• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.1183-1187
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• 2003

Five new satellite image interpretation modules are developed. The modules are for: 1) construction of a realistic color image, 2) feature recognition by intensity filtering, 3) removal of spurious spots by next -neighbor count comparison, 4) deviation-amplification filtering, and 5) feature recognition by spectral distribution pattern. The modules were applied to a set of IKONOS images of 8 x 8 km area of the city of Daejeon, Korea, to recognize the distribution of various features such as water resources, playgrounds, forests, etc.

• 대한원격탐사학회지
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• 제16권2호
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• pp.135-143
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• 2000

Ocean Scanning Multispectral Imager (OSMI) is a payload on the Korean Multi-Purpose SATellite (KOMPSAT) to perform global ocean color monitoring for the study of biological oceanography. HOMPSAT was launched 21 December 1999. The radiometric performance of OSMI is analyzed for various gain settings in the viewpoint of the instrument developer for OSMI calibration and application based on its ground performance data measured before launch. The radiometric response linearity and dynamic range are analyzed and the dynamic range is compared with the nominal input radiance for the ocean and the land. The noise equivalent radiance (NER) corresponding to the instrument radiometric noise is compared with the radiometric resolution of signal digitization (1-count equivalent radiance). The best gain setting of OSMI for ocean monitoring is recommended. This analysis is considered to be useful for the OSMI mission and operation planning, the OSMI image data calibration, and users' understanding about OSMI image quality.

• 분석과학
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• 제30권6호
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• pp.348-354
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• 2017

이 연구는 출산 후 1, 3, 6주가 경과한 산모에서 얻은 모유의 단백체 발현 양상과 과 발현 단백질을 검출하는 것을 목적으로 하였다. 샷 건 정량 단백체 분석법을 이용하여 모유 중의 단백질을 동정하였고, 각 수유단계 간에 정량적 비교를 하였다. 각 주의 모유 샘플은 두 명의 산모로부터 얻어진 모유를 혼합하였고, 각 샘플 마다 3회 반복 실험을 하였다. Casein은 모유 내에 가장 많이 존재하는 단백질로서 실험의 정확성을 위하여 제거하였고, 트립신을 이용한 절편 화로 모유 단백질들을 펩타이드로 변환하였다. 처리된 펩타이드들은 역상 C18 미세관 크로마토그래피 및 이온-트랩 질량분석기를 이용하여 분석하였으며, Spectra Counting으로 단백질의 정량적 비교를 하였다. 각 샘플 당, 80-109 개의 단백질을 중복 제거한 후 동정하였다. 당화 단백질, metabolic enzyme, 및 lactoferrin, Carboxylic ester hydrolase, Clusterin을 포함하는 chaperon 효소들이 주로 검출되었다. 각 반복실험에서 재현성 있게 검출되는 63개의 단백질에 대한 정량적 비교분석 결과 25개의 단백질이 통계적으로 유의하게 수유단계에 따라 변화하는 것을 확인할 수 있었고, 특히 Ig lambda-7 chain C region과 Tenascin은 시간에 따라 현저하게 감소하였다. 향후 이와 같은 수유 단계에 따른 모유 내 단백의 변화가 생리적으로 가지는 의미에 관하여 추가적인 연구가 필요하다 생각된다.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1247-1247
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• 2001

