• Journal of Biosystems Engineering
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• 제36권2호
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• pp.130-139
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• 2011

Three modes of VIS/NIR spectroscopic measurement (interactance and two modes of transmission) were compared for their ability to estimate soluble solids content (SSC) of 'Shingo' pear non-destructively. The two transmission modes are named as full- and semi-transmission, where full-transmission stands for passing of light through abdomen of pear and semi-transmission is for transit of light mainly through flesh of pear. For comparison of the modes, prediction models developed from the collected spectroscopic data by the three modes were developed and tested for comparison of their performance. Partial least square regression (PSLR) was used to develop the models and various pre-processing methods were applied to develop models of high accuracy. The experiment was repeated three times with pears produced in different regions. The experiments resulted that selection of pre-processing is very important to attain accurate models, and multiplicative scatter correction (MSC) was selected as a pre-processor of high accuracy for the three modes of spectroscopic measurement in every experiment. Except for MSC, different group of pre-processing methods were selected for the three modes of measurement in every experiment without any tendency to the tested modes of measurement and pears of different produced region. Root-mean-square error of prediction (RMSEP) of prediction models of the three modes of measurement using prepreocessor of MSC were compared for their ability to estimate SSC. The models resulted in ranges of $0.37{\sim}0.57^{\circ}Brix$, $0.65{\sim}0.72^{\circ}Brix$, $0.39{\sim}0.51^{\circ}Brix$ for interactance, full- and semi-transmission, respectively. As shown, modes of semi-transmission and interactance resulted about the same level of prediction accuracy and were noted as modes of high performance to predict SSC.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1530-1530
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• 2001

The objectives of this study were to develop models to predict quality parameters of Korean bee-honeys by visible and NIR spectroscopic technique. Two kinds of bee-honey fronl acacia and polyflower sources were tested in this study. The honeys were harvested in the spring of 2000 and stored in the storage facility at 20$^{\circ}C$ during experiments. Total of 394 samples of honey were analyzed. Reflectance spectra, moisture contents, ash, invert sugar, sucrose, F/G (fructose/glucose) ratio, HMF (hydroxymethyl furfural), and C12/C13 ratio of honeys were measured. The average values for the tested honeys were 19.9% of moisture contents, 0.12% of ash, 68.4% of invert sugar, 5.7% of sucrose, 1.27 of F/G(fructose/glucose) ratio, 14.4 mg/kg of HMF, and -19.1 of C12/C13 ratio. A spectrophotometer, equipped with a single-beam scanning monochromator (NIR Systems, Model 6500, USA) and a horizontal setup module, was used to collect reflectance data from honey. The reflectance spectra were measured in wavelength ranges of 400∼2,498 nm. with 2 nm of interval. Thirty-two repetitive scans were averaged, transformed to log(1/Reflectance), and then were stored in a microcomputer file, forming one spectrum per measurement. A sample cell and reflectance plate were made to hold honey samples constantly. Spectra of honey samples were divided into a calibration set and a validation set. The calibration set was used during model development, and the validation set was used to predict quality parameters from unknown spectra. The PLS(Partial Least Square) models were developed to predict the quality parameters of honeys. The first and the second derivatives of raw spectra were also used to develop the models with proper smoothing gap. The MSC (multiplicative scatter correction) and the SNV & Dtr.(standard normal variate and detranding) preprocessing were applied to all spectra to minimize sample-to-sample light scatter differences. The PLS models showed good relationships between predicted and measured quality parameters of honeys in the wavelength range of 1100∼2200 nm. However, the PLS analysis was not good enough to predict HMF of honeys.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1131-1131
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• 2001

