• Journal of Animal Environmental Science
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• v.20 no.4
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• pp.183-188
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• 2014

Near-infrared reflectance spectroscopy (NIRS) was used to study the potential of adulteration of imported forage. Hay samples were prepared two set ; calibration set and validation one. The former were mixed 12 sets from 100% to 50% with Yangcho (Chinese leymus, leymus chinensis Trin.) and the latter were adulterated with 6 set of 8% to 38% in 5% interval. Mixed materials with Yangcho were rice straw, reed and alfalfa. Stand error of prediction (SEP) in calibration equation for alfalfa, reed and rice straw were 0.97, 0.97 and 0.99 also 0.54, 0.86 and 1.26%. Multiple correlation coefficient ($R^2$) for alfalfa, reed and rice straw were 0.99, 0.97 and 0.99. SEP in the same samples were 1.88, 2.15 and 1.49, respectively.

• Journal of Crop Science and Biotechnology
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• v.10 no.3
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• pp.185-192
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• 2007

Near-infrared spectroscopy(NIRS) was used to develop a rapid and efficient method to determine lignan glucosides in intact seeds of sesame(Sesamum indicum L.) germplasm accessions in Korea. A total of 93 samples(about 2 g of intact seeds) were scanned in the reflectance mode of a scanning monochromator, and the reference values for lignan glucosides contents were measured by high performance liquid chromatography. Calibration equations for sesaminol triglucoside, sesaminol($1{\rightarrow}2$) diglucoside, sesamolinol diglucoside, sesaminol($1{\rightarrow}6$) diglucoside, and total amount of lignan glucosides were developed using modified partial least square regression with internal cross validation(n=63), which exhibited lower SECV(standard errors of cross-validation), higher $R^2$(coefficient of determination in calibration), and higher 1-VR(ratio of unexplained variance divided by variance) values. Prediction of an external validation set(n=30) showed a significant correlation between reference values and NIRS estimated values based on the SEP(standard error of prediction), $r^2$(coefficient of determination in prediction), and the ratio of standard deviation(SD) of reference data to SEP, as factors used to evaluate the accuracy of equations. The models for each glucoside content had relatively higher values of SD/SEP(C) and $r^2$(more than 2.0 and 0.80, respectively), thereby characterizing those equations as having good quantitative information, while those of sesaminol($1{\rightarrow}2$) diglucoside showing a minor quantity had the lowest SD/SEP(C) and $r^2$ values(1.7 and 0.74, respectively), indicating a poor correlation between reference values and NIRS estimated values. The results indicated that NIRS could be used to rapidly determine lignan glucosides content in sesame seeds in the breeding programs for high quality sesame varieties.

• Journal of Crop Science and Biotechnology
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• v.10 no.1
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• pp.13-18
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• 2007

Near-infrared spectroscopy(NIRS) was used as a rapid and nondestructive method to determine the fatty acid composition in intact seed samples of rapeseed(Brassica napus L.). A total of 349 samples(about 2 g of intact seeds) were scanned in the reflectance mode of a scanning monochromator, and the reference values for fatty acid composition were measured by gas-liquid chromatography. Calibration equations for individual fatty acids were developed using the regression method of modified partial least-squares with internal cross validation(n=249). The equations had low SECV(standard errors of cross-validation), and high $R^2$(coefficient of determination in calibration) values(>0.8) except for palmitic and eicosenoic acid. Prediction of an external validation set(n=100) showed significant correlation between reference values and NIRS estimated values based on the SEP(standard error of prediction), $r^2$(coefficient of determination in prediction), and the ratio of standard deviation(SD) of reference data to SEP. The models developed in this study had relatively higher values(> 3.0 and 0.9, respectively) of SD/SEP(C) and $r^2$ for oleic, linoleic, and erucic acid, characterizing those equations as having good quantitative information. The results indicated that NIRS could be used to rapidly determine the fatty acid composition in rapeseed seeds in the breeding programs for high quality rapeseed oil.