Constituents of animal biofluids such as milk, blood and urine contain information specifically related to metabolic and health status of the ruminant animals. Some changes in composition of biofluids can be attributed to disease response of the animals. Mastitis is a major problem for the global dairy industry and causes substantial economic losses from decreasing milk production and reducing milk quality. The purpose of this study was to investigate potential of NIRS combined with multivariate analysis for cow's mastitis diagnosis based on NIR spectra of milk, blood and urine. A total of 112 bulk milk, urine and blood samples from 4 Holstein cows were analyzed. The milk samples were collected from morning milking. The urine samples were collected before morning milking and stored at -35$^{\circ}C$ until spectral analysis. The blood samples were collected before morning milking using a catheter inserted into the carotid vein. Heparin was added to blood samples to prevent coagulation. All milk samples were analyzed for somatic cell count (SCC). The SCC content in milk was used as indicator of mastitis and as quantitative parameter for respective urine and blood samples collected at same time. NIR spectra of blood and milk samples were obtained by InfraAlyzer 500 spectrophotometer, using a transflectance mode. NIR spectra of urine samples were obtained by NIR System 6500 spectrophotometer, using 1 mm sample thickness. All samples were divided into calibration set and test set. Class variable was assigned for each sample as follow: healthy (class 1) and mastitic (class 2), based on milk SCC content. SIMCA was implemented to create models of the respective classes based on NIR spectra of milk, blood or urine. For the calibration set of samples, SIMCA models (model for samples from healthy cows and model for samples from mastitic cows), correctly classified from 97.33 to 98.67% of milk samples, from 97.33 to 98.61% of urine samples and from 96.00 to 94.67% of blood samples. From samples in the test set, the percent of correctly classified samples varied from 70.27 to 89.19, depending mainly on spectral data pretreatment. The best results for all data sets were obtained when first derivative spectral data pretreatment was used. The incorrect classified samples were 5 from milk samples,5 and 4 from urine and blood samples, respectively. The analysis of changes in the loading of first PC factor for group of samples from healthy cows and group of samples from mastitic cows showed, that separation between classes was indirect and based on influence of mastitis on the milk, blood and urine components. Results from the present investigation showed that the changes that occur when a cow gets mastitis influence her milk, urine and blood spectra in a specific way. SIMCA allowed extraction of available spectral information from the milk, urine and blood spectra connected with mastitis. The obtained results could be used for development of a new method for mastitis detection.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.4105-4105
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• 2001

Near infrared spectroscopy (NIRS) was employed to qualify and quantify on survival, the injury rate and apoptosis of the human breast cancer cell line MCF-7 cells. MCF-7 cells were cultured in RPMI medium supplemented with 10% FCS in a 95% air and 5% CO2 atmosphere at 37$^{\circ}C$. For the viable cells preparation, cells were de-touched by 0.1% of trypsin treatment and washed with RPMI supplemented with 10% FCS medium by centrifugation at 1000 rpm for 3min. For the dead cells preparation, cells were de-touched by a cell scraper. The cells were counted by a hemacytometer, and the viability was estimated by the exclusion method with frypan blue dye. Each viable and dead cells were suspended in PBS (phosphate bufferred saline) or milk at the cell density desired. For the quantitative determination of cell death by measuring the LDH (lactate dehydrogenase) activity liberated from cells with cell membrane injuries, LDH-Cytotoxic Test Wako (Wako, Pure Pharmaceutical Co. Ltd., Japan) was used. We found that NIRS measurement of MCF-7 cells at the density range could evaluate and monitor the different characteristics of living cells and dead cells. The spectral analysis was performed in two wavelength ranges and with 1,4, 10 mm pathlength. Different spectral data pretreatment and chemometrics methods were used. We applied SIMCA classificator on spectral data of living and dead cells and obtained good accuracy when identifying each class. Bigger variation in the spectra of living cells with different concentrations was observed when compared to the same concentrations of dead cells. PLS was used to measure the number of cells in PBS. The best model for measurement of dead cells, as well as living cells, was developed when raw spectra in the 600-1098 nm region and 4 mm pathlength were used. Smoothing and second derivative spectral data pretreatment gave worst results. The analysis of PLS loading explained this result with the scatter effect found in the raw spectra and increased with the number of cells. Calibration for cell count in the 1100-2500 nm region showed to be very inaccurate.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.4104-4104
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• 2001

Milk somatic cell count (SCC) is a recognized indicator of cow health and milk quality. The potential of near infrared (NIR) spectroscopy in the region from 1100 to 2500nm to measure SCC content of cow milk was investigated. A total of 196 milk samples from 7 Holstein cows were collected for 28 days, consecutively, and analyzed for fat, protein, lactose and SCC. Three of the cows were healthy, and the rest had mastitis periods during the experiment. NIR transflectance milk spectra were obtained by the InfraAlyzer 500 spectrophotometer in a wavelength range from 1100 to 2500 nm. The calibration for logSCC was performed using partial least square (PLS) regression and different spectral data pretreatment. The best accuracy of determination was found for equation, obtained using smoothed absorbance data and 10 PLS factors. The standard error of calibration was 0.361, calibration coefficient of multiple correlation 0.868, standard error of prediction for independent validation set of samples 0.382, correlation coefficient 0.854 and the variation coefficient 7.63%. The accuracy of logSCC determination by NIR spectroscopy would allow health screening of cows, and differentiation between healthy and mastitic milk samples. When the spectral information was studied it has been found that SCC determination by NIR milk spectra was indirect and based on the related changes in milk composition. In the case of mastitis, when the disease occurred, the most significant factors that simultaneously influenced milk spectra were alteration of milk proteins and changes in ionic concentration of milk.