To develop a nondestructive quality evaluation technique of fruits, a K-mean algorism is applied to near infrared (NIR) spectroscopy of apples. The K-mean algorism is one of neural network partition methods and the goal is to partition the set of objects O into K disjoint clusters, where K is assumed to be known a priori. The algorism introduced by Macqueen draws an initial partition of the objects at random. It then computes the cluster centroids, assigns objects to the closest of them and iterates until a local minimum is obtained. The advantage of using neural network is that the spectra at the wavelengths having absorptions against chemical bonds including C-H and O-H types can be selected directly as input data. In conventional multiple regression approaches, the first wavelength is selected manually around the absorbance wavelengths as showing a high correlation coefficient between the NIR $2^{nd}$ derivative spectrum and Brix value with a single regression. After that, the second and following wavelengths are selected statistically as the calibration equation shows a high correlation. Therefore, the second and following wavelengths are selected not in a NIR spectroscopic way but in a statistical way. In this research, the spectra at the six wavelengths including 900, 904, 914, 990, 1000 and 1016nm are selected as input data for K-mean analysis. 904nm is selected because the wavelength shows the highest correlation coefficients and is regarded as the absorbance wavelength. The others are selected because they show relatively high correlation coefficients and are revealed as the absorbance wavelengths against the chemical structures by B. G. Osborne. The experiment was performed with two phases. In first phase, a reflectance was acquired using fiber optics. The reflectance was calculated by comparing near infrared energy reflected from a Teflon sphere as a standard reference, and the $2^{nd}$ derivative spectra were used for K-mean analysis. Samples are intact 67 apples which are called Fuji and cultivated in Aomori prefecture in Japan. In second phase, the Brix values were measured with a commercially available refractometer in order to estimate the result of K-mean approach. The result shows a partition of the spectral data sets of 67 samples into eight clusters, and the apples are classified into samples having high Brix value and low Brix value. Consequently, the K-mean analysis realized the classification of apples on the basis of the Brix values.

• 한국산학기술학회논문지
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• 제22권1호
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• pp.208-213
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• 2021

본 논문에서는 농산물 산지 유통 센터에서 설치되어 사용하고 있는 비파괴 과일 선별 시스템을 이용하여 정상 사과와 내부에 결함이 있는 사과를 판별하기 위한 최적 파장과 해당 스펙트럼의 특성을 구명하고자 하였다. 총 54개 사과에 대해 470 - 1150 nm의 파장 범위에서 정상 사과와 갈변 사과의 투과 스펙트럼을 획득하였다. 주성분 분석(PCA)을 활용하여 정상 사과와 내부 갈변 사과의 군집을 확인하였으며, 판별 모델의 개발과 평가를 위해 부분최소제곱회귀(PLSR) 분석을 수행하였다. PCA 분석에서는 정상 사과와 내부 갈변 사과 군집의 확연한 구분이 보여 높은 판별율의 결과를 보여주었다. PLSR 분석 결과, 전처리를 하지 않은 예측 모델의 상관계수(R)는 0.902, RMSE 값은 0.157이었으며, 전처리를 적용했을 때 예측 모델의 상관계수는 0.906, RMSE 값은 0.154이었다. 따라서, 이 PLSR 모델은 이 시스템을 활용해 내부 갈변이 있는 사과도 우수하게 판별할 수 있음을 알 수 있었다. 이와 같은 방식을 이용할 경우, 외부 결함과 더불어 내부 결함에 대한 농산물 선별과 평가에 적용될 수 있을 것으로 사료된다.

• 한국축산시설환경학회지
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• 제13권2호
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• pp.113-120
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• 2007

