- 标题
- 摘要
- 关键词
- 实验方案
- 产品
-
Detection of Knot Defects on Coniferous Wood Surface Using Near Infrared Spectroscopy and Chemometrics
摘要： Lumber pieces usually contain defects such as knots, which strongly affect the strength and stiffness. To develop a model for rapid, accurate grading of lumbers based on knots, Douglas fir, spruce-pine-fir (SPF), Chinese hemlock, and Dragon spruce were used. The experiments explored the effects of modelling methods and spectral preprocess methods for knot detection, and investigated the feasibility of using a model built within one species to discriminate the samples from other species, using a novel variable selection method-random frog to select effective wavelengths. The results showed that least squares-support vector machines coupled with first derivative preprocessed spectra achieved best performance for both single and mixed models. Models built within Dragon spruce could be used to classify knot samples from SPF and Chinese hemlock but not Douglas fir, and vice versa. Eight effective wavelengths (1314 nm, 1358 nm, 1409 nm, 1340 nm, 1260 nm, 1586 nm, 1288 nm, and 1402 nm) were selected by RF to build effective wavelengths based models. The sensitivity, specificity, and accuracy in the validation set were 98.49%, 93.42%, and 96.30%, respectively. Good results could be obtained when using data at just eight wavelengths, as an alternative to evaluating the whole spectrum.
关键词： Coniferous wood,Knot detection,Near infrared spectroscopy (NIRS),Random frog algorithm,Least squares-support vector machines (LS-SVM)
更新于2025-09-23 15:23:52
-
Simultaneous Determination of Clarithromycin, Tinidazole and Omeprazole in Helicure Tablets Using Reflectance Near-Infrared Spectroscopy with the Aid of Chemometry
摘要： A near infrared spectroscopic method for the simultaneous determination of the active principles clarithromycin, tinidazole and omeprazole in a pharmaceutical preparation was developed. The three active principles are quantified using partial least-squares regression methods. The proposed method is applicable over a wide analyte concentration range (80–120%) of labeled content, so it requires careful selection of the calibration set and to ensure thorough homogenization of the product. The method was validated in accordance with the ICH standard validation guidelines for NIR spectroscopy by determining its selectivity, linearity, accuracy, precision and stability. Based on the results, it is an effective alternative to the existing choice (HPLC) for the same purpose.
关键词： Partial least squares,Clarithromycin,Helicure,Near Infrared Spectroscopy,Preprocessing,Genetic algorithm,Multivariate calibration
更新于2025-09-23 15:23:52
-
Real-time estimation of time-dependent imposed heat flux in graded index media by KF-RLSE algorithm
摘要： Due to the large computational time caused by complex computational process of the existing inversion algorithm, real-time reconstruction of high-magnitude time-dependent heat flux in graded index media is quite challenging. In this study, based on hybrid technology of the Kalman filter and recursive least-square estimator (KF-RLSE), the real time reconstructed high-magnitude time-varying heat flux on graded index media surface, and the measurement information comes from the opposite side of the media. The ideal participating media, which is assumed to be isotropic scattering, constant thermophysical properties, and opaque and diffuse gray boundary, is employed to verify the reliability and validity of the proposed. All the reconstruction results show that the KF-RLSE algorithm can effectively reconstruct the boundary heat flux regardless of the positive or negative gradient of the refractive index. When the refractive index of each position increases or reduces, the transient heat flux on the surface can still be predicted effectively and acceptably. Furthermore, effects of different parameters on the accuracy and stability of the estimated results are also investigated. The reconstructed results show that the time-dependent heat flux can still be effectively reconstructed even when the measurement noise does not match its covariance. Meanwhile, the accuracy of the reconstruction results improves with the decrease of measurement noise covariance when the measurement noise distribution is fixed in a curtain range.
关键词： Recursive least squares estimator,Inverse radiation-conduction problem,Time-dependent heat flux,Graded index media,Kalman filter
更新于2025-09-23 15:23:52
-
Classification of pre-dyed textile fibers exposed to weathering and photodegradation by non-destructive excitation-emission fluorescence spectroscopy paired with discriminant unfolded-partial least squares
摘要： Undyed textile fabrics such as Acrylic 864, Nylon 361 and Cotton 400 were pre-dyed with Basic Green 4 (BG4), Acid Yellow 17 (AY17) and Direct Blue 1 (DB1) dyes, respectively; and then exposed to two extremely diverse weather conditions in the United States: desert and humid environmental settings in Arizona (AZ) and Florida (FL) respectively, for different time intervals of exposure, which included 0, 3, 6, 9 and 12 months. After every interval of a 3 months period, ten fibers were uniformly sampled from each cloth piece, and fluorescence microscopy was employed to collect two-dimensional excitation and fluorescence spectra (2-D spectra) and three-dimensional (3D) excitation-emission matrices (EEMs). A significant loss of fluorescence intensity was observed upon fiber exposure to outdoor weathering conditions. For a comprehensive statistical data analysis and to be able to discriminate between any two single fibers weathered under different conditions, a multiway calibration algorithm known as discriminant unfolded partial least-squares (DU-PLS) method was applied to the exposed fibers. Results indicate that fluorescence spectroscopy combined with DU-PLS has the ability to appropriately classify and differentiate between any two pairs of dyed cotton or nylon fibers (acrylic in some cases) exposed to dry versus humid weather environments under different time intervals of exposure. These results provide the foundation for future studies towards a non-destructive approach capable to provide information on the weathering history of the fiber.
