Search Results (10)

Spectral indices such as NDRE (Normalized Difference Red Edge Index), CCCI (Canopy Chlorophyll Content Index), and IRECI (Inverted Red Edge Chlorophyll Index), derived from the Red Edge band of MSI/Sentinel-2A (B05, B06, B07), are critical for coffee monitoring. To align the Red Edge band (20 m resolution) with the NIR band (10 m resolution), the nearest neighbor, bilinear, cubic and Lanczos resampling methods were used, available in the Terra package in the R software(4.4.0). This study evaluates these methods using two original B05 images from 24 November 2023, and 21 September 2023, covering the “Ouro Verde” (15 ha) and “Canto do Rio” (45 ha) farms in Bahia, Brazil. A total of 500 random points were analyzed using PSF, linear models, and cross-validation with R², MAE, and RMSE. PSF analysis confirmed data integrity, and the cubic method demonstrated the best performance (R² = 0.996, MAE = 0.008 and RMSE = 0.012 in the “Ouro Verde” Farm and R² = 0.995, MAE = 0.007 and RMSE = 0.011 in the “Canto do Rio” Farm). The results highlight the importance of selecting appropriate resampling methods for precise remote sensing in coffee cultivation, ensuring accurate digital processing aligned with study objectives. Full article

This paper describes a Krylov subspace iterative method designed for solving linear systems of equations with a large, symmetric, nonsingular, and indefinite matrix. This method is tailored to enable the evaluation of error estimates for the computed iterates. The availability of error estimates makes it possible to terminate the iterative process when the estimated error is smaller than a user-specified tolerance. The error estimates are calculated by leveraging the relationship between the iterates and Gauss-type quadrature rules. Computed examples illustrate the performance of the iterative method and the error estimates. Full article

In the optical satellite on-orbit imaging quality estimation system, the calculation of Modulation Transfer Function (MTF) is not fully standardized, and the influence of atmosphere is often simplified, making it difficult to obtain completely consistent on-orbit MTF measurements and comparisons. This study investigates the effects of various factors—such as edge angle, edge detection methods, oversampling rate, and interpolation techniques—on the accuracy of MTF calculations in the commonly used slanted-edge method for on-orbit MTF assessment, informed by simulation experiments. A relatively optimal MTF calculation process is proposed, which employs the Gaussian fitting method for edge detection, the adaptive oversampling rate, and the Lanczos (a = 3) interpolation method, minimizing the absolute deviation in the MTF results. A method to quantitatively analyze the atmospheric scattering and absorption MTF is proposed that employs a radiative transfer model. Based on the edge images of GF-2 satellite, images with various atmospheric conditions and imaging parameters are simulated, and their atmospheric scattering and absorption MTF is obtained through comparing the MTFs of the ground and top atmosphere radiance. The findings reveal that aerosol optical depth (AOD), viewing zenith angle (VZA), and altitude (ALT) are the primary factors influencing the accuracy of GF-2 satellite on-orbit MTF measurements in complex scenarios. The on-orbit MTF decreases with the increase in AOD and VZA and increases with the increase in ALT. Furthermore, a collaborative analysis of the main influencing factors of atmospheric scattering and absorption MTF indicates that, taking the PAN band of the GF-2 satellite as an example, the atmospheric MTF values are consistently below 0.7905. Among these, 90% of the data are less than 0.7520, with corresponding AOD conditions ranging from 0 to 0.08, a VZA ranging from 0 to 50°, and an ALT ranging from 0 to 5 km. The results can provide directional guidance for the selection of meteorological conditions, satellite attitude, and geographical location during satellite on-orbit testing, thereby enhancing the ability to accurately measure satellite MTF. Full article