본 시험은 근적외선분광법을 이용한 돈분뇨 액비의 질소, 인산, 칼리, 수분 및 유기물의 분석 가능성을 구명하고, 이를 활용한 분석기의 개발을 목적으로 수행하였으며, 그 결과는 다음과 같다. 1. 돈분뇨 액비시료는 $400{\sim}2,500nm$ 대역의 근적외선을 시료에 투과하여 측정하였으며, 동일시료에 대한 습식분석 결과, N, $P_2O_5,\;K_2O$, 수분 및 유기물 함량은 각각 1,555mg/l, 302mg/l, 240mg/l, 98.8%, 0.53%로 조사되었다. 2. 근적외선 분광광도법을 이용한 분석에서 N, $P_2O_5,\;K_2O$, 수분 및 유기물에 대한 RSQ ($r^2$, R, Coefficient of determination)는 각각 0.9190, 0.9749, 0.5046, 0.9883 및 0.9777이었고 SEC(Standard Error of Calibration)는 2.1649, 0.5019, 1.9252, 0.1180 및 0.0789였다. 3. 액비에 대한 이화학적 습식분석과 NIR 흡수스펙트럼 측정결과를 비교 분석하여 돈 분뇨 액비에 포함된 질소, 인산, 칼리, 수분 및 유기물 함량을 실시간으로 분석하고 액비 성분량을 자동 계산할 수 있는 알고리즘을 도입한 액비분석 프로그램을 작성하였다. 4. 액비 성분분석 시작기는 근적외선(NIR : Near InfraRed)을 받아들여 실시간으로 액비성분의 흡수율을 측정하는 광검출장치(NIR Spectrometer), 근적외선 Light Source로부터 나오는 빛을 반사시키는 반사경, 액비성분 분석용 시료를 넣어 측정하는 Cell Mount, $400{\sim}2,500nm$ 대역의 가시광선-근적외선을 방출하는 Tungsten halogen lamp, NIR Spectrometer와 Tungsten halogen lamp로 전압을 입력시켜 주는 Power Supply Module 및 전체를 Black Anodizing한 외형으로 구성되었다. 5. 실험결과, 칼리를 제외한 액비내 모든 성분이 광을 흡수하는 강도는 성분의 농도에 비례하였으며 원시 스펙트럼의 중첩 제거 및 빛의 산란보정을 통해 액비의 질소, 인산성분, 수분 및 유기물 함량을 측정하는데 효과적으로 이용할 수 있을 것으로 사료되며, 분광분석법을 이용한 액비성분 분석기 개발이 완료되면 현장에서 신속하고 정확한 분석이 가능할 것으로 판단된다.

• 대한원격탐사학회지
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• 제28권3호
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• pp.297-305
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• 2012

This study was performed to estimate forest canopy density (FCD) using airborne hyperspectral data acquired in the Independence Hall of Korea in central Korea. The airborne hyperspectral data were obtained with 36 narrow spectrum ranges of visible (Red, Green, and Blue) and near infrared spectrum (NIR) scope. The FCD mapping model developed by the International Tropical Timber Organization (ITTO) uses vegetation index (VI), bare soil index (BI), shadow index (SI), and temperature index (TI) for estimating FCD. Vegetation density (VD) was calculated through the integration of VI and BI, and scaled shadow index (SSI) was extracted from SI after the detection of black soil by TI. Finally, the FCD was estimated with VD and SSI. For the estimation of FCD in this study, VI and SI were extracted from hyperspectral data. But BI and TI were not available from hyperspectral data. Hyperspectral data makes the numerous combination of each band for calculating VI and SI. Therefore, the principal component analysis (PCA) was performed to find which band combinations are explanatory. This study showed that forest canopy density can be efficiently estimated with the help of airborne hyperspectral data. Our result showed that most forest area had 60 ~ 80% canopy density. On the other hand, there was little area of 10 ~ 20% canopy density forest.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.3112-3112
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• 2001

Near-Infrared Spectroscopy (NIRS) was investigated aiming at the identification of falsified drugs. The identification is based on comparison of the NIR spectrum of a sample with a typical spectra of an authentic drug using multivariate modelling and classification algorithms (PCA/SIMCA). Two spectrophotometers (Brimrose - Luminar 2000 and 2030), based on acoustic-optical filter (AOTF) technology, sharing the same controlling computer, software (Brimrose - Snap 2.03) and the data acquisition electronics, were employed. The Luminar 2000 scans the range 850 1800 nm and was employed for transmitance/absorbance measurements of liquids with a transflectance optical bundle probe with total optical path of 5 mm and a circular area of 0.5 $\textrm{cm}^2$. Model 2030 scans the rage 1100 2400 nm and was employed for reflectance measurement of solids drugs. 300 spectra, acquired in about 20 s, were averaged for each sample. Chemometric treatment of the spectral data, modelling and classification were performed by using the Unscrambler 7.5 software (CAMO Norway). This package provides the Principal Component Analysis (PCA) and SIMCA algorithms, used for modelling and classification, respectively. Initially, NIRS was evaluated for spectrum acquisition of various drugs, selected in order to accomplish the diversity of physico-chemical characteristics found among commercial products. Parameters which could affect the spectra of a given drug (especially if presented as solid tablets) were investigated and the results showed that the first derivative can minimize spectral changes associated with tablet geometry, physical differences in their faces and position in relation to the probe beam. The effect of ambient humidity and temperature were also investigated. The first factor needs to be controlled for model construction because the ambient humidity can cause spectral alterations that should cause the wrong classification of a real drug if the factor is not considered by the model.

