In this paper we employ the Petrov Galerkin method for the parabolic problems to get the finite element approximate solution of high accuracy by means of the interpolation postprocessing, extrapolation and defect cor...In this paper we employ the Petrov Galerkin method for the parabolic problems to get the finite element approximate solution of high accuracy by means of the interpolation postprocessing, extrapolation and defect correction techniques.展开更多
[Objective] This study was conducted to evaluate the feasibility of deter- mining crude protein in ramie using near-infrared （NIR） spectrometer. [Method] Par- tial least square regression （PLSR） was performed to e...[Objective] This study was conducted to evaluate the feasibility of deter- mining crude protein in ramie using near-infrared （NIR） spectrometer. [Method] Par- tial least square regression （PLSR） was performed to establish a calibration model based on 50 samples for predicting the crude protein content in ramie, and the model was validated with data in the validation set consisting of 10 samples. [Result] The correlation coefficient of the model was 0.98. There was a good correla- tion between the predicted values by the near-infrared prediction model and the measured values by chemical analysis, and the relative error was 3.54% on aver- age between the predicted and the measured values. [Conclusion] The results showed that it is feasible to determine crude protein content in ramie using NIR spectroscopy-based prediction model.展开更多
A new algorithm of nonuniformity correction for infrared focal plane array(IRFPA) is reported,which is a combined algorithm based on both the two-point correction and artificial neural networks correction. The combine...A new algorithm of nonuniformity correction for infrared focal plane array(IRFPA) is reported,which is a combined algorithm based on both the two-point correction and artificial neural networks correction. The combined algorithm is calibrated by two-point correction,and the calibrated correction coefficients are automatically modified by BP algorithm. So it is not only calibrated,but also real-time processed. In adaptive nonuniformity correction algorithm,the phenomena ghost artifact and target fade-out are avoided by edge extraction. In order to get intensified image,the modified median filters are adopted. The simulated data indicates the proposed scheme is an effective algorithm.展开更多
In addition to the conventional methods of the calibration model construction, such as PCR （principal components regression） and PLS （partial least-squares）, a MPM （mathematical programming method） is developed ...In addition to the conventional methods of the calibration model construction, such as PCR （principal components regression） and PLS （partial least-squares）, a MPM （mathematical programming method） is developed and proposed for practical use in NIR analyses of agricultural and food products. The proposed method involves the mathematical programming techniques to seek the regression coefficients for the calibration model calculation. It is based on the optimization theory used for finding the extremum of the objective function in the given domain of a vector space and employs the method of the complementarity problems solving. The MPM algorithm is described in detail. The MPM was tested on an InfraLUM FT-10 NIR analyzer of Lumex company with samples of dry milk （for fat）, corn （for protein） and rye flour （for moisture）. The obtained results show that the MPM can be used for constructing multivariate calibrations with the qualitative characteristics superior over those of the classical PCR and PLS methods of analysis.展开更多
A calibration board composed of 8×8 near-infrared surface-mounted diodes(NIR-SMDs)(940 nm)is designed.Meanwhile,a common binocular measurement system with the average error less than 0.1320 mm is used to obtain t...A calibration board composed of 8×8 near-infrared surface-mounted diodes(NIR-SMDs)(940 nm)is designed.Meanwhile,a common binocular measurement system with the average error less than 0.1320 mm is used to obtain the geometric information of this board.A calibration method with the designed pattern is performed to obtain the parameters of the near-infrared camera(NIRC).In the experiment,the average relative errors of focal length and principal point are 0.244%and 0.735%,respectively.The mean of image residuals is less than 0.01 pixel.The error of three-dimensional(3D)measurement is less than 0.3 mm.All those results indicate that the designed calibration board is suitable and accurate for calibrating NIRC.展开更多
Consensus methods have presented promising tools for improving the reliability of quantitative models in near-infrared(NIR) spectroscopic analysis.A strategy for improving the performance of consensus methods in multi...Consensus methods have presented promising tools for improving the reliability of quantitative models in near-infrared(NIR) spectroscopic analysis.A strategy for improving the performance of consensus methods in multivariate calibration of NIR spectra is proposed.In the approach,a subset of non-collinear variables is generated using successive projections algorithm(SPA) for each variable in the reduced spectra by uninformative variables elimination(UVE).Then sub-models are built using the variable subsets and the calibration subsets determined by Monte Carlo(MC) re-sampling,and the sub-model that produces minimal error in cross validation is selected as a member model.With repetition of the MC re-sampling,a series of member models are built and a consensus model is achieved by averaging all the member models.Since member models are built with the best variable subset and the randomly selected calibration subset,both the quality and the diversity of the member models are insured for the consensus model.Two NIR spectral datasets of tobacco lamina are used to investigate the proposed method.The superiority of the method in both accuracy and reliability is demonstrated.展开更多
文摘In this paper we employ the Petrov Galerkin method for the parabolic problems to get the finite element approximate solution of high accuracy by means of the interpolation postprocessing, extrapolation and defect correction techniques.