• Journal of The Korean Astronomical Society
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• v.50 no.2
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• pp.21-27
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• 2017

The autoregressive method provides a univariate procedure to predict the future sunspot number (SSN) based on past record. The strength of this method lies in the possibility that from past data it yields the SSN in the future as a function of time. On the other hand, its major limitation comes from the intrinsic complexity of solar magnetic activity that may deviate from the linear stationary process assumption that is the basis of the autoregressive model. By analyzing the residual errors produced by the method, we have obtained the following conclusions: (1) the optimal duration of the past time for the forecast is found to be 8.5 years; (2) the standard error increases with prediction horizon and the errors are mostly systematic ones resulting from the incompleteness of the autoregressive model; (3) there is a tendency that the predicted value is underestimated in the activity rising phase, while it is overestimated in the declining phase; (5) the model prediction of a new Solar Cycle is fairly good when it is similar to the previous one, but is bad when the new cycle is much different from the previous one; (6) a reasonably good prediction of a new cycle can be made using the AR model 1.5 years after the start of the cycle. In addition, we predict the next cycle (Solar Cycle 25) will reach the peak in 2024 at the activity level similar to the current cycle.

• Journal of Power System Engineering
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• v.19 no.5
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• pp.45-51
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• 2015

Grade 91 steel is used for the major structural components of Generation-IV reactor systems such as a very high temperature reactor (VHTR) and sodium-cooled fast reactor (SFR). Since these structures are designed for up to 60 years at elevated temperatures, the prediction of long-term creep life is very important to determine an allowable design stress of elevated temperature structural component. In this study, a large body of creep rupture data was collected through world-wide literature surveys, and using these data, the long-term creep life was predicted in terms of three methods: Larson-Miller (L-M), Manson-Haferd (M-H) and Wilshire methods. The results for each method was compared using the standard deviation of error. The L-M method was overestimated in the longer time of a low stress. The Wilshire method was superior agreement in the long-term life prediction to the L-M and M-H methods.

• Structural Engineering and Mechanics
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• v.84 no.2
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• pp.143-154
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• 2022

Corrosion of steel reinforcement is considered as the main cause of concrete structures deterioration, especially those under humid environmental conditions. Hence, fiber reinforced polymer (FRP) bars are being increasingly used as a replacement for conventional steel owing to their non-corrodible characteristics. However, predicting the shear strength of beams reinforced with FRP bars still challenging due to the lack of robust shear theory. Thus, this paper aims to develop an explicit data driven based model to predict the shear strength of FRP reinforced beams using multi-objective evolutionary polynomial regression analysis (MOGA-EPR) as data driven models learn the behavior from the input data without the need to employee a theory that aid the derivation, and thus they have an enhanced accuracy. This study also evaluates the accuracy of predictive models of shear strength of FRP reinforced concrete beams employed by different design codes by calculating and comparing the values of the mean absolute error (MAE), root mean square error (RMSE), mean (𝜇), standard deviation of the mean (𝜎), coefficient of determination (R²), and percentage of prediction within error range of ±20% (a20-index). Experimental database has been developed and employed in the model learning, validation, and accuracy examination. The statistical analysis illustrated the robustness of the developed model with MAE, RMSE, 𝜇, 𝜎, R², and a20-index of 14.6, 20.8, 1.05, 0.27, 0.85, and 0.61, respectively for training data and 10.4, 14.1, 0.98, 0.25, 0.94, and 0.60, respectively for validation data. Furthermore, the developed model achieved much better predictions than the standard predictive models as it scored lower MAE, RMSE, and 𝜎, and higher R² and a20-index. The new model can be used in future with confidence in optimized designs as its accuracy is higher than standard predictive models.

• Food Science and Biotechnology
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• v.16 no.3
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• pp.477-481
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• 2007

Fourier transform near-infrared (FT-NIR) spectroscopy and partial least squares (PLS) regression were used to predict the amylose content of polished rice. Spectral reflectance data in a wavelength range of 1,000 to 2,500 nm were obtained with a commercial spectrophotometer for 60 different varieties of Korean rice. For a comparison of this spectroscopic method to a standard chemical analysis, the amylose contents of the tested rice samples were determined by the iodine-blue colorimetric method. The highest correlation for the rice amylose ($R^2=0.94$, standard error of prediction=0.20% amylose content) was obtained when using the FT-NIR spectrum data pre-treated with normalization, the first derivative, smoothing, and scattering correction.

