• 대한화학회지
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• 제47권1호
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• pp.19-25
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• 2003

흡수 분광법에 의해 얻은 스펙트럼을 주성분분석(principal analysis, PCA) 으로 자료를 요약하여 주성분 회귀분서(principal component regression, PCR)과 부분 최소자승법(partial least squares, PLS)으로 음이온과 비이온 계면활성제(anionic and nonionic surfactant)를 동시에 정량하는 방법에 대하여 연구하였다. 두 가지 계면활성제가 서로 다른 농도로 혼합되어 있는 26개의 시료용액을 400~700 nm 범위에서 스펙트럼을 얻었고, 이를 이용하여 PCR과 PLS회귀모델을 얻었다. 두 가지 계면활성제가 서로 다른 농도로 포함된 5개의 외부검정용 시료들의 스펙트럼들을 이용해서 회귀모델의 적합성을 검정하기 위하여 외부검정용 시료의 농도를 계산하였다. 계산된 농도를 이용하여 relative standard error of prediction(RSEP$_{\alpha}$)를 구하여 회귀모델의 적합성을 검정하였다.

• 한국자동차공학회논문집
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• 제21권6호
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• pp.175-182
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• 2013

Lately, customers think highly of the emotional satisfaction and as a result, issues on odor are matters of concern. The cases are odor of interior material and air-conditioner of vehicles. In particualar, with respect to the odor of air-conditioner, customers strongly claimed defects with provocative comments : "It smells like something rotten," "It smells like a foot odor," "It stinks like a rag." Generally, it is known that mold of evaporator core in the air-conditioning system decays and this produce VOCs which causes the odor to occur. In this study, partial least squares regression model is applied to predict the strength of the odor and select of important VOCs which affect car air conditioning smell. The PLS method is basically a particular multilinear regression algorithm which can handle correlated inputs and limited data. The number of latent variable is determined by the point which is stabilized mean absolute deviations of VOCs data. Also multiple linear regression is carried out to confirm the validity of PLS method.

• 분석과학
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• 제16권4호
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• pp.277-282
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• 2003

감귤의 생육단계별 토양 수분의 양은 감귤의 비대와 당도에 영향을 미치며, 토양 건조 처리를 통해 수분스트레스를 부여하면 과실의 당도를 높일 수 있다. 감귤잎 수분 함유율의 측정은 감귤 성장 시기에 따른 관수 시점, 관수량 조절의 지표가 될 수 있다. 본 연구는 근적외분광분석법(NIRS)을 이용하여 비파괴적으로 감귤잎의 수분을 측정하기 위하여 수행되었다. 온주밀감 (Citrus unshiu Marc.)의 잎 ('Okitsu' Satusuma mandarin leaves)은 건조감량시험법에 따라 건조시켜 수분 함유율 20.80-69.98% 범위로 하여 사용하였다. 감귤잎의 흡수 스펙트럼은 광섬유 반사 프로브를 이용하여 측정하였고, 1450 nm에서 수분 함유율 변화에 따른 OH band의 변화를 관찰할 수 있었다. 감귤잎 수분 측정을 위한 모델은 1100-1700 nm 파장 범위의 스펙트럼을 사용하여, 부분최소제곱법 (PLSR, Partial least squres regression)을 실시하여 개발되었다. 그 결과 SEP (Standard errors of prediction)는 0.97%였다. 개발된 모델을 검증하기 위하여 다른 감귤잎에 적용시킨 결과, 건조감량 측정 결과에 대하여 SEP 0.81%로 좋은 상관성을 보여주고 있다. 본 연구를 통해서 신속하고 비파괴적인 감귤잎의 수분 함유율 측정이 근적외분광분석법을 이용하여 성공적으로 수행되었다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 Proceedings of the Korea Automatic Control Conference, 11th (KACC); Pohang, Korea; 24-26 Oct. 1996
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• pp.295-298
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• 1996

In distillation column control, secondary measurements such as temperatures and flows are widely used in order to infer product composition. This paper addresses the design of static estimators using the secondary measurements for estimating the product compositions of the multicomponent distillation columns. Based on the unified framework for the estimator problems, the relationships among several typical static estimators are discussed including the effect of the measured inputs. Design guidelines for the composition estimator using PLS regression are also presented. The estimator based on the guidelines is robust to sensor noise and has a good predictive power.