文摘[Objective] This study was conducted to evaluate the feasibility of deter- mining crude protein in ramie using near-infrared （NIR） spectrometer. [Method] Par- tial least square regression （PLSR） was performed to establish a calibration model based on 50 samples for predicting the crude protein content in ramie, and the model was validated with data in the validation set consisting of 10 samples. [Result] The correlation coefficient of the model was 0.98. There was a good correla- tion between the predicted values by the near-infrared prediction model and the measured values by chemical analysis, and the relative error was 3.54% on aver- age between the predicted and the measured values. [Conclusion] The results showed that it is feasible to determine crude protein content in ramie using NIR spectroscopy-based prediction model.
文摘A new algorithm of nonuniformity correction for infrared focal plane array(IRFPA) is reported,which is a combined algorithm based on both the two-point correction and artificial neural networks correction. The combined algorithm is calibrated by two-point correction,and the calibrated correction coefficients are automatically modified by BP algorithm. So it is not only calibrated,but also real-time processed. In adaptive nonuniformity correction algorithm,the phenomena ghost artifact and target fade-out are avoided by edge extraction. In order to get intensified image,the modified median filters are adopted. The simulated data indicates the proposed scheme is an effective algorithm.
文摘In addition to the conventional methods of the calibration model construction, such as PCR （principal components regression） and PLS （partial least-squares）, a MPM （mathematical programming method） is developed and proposed for practical use in NIR analyses of agricultural and food products. The proposed method involves the mathematical programming techniques to seek the regression coefficients for the calibration model calculation. It is based on the optimization theory used for finding the extremum of the objective function in the given domain of a vector space and employs the method of the complementarity problems solving. The MPM algorithm is described in detail. The MPM was tested on an InfraLUM FT-10 NIR analyzer of Lumex company with samples of dry milk （for fat）, corn （for protein） and rye flour （for moisture）. The obtained results show that the MPM can be used for constructing multivariate calibrations with the qualitative characteristics superior over those of the classical PCR and PLS methods of analysis.
基金supported by the National Natural Science Foundation of China(No.81101130)the Fundamental Research Funds for Central Universities under the South China University of Technology(No.2012ZZ0095)the Science and Technology Program of Guangdong Province(No.2012B031800026)
文摘A calibration board composed of 8×8 near-infrared surface-mounted diodes(NIR-SMDs)(940 nm)is designed.Meanwhile,a common binocular measurement system with the average error less than 0.1320 mm is used to obtain the geometric information of this board.A calibration method with the designed pattern is performed to obtain the parameters of the near-infrared camera(NIRC).In the experiment,the average relative errors of focal length and principal point are 0.244%and 0.735%,respectively.The mean of image residuals is less than 0.01 pixel.The error of three-dimensional(3D)measurement is less than 0.3 mm.All those results indicate that the designed calibration board is suitable and accurate for calibrating NIRC.
基金supported by the National Natural Science Foundation of China (20835002)
文摘Consensus methods have presented promising tools for improving the reliability of quantitative models in near-infrared(NIR) spectroscopic analysis.A strategy for improving the performance of consensus methods in multivariate calibration of NIR spectra is proposed.In the approach,a subset of non-collinear variables is generated using successive projections algorithm(SPA) for each variable in the reduced spectra by uninformative variables elimination(UVE).Then sub-models are built using the variable subsets and the calibration subsets determined by Monte Carlo(MC) re-sampling,and the sub-model that produces minimal error in cross validation is selected as a member model.With repetition of the MC re-sampling,a series of member models are built and a consensus model is achieved by averaging all the member models.Since member models are built with the best variable subset and the randomly selected calibration subset,both the quality and the diversity of the member models are insured for the consensus model.Two NIR spectral datasets of tobacco lamina are used to investigate the proposed method.The superiority of the method in both accuracy and reliability is demonstrated.