• Korean Journal of Radiology
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• 제23권9호
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• pp.854-865
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• 2022

Photon-counting detector (PCD) CT is a new CT technology utilizing a direct conversion X-ray detector, where incident X-ray photon energies are directly recorded as electronical signals. The design of the photon-counting detector itself facilitates improvements in spatial resolution (via smaller detector pixel design) and iodine signal (via count weighting) while still permitting multi-energy imaging. PCD-CT can eliminate electronic noise and reduce artifacts due to the use of energy thresholds. Improved dose efficiency is important for low dose CT and pediatric imaging. The ultra-high spatial resolution of PCD-CT design permits lower dose scanning for all body regions and is particularly helpful in identifying important imaging findings in thoracic and musculoskeletal CT. Improved iodine signal may be helpful for low contrast tasks in abdominal imaging. Virtual monoenergetic images and material classification will assist with numerous diagnostic tasks in abdominal, musculoskeletal, and cardiovascular imaging. Dual-source PCD-CT permits multi-energy CT images of the heart and coronary arteries at high temporal resolution. In this special review article, we review the clinical benefits of this technology across a wide variety of radiological subspecialties.

• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 2017년도 춘계공동학술대회
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• pp.40-40
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• 2017

본 연구는 빛의 파장대가 넓어 보다 다양한 접근과 검출이 가능한 초분광 카메라 (VNIR spectral camera PS, SPECIN Filand)를 이용하여 정식시기가 다른 배추를 생육단계별로 영상을 취득한 후 배추 캐노피의 전 파장 (400~1000nm)으로 생육 추정모델을 개발하기 위해 수행하였다. 정식시기가 다른 배추를 생육단계별로 초분광 카메라로 영상을 취득한 후 취득된 영상 ($348{\times}1040$)을 ENVI (ver. 5.2, Exelis Visual Information Solutions, USA) 프로그램을 이용하여 식생지수 NDVI로 작물과 배경을 구분하였다. 배추 캐노피 영역에 전 파장을 산출한 후 반사판 영역의 전 파장을 이용하여 광 보정된 반사율을 산출하였다. 통계 프로그램인 R Project (ver.3.3.3, Development Core Team, Vienna, Austria)를 이용하여 배추의 반사율과 계측한 생육 정보를 PLSR (Partial least squares regression) 분석하여 정확도($R^2$) 및 정밀도 (RMSE [g,cm,count], RE [%])로 나타내었고 그 모델은 full-cross validation (FV) 하여 타당성을 검증하였다. 정식시기가 다른 배추의 모든 생육단계의 생육정보를 이용하여 PLSR (Partial least squares regression) 결과 엽장을 추정한 모델의 $R^2$는 84% 이상의 정확도와 RMSE 3.2cm 이하의 좋은 정밀도를 보였다. 엽폭을 추정한 모델의 $R^2$는 73% 이상의 정확도와 RMSE 3.5cm 이하의 정밀도를 보였고 엽수를 추정한 모델의 $R^2$는 93% 이상의 정확도와 RMSE 6.3Count 이하의 정밀도로 보여 캐노피의 전 파장을 이용해 생육을 추정하는 것이 가능하다고 판단되었으며 이 모델들의 타당성 검증에서도 좋은 정확도와 정밀도를 보였다. 그러나 배추의 중요한 생육인자 중 생체중을 추정한 모델의 $R^2$는 89% 이상으로 정확도가 높았으나 RMSE 571.1g 이하로 낮은 정밀도를 보여 생체중을 정확히 추정하기 어려웠다. 따라서 다른 통계분석방법으로 전 파장과 생육정보를 분석하거나 특정 밴드를 선택하여 산출한 식생지수를 이용한 추정 모델의 개발을 통하여 오차를 개선할 필요가 있다고 사료된다. 추후 반복 실험하여 분석한 추정 모델과 비교 분석하여 다양한 환경 및 생물 조건에 범용성을 가진 모델을 개발할 필요가 있다.