关键词： Discriminant unfolded partial least squares,Fiber analysis,Photodegradation,Excitation emission matrices,Weathering,Fluorescence spectroscopy
更新于2025-09-23 15:23:52
-
Predicting Apple Firmness and Soluble Solids Content Based on Hyperspectral Scattering Imaging Using Fourier Series Expansion
摘要： This article reports on using a Fourier series expansion method to extract features from hyperspectral scattering profiles for apple fruit firmness and soluble solids content (SSC) prediction. Hyperspectral scattering images of ‘Golden Delicious’ (GD), ‘Jonagold’ (JG), and ‘Delicious’ (RD) apples, harvested in 2009 and 2010, were acquired using an online hyperspectral imaging system over the wavelength region of 500 to 1000 nm. The moment method and Fourier series expansion method were used to analyze the scattering profiles of apples. The zeroth-first order moment (Z-FOM) spectra and Fourier coefficients were extracted from each apple, which were then used for developing fruit firmness and SSC prediction models using partial least squares (PLS) and least squares support vector machine (LSSVM). The PLS models based on the Fourier coefficients improved the standard errors of prediction (SEP) by 4.8% to 19.9% for firmness and by 2.4% to 13.5% for SSC, compared with the PLS models using the Z-FOM spectra. The LSSVM models for the prediction set of Fourier coefficients achieved better SEP results, with improvements of 4.4% to 11.3% for firmness and 2.8% to 16.5% for SSC over the LSSVM models for the Z-FOM spectra data and 3.7% to 12.6% for firmness and 5.4% to 8.6% for SSC over the PLS models for the Fourier coefficients. Experiments showed that Fourier series expansion provides a simple, fast, and effective means for improving hyperspectral scattering prediction of fruit internal quality when used with either PLS or LSSVM.
关键词： Partial least squares,Soluble solids content,Apples,Least squares support vector machine,Fourier series expansion,Hyperspectral scattering imaging,Firmness
更新于2025-09-23 15:22:29
-
Green method by diffuse reflectance infrared spectroscopy and spectral region selection for the quantification of sulphamethoxazole and trimethoprim in pharmaceutical formulations
摘要： An alternative method for the quantification of sulphametoxazole (SMZ) and trimethoprim (TMP) using diffuse reflectance infrared Fourier-transform spectroscopy (DRIFTS) and partial least square regression (PLS) was developed. Interval Partial Least Square (iPLS) and Synergy Partial Least Square (siPLS) were applied to select a spectral range that provided the lowest prediction error in comparison to the full-spectrum model. Fifteen commercial tablet formulations and forty-nine synthetic samples were used. The ranges of concentration considered were 400 to 900 mg g-1 SMZ and 80 to 240 mg g-1 TMP. Spectral data were recorded between 600 and 4000 cm-1 with a 4 cm-1 resolution by Diffuse Reflectance Infrared Fourier Transform Spectroscopy (DRIFTS). The proposed procedure was compared to high performance liquid chromatography (HPLC). The results obtained from the root mean square error of prediction (RMSEP), during the validation of the models for samples of sulphamethoxazole (SMZ) and trimethoprim (TMP) using siPLS, demonstrate that this approach is a valid technique for use in quantitative analysis of pharmaceutical formulations. The selected interval algorithm allowed building regression models with minor errors when compared to the full spectrum PLS model. A RMSEP of 13.03 mg g-1 for SMZ and 4.88 mg g-1 for TMP was obtained after the selection the best spectral regions by siPLS.
关键词： green analytical method,diffuse reflectance infrared Fourier transform spectroscopy,interval partial least squares (iPLS),chemometrics,synergy partial least squares (siPLS),high performance liquid chromatography
更新于2025-09-23 15:22:29
-
On the Condition Number of a Normal Matrix in Near-Field to Far-Field Transformations
摘要： In near-field scanning, the model parameters for the antenna under test (AUT) can be determined from measured probe outputs by solving a linear system of equations in the least-squares sense. The model parameters are far-field pattern values, cylindrical or spherical-wave expansion coefficients, or equivalent surface-source values. The normal matrix of this linear system of equations is sometimes extremely ill-conditioned. This occurs when certain sets of model parameters lie outside the spatial bandwidth of the operator that computes the probe output. One remedy is to restrict the sets of model parameters allowed and perform up-sampling if needed to achieve the desired accuracy. These ideas are illustrated through analysis and examples that involve both two and three dimensional scanning geometries.
