- 标题
- 摘要
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- 实验方案
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Assessment of different combinations of meteorological parameters for predicting daily global solar radiation using artificial neural networks
摘要： In this study, for determining the best-input scenarios of the used parameters in predicting the Daily Global Solar Radiation (DGSR), a new approach based on Artificial Neural Networks (ANNs) was presented. The proposed approach is based on comparisons between all possible input combinations for determining the best scenarios that can give perfect correlations and approximations with DGSR. Recorded data from 35 stations belonging to different climatic zones (27 in Morocco and 8 in neighboring countries) were reported for training and testing the obtained results. The used input parameters include geographical coordinates, sun declination, day length, day number, clearness index (KI), Top Of Atmosphere (TOA), average ambient temperature (Ta), maximum temperature (Tmax), minimum temperature (Tmin), difference temperature (ΔT), temperature ratio (TR), relative humidity (Rh) and wind speed (Ws). The results revealed 128 best-input scenarios, where the first relevant input combination was found for KI, Ta, ΔT, TR and TOA. This result indicated that the best-input scenario for predicting DGSR is based only on three climatological parameters: KI, function of Ta f(Ta) and TOA. In addition, based on these found best-input scenarios and on the least square regression (LSR) technique, 128 new linear relationships between DGSR and the found best-input combinations were developed. The statistical analysis expressed through statistical criteria indicated perfect correlations and approximations between the predicted and measured values of DGSR.
关键词： Best scenarios,ANNs,Least square regression,Statistical analysis,Solar radiation modelling,Forecasting
更新于2025-09-23 15:23:52
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Nondestructive Detection of Postharvest Quality of Cherry Tomatoes Using a Portable NIR Spectrometer and Chemometric Algorithms
摘要： The aim of this study was to assess the applicability of a portable NIR spectroscopy system and chemometric algorithms in intelligently detecting postharvest quality of cherry tomatoes. The postharvest quality of cherry tomatoes was evaluated in terms of firmness, soluble solids content (SSC), and pH, and a portable NIR spectrometer (950–1650 nm) was used to obtain the spectra of cherry tomatoes. Partial least square (PLS), support vector machine (SVM), and extreme learning machine (ELM) were applied to predict the postharvest quality of cherry tomatoes from their spectra. The effects of different preprocessing techniques, including Savitzky–Golay (S-G), multiplicative scattering correction (MSC), and standard normal variate (SNV) on prediction performance were also evaluated. Firmness, SSC and pH values of cherry tomatoes decreased during storage period, based on which the tomato samples could be classified into two distinct clusters. Similarly, cherry tomatoes with different storage time could also be separated by the NIR spectroscopic characteristics. The best prediction accuracy was obtained from ELM algorithms using the raw spectra with Rp2, RMSEP, and RPD values of 0.9666, 0.3141 N, and 5.6118 for firmness; 0.9179, 0.1485%, and 3.6249 for SSC; and 0.8519, 0.0164, and 2.7407 for pH, respectively. Excellent predictions for firmness and SSC (RPD value greater than 3.0), good prediction for pH (RPD value between 2.5 and 3.0) were obtained using ELM model. NIR spectroscopy is capable of intelligently detecting postharvest quality of cherry tomatoes during storage.
关键词： Partial least square,Extreme learning machine,Support vector machine,Cherry tomato,Near infrared spectroscopy
更新于2025-09-23 15:23:52
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Robust Optical Flow Estimation Using Tchebichef Moment Invariant Feature
摘要： In this paper, orthogonal moment invariant-based features are used to compute 2D optical flow from sequence of images. The gray level of pixel is described in terms of its local neighborhood using Tchebichef moment invariants rather than its individual intensity value. The description is then normalized in order to make it insensitive to intensity fluctuations due to noise or other perturbations such as varying illumination conditions. The principle of conservation of moment invariance is used to derive overdetermined system of 2D motion constraint equations in local neighborhood of each pixel. The velocity field is then estimated using the least square method. Experimental results are performed on sequential video and thermal image frames under varying environmental conditions. The run time, robustness against noisy and varying illumination conditions and rotation invariance of proposed method are compared with already existing moment and non-moment-based techniques.