• Near Infrared Analysis
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• 제2권1호
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• pp.59-66
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• 2001

Nowadays, medical diagnostics is efficiently supported by clinical chemistry and near infrared spectroscopy is becoming a new dimension, which has shown high potential to provide valuable information for diagnosis. The investigation was carried out to study the influence of mammary gland inflammation, called mastitis, on cow´s milk spectra and milk composition measured by near infrared spectroscopy (NIRS). Milk somatic cell counts (SCC) in milk were used as a measure of mammary gland inflammation. Naturally occurred variations with milk composition within lactation and in the process of milking were included in the experimental design of this study. Time series of unhomogenized, raw milk spectral data were collected from 3 cow along morning and evening milking, for 5 consecutive months, within their second lactation. In the time of the trial, the investigated cows had periods with mammary gland inflammation. Transmittance spectra of 258 milk samples were obtained by NIRSystem 6500 spectrophotometer in 1100-2400 nm region. Calibration equations for the examined milk components were developed by PLS regression using 3 different sets of samples: samples with low somatic cell count (SCC), samples with high SCC and combined data set. The NIR calibration and prediction of individual cow´s milk fat, protein, and lactose were highly influenced by the presence of mil samples from animals with mammary gland inflammation in the data set. The best accuracy of prediction (i.e. the lower SEP and the higher correlation coefficient) for fat, protein and lactose was obtained for equations, developed when using only “healthy” samples, with low SCC. The standard error of prediction increased and correlation coefficient decreased significantly when equations for low SCC milk were used to predict examined components in “mastitis” samples with high SCC, and vice versa. Combined data set that included samples from healthy and mastitis animals could be used to build up regression models for screening. Further use of separate model for healthy samples improved milk composition measurement. Regression vectors for NIR mild protein measurement obtained for “healthy” and “mastitic” group were compared and revealed differences in 1390-1450 nm, 1500-1740 nm and 1900-2200 nm regions and thus illustrated post-secretory breakdown of milk proteins by hydrolytic enzymes that occurred with mastitis. For the first time it has been found that monitoring the spectral differences in water bands at 1440 nm and 1912 nm could provide valuable information for inflammation diagnosis.

• Asian Pacific Journal of Cancer Prevention
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• 제15권16호
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• pp.6773-6779
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• 2014

Background: Nanotechnology opens new applications in many fields including medicine. Among all metallic nanoparticles, silver nanoparticles (silver NPS) have proved to be the most effective against a large variety of organisms including toxic cyanobacteria. Materials and Methods: Silver NPs were biosynthesized in vivo with different alga species namely, Spirulina piatensis, Chlorella vulgaris and Scenedesmus oh/iquus following two scenarios. First: by suspending a thoroughly washed algae biomass in 1 mM aqueous $AgN0_3$ solution. Second: by culturing them individually in culture media containing the same concentration of $AgN0_3$. Silver NPs were characterized using UV-Vis spectroscopy, transmission electron microscopy (TEM), energy dispersive analysis (EDX) and Fourier transform infra-red (FfIR) spectroscopy. The biosynthesized silver NPs were tested for cytotoxic activity against a cancer promoter cyanobacteruim Microcystis aeruginosa, considering effects on cell viability and chlorophyll content. Results: The surface plasmon band indicated the biosynthesis of silver NPs at ~400 nm. Transmission electron microscopy (TEM) revealed that the silver NPs had a mean average size below 100 nm. Energy-dispersive analysis X-ray (EDX) spectra confirmed the presence of silver element. FfIR spectral analyses suggested that proteins and or polysaccharides may be responsible for the biosynthesis of silver NPs and (-COO-) of carboxylate ions is responsible for stabilizing them. The toxic potentialities ofthe biosynthesized silver NPs against the cancer promoter cyanobacterium, Microcystis aeruginosa showed high reduction in viable cells count and the total chlorophyll content. Conclusions: The potential activity of the biosynthesized silver NPs from the studied algae species against Microcystis aernginosa cells is expected to be mainly mediated by the release of silver ions (Ag+) from the particle surface and bioactive compounds as indicated by FfIR analysis.