• Journal of the Korean Society of Tobacco Science
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• v.21 no.1
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• pp.95-101
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• 1999

This study was carried out to analyze chemical components in burley tobacco using near infrared spectroscopy(NIRS). Samples were collected in '96 and '97 crop year. Calibration equations were developed by modified partial least square. The standard error performance(SEP) of '96 crop year samples between NIRS and standard laboratory analysis were 0.25% for nicotine, 0.18% for total nitrogen, 0.59% for crude ash, 0.32% for ether extracts, and 0.14% for chlorine, respectively. The analytical results of '97 crop year samples were similar to those of '96 crop year samples. The analytical result of '97 crop year samples analyzed by '96 calibration equation was more inaccurate than that of '96 crop year samples. The SEP of '96 or '97 crop year samples applying calibration equation derived from '96 plus '97 crop year samples was similar to that of '96 or '97 crop year samples analyzed by '96 or '97 calibration equation, respectively. The SEP of '97 crop year samples analyzed by calibration equation derived from '96 plus '97 crop year samples was more accurate than that of '97 crop year samples analyzed by '96 calibration equation. To improve the analytical inaccuracy caused by the difference of crop year between calibration and prediction samples, we need to include the prediction sample spectra which were different from calibration sample spectra in recalibration sample spectra, and then develop recalibration equation. The NIRS can apply to analyze burley leaf tobacco, leaf process or tobacco manufacturing process which were required the rapid analytical result.

• Korean Journal of Optics and Photonics
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• v.19 no.6
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• pp.416-421
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• 2008

A scheme for predicting the concentration of a glucose solution based on its relative optical absorbance at multiple probe wavelengths was proposed and verified. The relative absorbance at each of the probe wavelength was obtained with respect to the absorbance at a reference wavelength. The single reference wavelength (1310 nm) and a group of four different probe wavelengths (1064, 1550, 1685, 1798 nm) were selected to exhibit the glucose absorbance with opposite signs, thereby enhancing the accuracy of the prediction. The final glucose concentration was estimated by taking the average of the predicted values provided by the four probe wavelengths. The absorbance of the glucose solution for the path length of 5 mm was $-1.42{\times}10^{-6}\;AU$/(mg/dL) at the reference wavelength of 1310 nm and peaked at $+8.12{\times}10^{-6}\;AU$/(mg/dL) at 1685 nm. The concentration of the glucose solution was decently predicted by means of the proposed scheme with the standard error of prediction of ${\sim}28\;mg/dL$. In addition, the influence of the ambient temperature and the fat thickness upon the prediction of the glucose concentration was examined. The absorption change with the temperature was $-9.1{\times}10^{-5}\;AU/^{\circ}C$ in the temperature range of $26{\sim}40^{\circ}C$ at the reference wavelength, and $-2.08{\times}10^{-2}\;AU/^{\circ}C$ at 1550 nm. And the absorption change with respect to the fat thickness was +1.093 AU/mm at the probe wavelength of 1685 nm.

• Analytical Science and Technology
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• v.11 no.1
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• pp.47-53
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• 1998

This study is to improve the diagnosis of diabetes mellitus and the self-monitoring of blood glucose in people with diabetes by providing a non-invasive method of monitoring blood glucose. A near-infrared (NIR) spectrophotometer was used to measure absorption spectra of 80 glucose samples ranges from 1 mg/dL to 200 mg/dL, and shows the standard error of prediction 1.8 mg/dL. Also, to investigate the effect of interference in blood, NaCl and sand were added in glucose and found the standard error of prediction of 2.8 mg/dL and 3.8 mg/dL, respectively. A new and more accurate calibration system for the spectrophotometer was developed from systematic study of light scattering, which cause nonlinear spectrophotometer response.