关键词： Tchebichef moment,Least square estimation,Moment invariant,Optical flow,Zernike moment,Velocity field
更新于2025-09-23 15:23:52
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Measurement of proton quenching in a LAB-based liquid scintillator
摘要： In this paper, we propose a mathematical model to evaluate the transmission of Tuberculosis with drug-resistant strains and with drug-sensitive strains. Based on the epidemic data from Chinese Center for Disease Control and Prevention, we first estimate the values of parameters in the model. Then the basic reproduction number of TB infection in the mainland China is calculated to be 1.0558. Since the basic reproduction number is greater than 1, Tuberculosis spreads as an endemic in mainland China. Through our investigations, the basic reproduction number associated with drug-sensitive strains is less than 1, but the number of individuals infected by drug-resistant strains will still increase quickly, thus the epidemic is not under control. Moreover, increasing the vaccination coverage rate for newborns is not always beneficial for controlling TB prevalence in China. Whether vaccination effect is positive or negative depends on the relapse rate from the recovered state to the infected state. In summary, improving sanitation conditions, introducing efficient measures to detect the disease, and keeping the public informed about how to lower the chance of being infected and the current epidemic situation are essential in slowing down or eliminating Tuberculosis transmission.
关键词： Tuberculosis Transmission,Drug-Sensitive Strain,The Basic Reproduction Number,Drug-Resistant Strain,Least-Square Method
更新于2025-09-23 15:23:52
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Portable spectroscopic system for <i>in vivo</i> skin neoplasms diagnostics by Raman and autofluorescence analysis
摘要： This paper studies the applicability of a portable cost-effective spectroscopic system for the optical screening of skin tumors. In vivo studies of Raman scattering and autofluorescence of skin tumors with the 785 nm excitation laser in the near infrared region included malignant melanoma, basal cell carcinoma, and various types of benign neoplasms. The efficiency of the portable system was evaluated by comparison with a highly sensitive spectroscopic system and with the diagnosis accuracy of a human oncologist. Partial least square analysis of Raman and autofluorescence spectra was performed; specificity and sensitivity of various skin oncological pathologies detection varied from 78.9% to 100%. 100% accuracy of benign and malignant skin tumors differentiation is possible only with a combined analysis of Raman and autofluorescence signals.
关键词： autofluorescence,optical biopsy,portable spectroscopic equipment,skin neoplasms,melanoma,partial least square analysis,Raman spectroscopy,malignancy
更新于2025-09-23 15:23:52
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[IEEE 2018 International Conference on Communication and Signal Processing (ICCSP) - Chennai (2018.4.3-2018.4.5)] 2018 International Conference on Communication and Signal Processing (ICCSP) - A Comparative Analysis of Total Variation and Least Square Based Hyperspectral Image Denoising Methods
摘要： Hyperspectral image (HSI) with high spectral resolution will be always degraded by the noise accumulation. Therefore, image denoising is a fundamental preprocessing technique which improves the precision of successive processes like image classification, unmixing etc. In this paper, we compare least square (LS) weighted regularization in spectral domain with spatial least square and total variation (TV) denoising techniques. These methods are experimented on real, and noise simulated hyperspectral image datasets. The contrast and edges of the image are well preserved in the spectral LS. The image contrast varies in spatial LS, and edge informations are lost in TV. The experimental results show that, the spectral LS is superior to other two techniques in terms of visual interpretation, Signal-to-Noise Ratio (SNR) and Structural Similarity (SSIM) Index.
关键词： IBBC,SNR,Least Square,Hyperspectral Image,Denoising,Spectral domain,Total Variation,SSIM
更新于2025-09-23 15:22:29
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Adaptive SVD Domain-Based White Gaussian Noise Level Estimation in Images
摘要： Noise level estimation is a challenging area of digital image processing with a variety of applications, including image enhancement, image segmentation, and feature extraction. In this paper, an adaptive estimation of additive white Gaussian noise level based on the singular value decomposition (SVD) of images is proposed. The proposed algorithm aims to improve the performance of noise level estimation in the SVD domain at low noise levels. An initial noise level estimate is used to adjust the parameters of the algorithm in order to increase the accuracy of noise level estimation. The proposed algorithm exhibits the ability to adapt the number of considered singular values and to accordingly adjust the slope of a linear function that describes how the average value of the singular value tail varies with noise levels. Although, for each image, the proposed algorithm performs the noise level estimation twice in two distinct stages, the singular value decompositions are only performed in the first stage of the algorithm. The experimental results demonstrate that the proposed algorithm improves the noise level estimation at low noise levels without a significant increase in computational complexity. At noise level σ = 15, the improvements in the mean square level are about 39% at the expense of slightly higher additional computational time.
