미생물학회지
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• 제41권3호
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• pp.195-200
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• 2005

Comamonas sp. strain DJ-12의 pmcABCDEFT 유전자군은 protocatechuate (PCA)의 분해과정에 관여하는 PCA 4,5-dioxygenase, 4-carboxy-2hydroxymuconic semialdehyde (CHMS) dehydrogenase, 2-pyrone04,5-dicarboxylate(PDC) hydrolase, 4-oxalomesaconate (OMA) hydratase, 그리고 4-oxalocitramalate (OCM) aldolase 등의 효소들을 생산하는 유전자들과 transporter의 역학을 하는 유전자로 각각 확인되었다. 이 유전자군은 Comamonas sp. strain DJ-12의 chromosomal DNA로부터 얻은 PCR 산물들을 T-vector에 ligation하여 재조합 플라스미드 pMT1, pMT2, pMT3, pMT4, pMT5, pMT6, pMT7, pMT8, pMT9, pMT10을 제조하였다. 이들 재조합 플라스미드의 염기서열을 분석한 결과 PCA 4,5-dioxygenase 유전자는 alpha(pmcA)와 beta(pmcB) 두 개의 subunit으로 구성 되어있으며, 각각 450 bp와 870 bp이었다. CHMS dehydrogenase 유전자(pmcC)는 960 bp, PDC hydrolase 유전자(pmcD)는 918 bp이였으며, OMA hydratase 유전자(pmcE)는 1029 bp, OCM aldolase 유전자 (pmcF)는 689 bp, 그리고 transporter 유전자(pmcT)는 1,398 bp이였다. 이들 pmc 유전자들은 pmcT-pmcE-pmcF-pmcD-pmcA-pmcB-pmcC의 순서로 배열되어 있었다. Comamonas sp. strain DJ-12의 pmcABCDEFT 유전자산물의 아미노산 서열을 분석한 결과, Comamonas testosteroni BR6020 및 Psedomonas ochraceae NG.J1와 $94{\~}98\%$의 높은 유사성을 보였고, 그 유전자들의 배열 순서도 동일하였다. 그러나 Sphingomonas paucimobilis SYK-6, Sphingomonas sp. LB126, 그리고 Arthrobacter keyser 12B와는 아미노산 서열이 $52{\~}74\%$의 유사성을 보였고, 그 유전자의 배열 구조도 상이하였다.

• 정보과학회 논문지
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• 제44권3호
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• pp.295-305
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• 2017

얼굴 외형은 조명의 영향을 크게 받기 때문에 조명 변화는 얼굴 인식 시스템의 성능을 저하시키는 요인 중 하나이다. 본 논문에서는 non-alpha Weberface(non-alpha WF)와 히스토그램 평활화를 결합하여 조명 변화에 강건한 얼굴 표현 방법을 제안한다. 먼저, 입력 얼굴 영상에 대해 명암 대비 조절 파라미터를 적용하지 않은 non-alpha WF를 생성한다. 이후, non-alpha WF의 히스토그램 분포를 전역적으로 균일하게 하고 명암 대비를 향상시키기 위해 히스토그램 평활화를 수행한다. 제안하는 방법을 통해 전처리된 얼굴 영상으로부터 저차원 판별 특징을 추출하기 위해 $(2D)^2PCA$를 적용한다. Extended Yale B 및 CMU PIE 얼굴 데이터베이스에 대해 실험한 결과, 제안하는 방법으로 각각 93.31%와 97.25%의 평균 인식률을 얻었다. 또한, 제안하는 방법은 기존 WF뿐만 아니라 여러 조명 처리 방법들과 비교하여 향상된 인식 성능을 보였다.

• International Journal of Aeronautical and Space Sciences
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• 제10권1호
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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.

• 한국축산식품학회지
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• 제24권3호
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• pp.260-265
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• 2004

본 연구는 전자 코 시스템을 이용하여 센서의 감응도, 주성분 분석, 판별분석을 통해 한우육의 향기 패턴을 구명하고, 이를 pH 및 TBARS 값과 비교함으로써 쇠고기의 신속한 향기 평가방법의 가능성을 모색하기 위해 실시하였다. 시료는 도축 후 24시간이 경과한 쇠고기의 등심을 5$\pm$1$^{\circ}C$에서 7일간 저장하면서 실험에 사용하였다. 저장기간이 증가함에 따라 SY/G, SY/AA, SY/Gh, SY/gCTl, SY/gCT 센서의 감응도(dR/R0) 값은 감소하였으나, SY/LG, T30/1, P10/1, P10/2, P40/1, T70/2, PA2 센서의 dR/R0 값은 증가하였다. 저장 1일과 3일째에서는 dR/R0 값이 SY/AA#, T70/2 센서에서만 유의적인 차이를 보였으나(p<0.05), 저장 7일째에서 저장1일과 비교하였을 때 12개의 센서가 모두 유의적인 차이를 보였다(p<0.05). 감응도의 결과를 주성분 분석으로 mapping 하였을 때 저장 1일에 오른쪽 중간, 3일에 오른쪽 하단, 7일에 왼쪽에 길게 퍼져 군락이 형성되었다. 다시 판별분석으로 mapping을 하면 동일 저장기간내 군락이 집중되고, 저장기간별 군락군이 분산되어 뚜렷하게 구별되었다. 저장기간동안 육의 pH와 TBARS는 모두 어떤 항목과도 상관성을 보이지 않았으나, 모든 센서의 값이 각각 정 또는 역의 높은상관성을 가지고 있었다(p<0.001).

• Journal of Microbiology
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• 제44권6호
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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.

• 대한원격탐사학회지
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• 제10권2호
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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.