关键词： Near-field scanning,least-squares solution,condition number,linear system of equations
更新于2025-09-23 15:22:29
-
Rapid Quantitative Analysis of Forest Biomass Using Fourier Transform Infrared Spectroscopy and Partial Least Squares Regression
摘要： Fourier transform infrared reflectance (FTIR) spectroscopy has been used to predict properties of forest logging residue, a very heterogeneous feedstock material. Properties studied included the chemical composition, thermal reactivity, and energy content. The ability to rapidly determine these properties is vital in the optimization of conversion technologies for the successful commercialization of biobased products. Partial least squares regression of first derivative treated FTIR spectra had good correlations with the conventionally measured properties. For the chemical composition, constructed models generally did a better job of predicting the extractives and lignin content than the carbohydrates. In predicting the thermochemical properties, models for volatile matter and fixed carbon performed very well (i.e., R2 > 0.80, RPD > 2.0). The effect of reducing the wavenumber range to the fingerprint region for PLS modeling and the relationship between the chemical composition and higher heating value of logging residue were also explored. This study is new and different in that it is the first to use FTIR spectroscopy to quantitatively analyze forest logging residue, an abundant resource that can be used as a feedstock in the emerging low carbon economy. Furthermore, it provides a complete and systematic characterization of this heterogeneous raw material.
关键词： FTIR spectroscopy,forest logging residue,energy content,partial least squares regression,thermal reactivity,chemical composition
更新于2025-09-23 15:22:29
-
Use of A Portable Camera for Proximal Soil Sensing with Hyperspectral Image Data
摘要： In soil proximal sensing with visible and near-infrared spectroscopy, the currently available hyperspectral snapshot camera technique allows a rapid image data acquisition in a portable mode. This study describes how readings of a hyperspectral camera in the 450–950 nm region could be utilised for estimating soil parameters, which were soil organic carbon (OC), hot-water extractable-C, total nitrogen and clay content; readings were performed in the lab for raw samples without any crushing. As multivariate methods, we used PLSR with full spectra (FS) and also combined with two conceptually different methods of spectral variable selection (CARS, “competitive adaptive reweighted sampling” and IRIV, “iteratively retaining informative variables”). For the accuracy of obtained estimates, it was beneficial to use segmented images instead of image mean spectra, for which we applied a regular decomposing in sub-images all of the same size and k-means clustering. Based on FS-PLSR with image mean spectra, obtained estimates were not useful with RPD values less than 1.50 and R2 values being 0.51 in the best case. With segmented images, improvements were marked for all soil properties; RPD reached values ≥ 1.68 and R2 ≥ 0.66. For all image data and variables, IRIV-PLSR slightly outperformed CARS-PLSR.
关键词： spectral variable selection,hyperspectral snapshot camera,partial least squares regression,multivariate calibration,hyperspectral imaging,proximal soil sensing
更新于2025-09-23 15:22:29
-
Proximal VIS-NIR spectrometry to retrieve substance concentrations in surface waters using partial least squares modelling
摘要： Many water quality parameters such as concentrations of suspended matter, nutrients and algae directly or indirectly change the electromagnetic reflectance and transmission properties of surface water bodies. Optical measurement approaches have shown great potential to partially substitute water sampling and laboratory analyses, but are obstructed by limited flexibility or high maintenance demands. In order to overcome these problems and to bridge the gap between in situ and remote sensing measurements, the use of close-range, above-surface reflectance measurements in the VIS-NIR domain to measure water quality parameters in surface water bodies was investigated. Remote sensing reflectance in a 1 m3 water tank with increasing, known concentrations of suspended solids was measured. A partial least squares model was trained to predict concentrations from reflectance curves, which performed well, considering the wide range of concentrations and illumination conditions (R2cal ? 0.96, R2val ? 0.97). The approach was then transferred to the field and further parameters were tested. Using a semi-autonomous spectrometer mounted to a boom stand on a motor boat, we traced substance concentrations in close intervals along a longitudinal gradient from inflow to dam in a drinking water reservoir in Brazil. The method is suitable for parameters directly influencing the reflection properties of the water body (e.g. suspended solids (R2cal ? 0.93), chlorophyll-a (R2cal ? 0.74)), or for parameters closely related to those (e.g. total phosphorus (R2cal ? 0.97)). For chemical oxygen demand, the method is not well suited (R2cal ? 0.14, R2val ? 0.45). Once calibrated to the local conditions, the spectrometer can be used stationary or on moving platforms to map and monitor surface waters. The integration of the procedure into acoustic and imaging techniques is further investigated.
关键词： water quality,suspended solids,hyperspectral,reservoir,partial least squares,proximal sensing
更新于2025-09-23 15:22:29