• 한국수소및신에너지학회논문집
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• 제25권5호
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• pp.491-499
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• 2014

It is important to accurately measure and control the relative humidity of humidified gas entering a PEM (polymer electrolyte membrane) fuel cell stack because the level of humidification strongly affects the performance and durability of the stack. Humidity measurement devices can be used to directly measure the relative humidity, but they cost much to be equipped and occupy spaces in a fuel cell system. We present soft sensors for predicting the relative humidity without actual humidity measuring devices. By combining FIR (finite impulse response) model with PLS (partial least square) and SVM (support vector machine) regression models, DPLS (dynamic PLS) and DSVM (dynamic SVM) soft sensors were developed to correctly estimate the relative humidity of humidified gases exiting a planar-type membrane humidifier. The DSVM soft sensor showed a better prediction performance than the DPLS one because it is able to capture nonlinear correlations between the relative humidity and the input data of the soft sensors. Without actual humidity sensors, the soft sensors presented in this work can be used to monitor and control the humidity in operation of PEM fuel cell systems.

• Journal of the Korean Wood Science and Technology
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• 제44권6호
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• pp.852-863
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• 2016

Wood-plastic composite (WPC) is a promising and sustainable material, and refers to a combination of wood and plastic along with some binding (adhesive) materials. In comparison to pure wood material, WPCs are in general have advantages of being cost effective, high durability, moisture resistance, and microbial resistance. The properties of WPCs come directly from the concentration of different components in composite; such as wood flour concentration directly affect mechanical and physical properties of WPCs. In this study, wood powder concentration in WPC was determined by Fourier transform near-infrared (FT-NIR) and Fourier transform infrared (FT-IR) spectroscopy. The reflectance spectra from WPC in both powdered and tableted form with five different concentrations of wood powder were collected and preprocessed to remove noise caused by several factors. To correlate the collected spectra with wood powder concentration, multivariate calibration method of partial least squares (PLS) was applied. During validation with an independent set of samples, good correlations with reference values were demonstrated for both FT-NIR and FT-IR data sets. In addition, high coefficient of determination (${R^2}_p$) and lower standard error of prediction (SEP) was yielded for tableted WPC than powdered WPC. The combination of FT-NIR and FT-IR spectral region was also studied. The results presented here showed that the use of both zones improved the determination accuracy for powdered WPC; however, no improvement in prediction result was achieved for tableted WPCs. The results obtained suggest that these spectroscopic techniques are a useful tool for fast and nondestructive determination of wood concentration in WPCs and have potential to replace conventional methods.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1511-1511
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• 2001

Energy content, expressed as calories per gram, is an important part of the evaluation and marketing of foods in developed countries. Currently accepted methods of measurement of energy by U.S. food labeling legislation include measurement of gross calories by bomb calorimetry with an adjustment for undigested protein and by calculation using specific factors for the energy values of protein, carbohydrate less the amount of insoluble dietary fiber, and total fat. The ability of NIRS to predict the energy value of diverse, processed and unprocessed cereal food products was investigated. NIR spectra of cereal products were obtained with an NIR Systems monochromator and the wavelength range used for analysis was 1104-2494 nm. Gross energy of the foods was measured by oxygen bomb calorimetry (Parr Manual No. 120) and expressed as calories per gram (CPGI, range 4.05-5.49 cal/g). Energy value was adjusted for undigested protein (CPG2, range 3.99-5.38 cal/g) and undigested protein and insoluble dietary fiber (CPG3, range 2.42-5.35 cal/g). Using a multivariate analysis software package (ISI International, Inc.) partial least squares models were developed for the prediction of energy content. The standard error of cross validation and multiple coefficient of determination for CPGI using modified partial least squares regression (n=127) was 0.060 cal/g and 0.95, respectively, and the standard error of performance, coefficient of determination, bias and slope using an independent validation set (n=59) were 0.057 cal/g, 0.98, -0.027 cal/g and 1.05 respectively. The PLS loading for factor 1 (Pearson correlation coefficient 0.92) had significant absorption peaks correlated to C-H stretch groups in lipid at 1722/1764 nm and 2304/2346 nm and O-H groups in carbohydrate at 1434 and 2076 nm. Thus the model appeared to be predominantly influenced by lipid and carbohydrate. Models for CPG2 and CPG3 showed similar trends with standard errors of performance, using the independent validation set, of 0.058 and 0.088 cal/g, respectively, and coefficients of determination of 0.96. Thus NIRS provides a rapid and efficient method of predicting energy content of diverse cereal foods.