• Transactions on Electrical and Electronic Materials
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• 제17권3호
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• pp.146-149
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• 2016

The CrN/TiN/Al thin films for solar selective absorber were prepared by dc reactive magnetron sputtering with multi targets. The binary nitride CrN layer deposited with change in N₂ gas flow rates. The gas mixture of Ar and N2 was an important parameter during sputtering deposition because the metal volume fraction (MVF) was controlled by the N2 gas flow rate. In this study, the crystallinity and surface properties of the CrN/TiN/Al thin films were estimated by X-ray diffraction (XRD), atomic force microscopy (AFM) and field emission scanning electron microscopy (FESEM). The composition and depth profile of thin films were investigated using Auger electron spectroscopy (AES). The absorptance and reflectance with wavelength spectrum were recorded by UV-Vis-NIR spectrophotometry at a range of 300~1,100 nm.

• 한국진공학회:학술대회논문집
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• 한국진공학회 2012년도 제43회 하계 정기 학술대회 초록집
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• pp.247-247
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• 2012

Plasmon subwavelength nanostructures enable the structurally modulated color due to the resonance conditions for the specific wavelength range of light with the nanoscale hole arrays on a metal layer. While the unique properties offered from a single layer of metal may open up the potential applications of integrated devices to displays and sensors, fabrication requirements in nanoscale, typically on the order of or smaller than the wavelength of light in a corresponding medium can limit the cost-effective implementation of the plasmonic nanostructures. Simpler nanoscale replication technologies based on the soft lithography or roll-to-roll nanoimprinting can introduce economically feasible manufacturing process for these devices. Such replication requires an optimal design of a master template to produce a stamp that can be applied for a roll-to-roll nanoimprinting. In this paper, a master mold with subwavelength nanostructures is fabricated and optimized using focused ion beam for the applications to nanoimprinting process. Au thin film layer is deposited by sputtering on a glass that serves as a dielectric substrate. Focused ion beam milling (FIB, JEOL JIB-4601F) is used to fabricate surface plasmon subwavelength nanostructures made of periodic hole arrays. The light spectrum of the fabricated nanostructures is characterized by using UV-Vis-NIR spectrophotometer (Agilent, Cary 5000) and the surface morphology is measured by using atomic force microscope (AFM, Park System XE-100) and scanning electron microscope (SEM, JEOL JSM-7100F). Relationship between the parameters of the hole arrays and the corresponding spectral characteristics and their potential applications are also discussed.

• Near Infrared Analysis
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• 제1권1호
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• pp.31-35
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• 2000

Near-infrared reflectance spectroscopy(NIRS) was used to determine the humic acids in soil samples from the fields of different crops and land-use over Youngnam and Honam regions in Korea. An InfraAlyzer 500 scanning spectrophotometer was obtained near infrared relectance spectra of soil at 2-nm intervals from 1100 to 2500nm. Multiple linear regression(MLR) or partial least square regression (PLSR) was used to evaluate a NIRS method for the rapid and nondestructive determination of humic acid, fulvic acid and its total contents in soils. The raw spectral data(log 1/R) can be used for estimating humic acid, fulvic acid and its total contents in soil by MLR procedure between the content of a given constituent and the spectral response of several bands. In which the predicted results for fulvic acid is the best in the constituents. The new spectral data are converted from the raw spectra by PLSR method such as the first derivative of each spectrum can also be used to predict humic acid and fulvic acid of the soil samples. A low SEC, SEP and a high coefficient of correlation in the calibration and validation stages enable selection of the best manipulation. But a simple calibration and prediction method for determining humic acid and fulvic acid should be selected under similar accuracy and precision of prediction. NIRS technique may be an effective method for rapid and nondestructive determination for humic acid, fulvic acid and its total contents in soils.