Papers by Keyword: NIR

Abstract: The greenhouse is widely used in agriculture, and its covering material is one of the most important factors that affect its performance. In summer, the inner temperature of the greenhouse is usually too high for people to cultivate plants. In this work, a polymer matrix composite (PMC) was developed to reduce the inner temperature of the greenhouse without affecting the photosynthesis for the growth of plants. The PMC developed in this study was made of LDPE with suitable additives such as pigments, metal oxide etc. The morphology of the covering layer made of the PMC was observed with the atomic force microscopy (AFM). The transmittance of visible light and NIR through the cladding layer was measured with an optical fiber detector and used as the primarily performance index. Finally a simulated greenhouse was used to verify the cooling effect of the cladding layer. Experimental results showed that the PMC developed in this study gave more temperature reduction than that of the commercial PE covering.

Abstract: A photoplethysmographic (PPG) near infrared (850nm) system has been developed for the non-invasive assessment of superficial tissues’ (skin) swelling and redness. The PPG signal is treated to avoid ambient light and to extract the DC (direct current) and AC (alternate current) components. These components are then subtracted from the same components acquired on a reference site on the same subject. The resulting measures are used in a model able to classify different states of inflammation of the tissues. Numerical results permit to follow the inflammation state and to evaluate possible medical and physiotherapy interventions. To avoid artefacts due to compression of the skin by the instrument, a pressure sensor has been also embedded on the optical sensing head of the system, so that the measures are considered as valid only if they are taken within the same range of applied pressure on the skin. This is important to get comparable PPG measures. Heart rate and hemoglobin oxygen saturation measures are a by-product out of the system and they can be exploited for other purposes or they can be taken into account for a better evaluation of the inflammation state. Although the system is still a research prototype and no real model is available about how inflammation affects the optical properties of the skin, the very first qualitative results show a strong sensibility of the system to skin alterations due to acute inflammation.

Abstract: Calcium yttrium silicoborate glasses doped with different Nd³⁺ ion concentrations have been prepared using the melt quenching technique at 1400 °C. Physical, optical and luminescence properties of glass samples were investigated. The density and molar volume measurements were carried out at room temperature. The results show that, the density and molar volume of glass samples not deepened on the concentration of Nd₂O₃. Absorption spectra were investigated in the UV–VIS–NIR region from 200 to 2500 nm. It was observed that the absorption bands have 8 peaks with corresponding to 467, 521, 584, 638, 682, 747, 805 and 877 nm. The luminescence properties were investigated in the NIR region. On excitation, with 584 and 805 nm, it is found that the emission peaks are located at 896 (904), 1060 and 1332 nm that correspond to the emission transitions from ⁴F_3/2 to ⁴I_9/2, ⁴I_11/2 and ⁴I_13/2, respectively. The NIR luminescence intensity obtained with 584 nm excitation was stronger than 805 nm.

Abstract: In this study, qualitative and quantitative analyses of peanut oils adulterated with waste oil, soybean oil, corn oil and canola oil were performed by combining near infrared (NIR) spectroscopy with chemometrics methods. With NIR spectrometer, the spectra of 108 adulterated peanut oil samples were collected. The collected data were preprocessed with three different preprocessing approaches, including standard normal variate (SNV) transformation, de-trending (DT), and orthogonal signal correction (OSC). Backward interval partial least squares (BiPLS) was used to extract the characteristic wavelengths of the preprocessed data. On the intervals of the full spectrum and the characteristic wavelengths, support vector classification qualitative discriminant models and support vector regression quantitative analysis models were established. Experiments demonstrated that the established qualitative models could accurately determine the type of adulterant in peanut oil, with the accuracies on both the calibration set and the prediction set reaching 100%. With the quantitative models, the percentage of adulteration (3% ~ 55%) could be determined accurately, with correlation coefficients as high as 99.10%. All the models returned prediction root mean square errors lower than 6.96E-4. It was validated that the combination of NIR spectroscopy with chemometrics methods can realize the qualitative and quantitative detection of adulteration of peanut oil.