• Asian-Australasian Journal of Animal Sciences
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• 제17권12호
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• pp.1736-1740
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• 2004

Since the application of relatively high levels of heavy metals in the compost poses a potential hazard to plants and animals, the content of heavy metals in the compost with animal manure is important to know if it is as a fertilizer. Measurement of heavy metals content in the compost by chemical methods usually requires numerous reagents, skilled labor and expensive analytical equipment. The objective of this study, therefore, was to explore the application of near-infrared reflectance spectroscopy (NIRS), a nondestructive, cost-effective and rapid method, for the prediction of heavy metals contents in compost. One hundred and seventy two diverse compost samples were collected from forty-seven compost facilities located along the Han river in Korea, and were analyzed for Cr, As, Cd, Cu, Zn and Pb levels using inductively coupled plasma spectrometry. The samples were scanned using a Foss NIRSystem Model 6500 scanning monochromator from 400 to 2,500 nm at 2 nm intervals. The modified partial least squares (MPLS), the partial least squares (PLS) and the principal component regression (PCR) analysis were applied to develop the most reliable calibration model, between the NIR spectral data and the sample sets for calibration. The best fit calibration model for measurement of heavy metals content in compost, MPLS, was used to validate calibration equations with a similar sample set (n=30). Coefficient of simple correlation (r) and standard error of prediction (SEP) were Cr (0.82, 3.13 ppm), As (0.71, 3.74 ppm), Cd (0.76, 0.26 ppm), Cu (0.88, 26.47 ppm), Zn (0.84, 52.84 ppm) and Pb (0.60, 2.85 ppm), respectively. This study showed that NIRS is a feasible analytical method for prediction of heavy metals contents in compost.

• 한국콘텐츠학회논문지
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• 제16권3호
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• pp.553-562
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• 2016

본 연구는 투자자가 부동산 투자의사결정에 있어 고려해야하는 투자선호특성을 규명하고 투자자 유형에 따른 선호특성의 차이를 비교 분석하였다. 투자만족도에 영향을 미치는 요인을 분석하기 위해 선행연구 고찰을 통하여 투자선호특성을 종합하고 PLS(Partial Least Squares)회귀분석을 활용하여 그 영향을 실증하였다. 또한 투자자 유형별 투자선호특성을 비교하기 위해 분석대상을 기관투자자와 일반투자자로 구분하여 설문을 진행하였다. 분석결과 기관투자자는 인플레이션 헤지, 조지자본회수, 재무적 안전성, 레버리지 위험 등의 투자선호특성을 중시하는 것으로 나타났으며 일반투자자의 경우 임대수익, 시설 및 설비, 상권 및 인구, 이용 편의성, 레버리지 위험, 조기자본회수 등의 투자선호특성이 중요한 것으로 도출되었다. 또한 공통적인 투자선호특성으로 레버리지 위험, 조기자본회수, 시설접근성이 도출되었다. 이러한 결과를 바탕으로 시사점을 도출하면 다음과 같다. 첫째, 투자자들은 부동산 투자에 있어 투자 위험을 회피하거나 줄일 수 있는 요인을 중시 한다는 점이다. 둘째, 부동산 경기 침체 및 저금리 현상으로 나타나는 부동산 관련 규제 및 금융규제완화를 중요시하는 것으로 나타났다. 셋째, 부동산 투자의사결정에 있어 투자자 유형에 따른 차이를 고려해야 한다는 것이다.

• 한국토양비료학회지
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• 제47권5호
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• pp.319-323
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• 2014

This study investigates the prediction of soil chemical properties (organic matter (OM), pH, Ca, Mg, K, Na, total acidity, cation exchange capacity (CEC)) on 688 Korean soil samples using the visible-near infrared reflectance (VIS-NIR) spectroscopy. Reflectance from the visible to near-infrared spectrum (350 to 2500 nm) was acquired using the ASD Field Spec Pro. A total of 688 soil samples from 168 soil profiles were collected from 2009 to 2011. The spectra were resampled to 10 nm spacing and converted to the 1st derivative of absorbance (log (1/R)), which was used for predicting soil chemical properties. Principal components analysis (PCA), partial least squares regression (PLSR) and regression rules model (Cubist) were applied to predict soil chemical properties. The regression rules model (Cubist) showed the best results among these, with lower error on the calibration data. For quantitatively determining OM, total acidity, CEC, a VIS-NIR spectroscopy could be used as a routine method if the estimation quality is more improved.