关键词： artificial neural networks,singular value decomposition,image analysis,noise level estimation,Digital images,AWGN,least square methods
更新于2025-09-23 15:22:29
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Omega-K Algorithm Based on Series Reversion and Least Square for High-Resolution Spaceborne SAR
摘要： When processing high-resolution spaceborne synthetic aperture radar (SAR) data, the orbit curvature is a key aspect that must be taken into account. The non-hyperbolic range history makes most SAR imaging approaches not suitable for the curved orbit. Based on the two-dimensional spectrum derived by series reversion (SR), a modified Omega-K algorithm (OKA) is proposed in this paper. Making use of the reference function calculated by SR, an accurate bulk compression is implemented. Following, a modified Stolt interpolation is applied based on least square (LS), to perform the residual range-variant processing efficiently. The method described can achieve satisfactory focusing results for spaceborne SAR, without a large number of computation. Point targets simulations have validated the presented research.
关键词： curved orbit,Omega-K algorithm,Spaceborne synthetic aperture radar,series reversion,least square
更新于2025-09-23 15:22:29
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Optical plasma boundary reconstruction based on least squares for EAST Tokamak
摘要： Reconstructing the shape and position of plasma is an important issue in Tokamaks. Equilibrium and fitting (EFIT) code is generally used for plasma boundary reconstruction in some Tokamaks. However, this magnetic method still has some inevitable disadvantages. In this paper, we present an optical plasma boundary reconstruction algorithm. This method uses EFIT reconstruction results as the standard to create the optimally optical reconstruction. Traditional edge detection methods cannot extract a clear plasma boundary for reconstruction. Based on global contrast, we propose an edge detection algorithm to extract the plasma boundary in the image plane. Illumination in this method is robust. The extracted boundary and the boundary reconstructed by EFIT are fitted by same-order polynomials and the transformation matrix exists. To acquire this matrix without camera calibration, the extracted plasma boundary is transformed from the image plane to the Tokamak poloidal plane by a mathematical model, which is optimally resolved by using least squares to minimize the error between the optically reconstructed result and the EFIT result. Once the transform matrix is acquired, we can optically reconstruct the plasma boundary with only an arbitrary image captured. The error between the method and EFIT is presented and the experimental results of different polynomial orders are discussed.
关键词： Least square,Global contrast,EAST Tokamak,Optical boundary reconstruction,Boundary detection
更新于2025-09-23 15:22:29
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Simultaneous quantitative analysis of indomethacin and benzoic acid in gel using ultra-violet-visible spectrophotometry and chemometrics
摘要： BACKGROUND: In order to manufacture pharmaceutical products, real-time monitoring in the manufacturing process is necessary, but large equipment cost is required to achieve it. OBJECTIVE: The aim of this research is to use ultra-violet-visible spectroscopy along with chemometrics procedure to simultaneously quantitative analysis of indomethacin (IMC) and benzoic acid (BA) in the gel during pharmaceutical manufacturing process. METHODS: The gel preparations were contained of 0.1–1.5% IMC, 0.015–0.225% BA, 2% carbopol? 941 and 95% ethanol solution. The calibration models were constructed using the partial least square regression (PLS). RESULTS: The relationships of the measured and predicted concentrations for both IMC and BA had linear plots. The developed PLS calibration models were used to monitor the IMC and BA concentrations during mixing of the gels by the planetary centrifugal and conventional mixers, respectively. IMC and BA were gradually dispersed, dissolved and completely homogeneous within 30 min by the centrifugal mixer. In contrast, IMC and BA were slowly dispersed, dissolved and completely homogeneous at more than 60 min by the conventional mixer. CONCLUSIONS: The ultra-violet-visible spectrophotometric method couples with multivariate chemometric techniques for quantitative data analysis were successfully applied for the simultaneous determination of major component IMC and trace component BA in the gel.
关键词： benzoic acid,indomethacin,partial least square regression,Ultra-violet-visible spectroscopy,process analysis technology,process monitoring
更新于2025-09-23 15:22:29