Abstract: An identifiable model based on near-infrared spectra (NIR) was proposed to distinguish the classification of greengrocery seeds. The performance of five pretreatment methods: Original, Smoothing, MSC (Multiplication scatter correction), SNV (Standard Normalized Variable) and FD (First Derivative) were utilized to reduce the noise in the original spectrum. The effective wavelengths were selected to remove the redundancy existing in the spectra by simulating stepwise regression. The performances of the model were optimized by the combination of pretreatments and effective wavelengths selection in this paper. Compared with the five pretreatment methods, SNV was superior to other methods with an accuracy of 100%. It is concluded that SNV coupled with simulating stepwise regression could be used to identify greengrocery seeds effectively.

Abstract: NIR spectroscopy has been applied in detecting inside quality of chestnut successfully. In this work, Support Vector Machine Discriminant Analysis was utilized to identify the qualified chestnuts, the serious moldy chestnuts and the slight moldy chestnuts using their Near infrared spectra region from 833 nm to 2500 nm. 109 chestnut samples were involved and four different preprocessing methods were compared. The results showed that for all the models, the average correct rates of training set and validation set were higher than 90%. The performance of model based on raw spectra was not as good as other models, which indicated the necessity of preprocessing. The models based on the spectra preprocessed by first derivative and multiplicative scatter correction had the same performances, with 97% and 85% as the correct rate of training set and validation set. The models based on the spectra preprocessed by Standard normal transformation has 100% correct rate of training set while 88% of validation set. The second derivative model had the best result with 100% and 90% as the correct rate of training set and validation set. These results demonstrated that the NIR spectroscopy had capability to detect interior mildew of intact chestnut nondestructively.

Abstract: Silica nanoparticles (Si NPs) have a wide range of uses in semiconductors, battery cathode material, and high power laser source materials. However, Si NPs would flow into the wastewater treatment inevitably, and then potentially harmful interactions can occur between nanoparticles and wastewater systems, especially in denitrification process. The present study was aimed to investigate the effects of Si NPs on nitrate nitrogen removal under anaerobic conditions by employing activated sludge. Our data demonstrates that Si NPs had positive effects on denitrification at the beginning and did not display any measurable effect on nitrite nitrogen removal at the concentration of 100 mg/L and below. The denitrification process was elucidated by using the first-order reaction kinetics equation. This study provided useful data for understanding the effects of Si NPs on wastewater treatment.

Abstract: In the present work, Cerium Fluoride (CeF₃) was selected as the host material because of its High density, fast response and high radiation resistance, efficient absorption and energy transfer by host (to activator). Rare earths have been used to show the process of Quantum Cutting (QC) via energy transfer process between Tb³⁺ and Yb³⁺ incorporated in CeF₃. For the synthesis of CeF₃ nanoparticles codoped with Tb³⁺ and Yb³⁺ ion, co-precipitation route was employed. Different doping concentrations were prepared to study the changes that take place in the luminescence spectra of the composition. Thus, concentration dependent study of the fluorescence of CeF₃: Tb³⁺, Yb³⁺ was carried out. These materials have great applications in solar cell devices as quantum efficiencies up to 200 % can be achieved.

Abstract: Palm vein pattern recognition is one of the newest biometric techniques researched today. In order to reduce the recognition calculation and increase the recognition accuracy, the region of interest (ROI) in the palm vein image must be selected. There are three areas on the palm: the center area of palm, the thenar area and the hypothenar area.This paper does contrast experiment of light absorption on the three area of palm. The experiment result is the thenar area is selected as the main scope of ROI.

Abstract: Do quantitative detection of talc-containing wheat flour using near infrared spectroscopy combined with BP neural network.Confect 50samples by adulterating talc to wheat flour,randomly selected nine samples as the prediction samples, formulated10 talc-free flour samples for qualitative analysis.The results show that:BP neural network combined with NIR for the determination of talc-containing flour is ideal, can be used for talc-containing flour; the result of cluster analysis should that it need to seek better methods for talc-containing wheat flour.