Heart sounds and murmur provide crucial diagnosis information for valvular heart diseases (VHD). A phonocardiogram (PCG) combined with modern digital processing techniques provides a complementary tool for clinicians. This article proposes a benchmark different time–frequency representations, which are spectograms, mel-spectograms and cochleagrams for obtaining images, in addition to the use of two interpolation techniques to improve the quality of the images, which are bicubic and Lanczos. Deep features are extracted from a pretrained model called VGG16, and for feature reduction, the Boruta algorithm is applied. To evaluate the models and obtain more precise results, nested cross-validation is used. The best results achieved in this study were for the cochleagram with 99.2% accuracy and mel-spectogram representation with the bicubic interpolation technique, which reached 99.4% accuracy, both having a support vector machine (SVM) as a classifier algorithm. Overall, this study highlights the potential of time–frequency representations of PCG signals combined with modern digital processing techniques and machine learning algorithms for accurate diagnosis of VHD. Full article

The vibration of the tires significantly impacts a vehicle’s ride comfort and noise level; however, the current analysis of tire vibration characteristics often involves excessive simplification in their models, leading to a reduction in model accuracy. To analyze the tire vibrational properties and the influence of its design and service conditions, a combined modeling technology was developed to construct a three-dimensional (3D) finite element model of a 205/55R16 specification radial tire with intricate tread patterns. The accuracy and reliability of the simulation model was verified through vibration modal tests. Based on the vibration mode theory, the Lanczos method provided by ABAQUS was adopted to analyze the modal characteristics of the tire under free inflation and grounded conditions, and the effects of different inflation pressures, loads, operating conditions, and belt cord angles on the tire vibration characteristics were analyzed. The results indicate that grounding constraints will suppress the low order radial modal frequency of the tire and enhance the lateral modal frequency. The higher the order of the tire vibration mode, the greater the impact of inflation pressure. As the operating conditions change, the modal frequencies of all directions have the same trend of change, and as the ground load increases, the tire is prone to misalignment at lower lateral frequencies. The radial and lateral grounding modes of the tire are slightly affected by the change of the cord angle in the belt layer, but the circumferential grounding frequency decreases as the belt layer angle increases. These research findings offer a crucial foundation for the structural design of complex tread pattern tires, and also serve as a reference for addressing vibration and comfort issues encountered in the tire matching process. Full article

The generalized eigenvalue problem for a symmetric definite matrix pencil obtained from finite-element modeling of electroelastic materials is solved numerically by the Lanczos algorithm. The mass matrix is singular in the considered problem, and therefore the process proceeds with the semi-inner product defined by this matrix. The shift-and-invert Lanczos algorithm is used to find multiple eigenvalues closest to some shift and the corresponding eigenvectors. The results of the numerical experiments are presented. Full article

Resolution plays an essential role in oral imaging for periodontal disease assessment. Nevertheless, due to limitations in acquisition tools, a considerable number of oral examinations have low resolution, making the evaluation of this kind of lesion difficult. Recently, the use of deep-learning methods for image resolution improvement has seen an increase in the literature. In this work, we performed two studies to evaluate the effects of using different resolution improvement methods (nearest, bilinear, bicubic, Lanczos, SRCNN, and SRGAN). In the first one, specialized dentists visually analyzed the quality of images treated with these techniques. In the second study, we used those methods as different pre-processing steps for inputs of convolutional neural network (CNN) classifiers (Inception and ResNet) and evaluated whether this process leads to better results. The deep-learning methods lead to a substantial improvement in the visual quality of images but do not necessarily promote better classifier performance. Full article

This paper describes a new design method that was developed to achieve an optimal design method for weight reduction of a bell crank, sourced from a Louis Christen Road Racing F1 Sidecar. The method involved reverse engineering to produce a 3D model of the mechanical part. The 3D bell crank model was converted to a finite element (FE) model to characterize the eigenvalues of vibration and responses to excitation using the Lanczos iteration method in Abaqus software. The bell crank part was also tested using a laser vibrometer to capture its natural frequencies and corresponding vibration mode shapes. The test results were used to validate the FE model, which was then analysed through a topology optimization process. The objective function was the weight and the optimization constraints were the stiffness and the strain energy of the structure. The optimized design was converted back to a 3D model and then fabricated to produce a physical prototype for design verification and validation by means of FE analysis and laboratory experiments and then compared with the original part. Results indicated that weight reduction was achieved while also increasing the natural frequency by 2%, reducing the maximum principal strain and maximum von Mises stress by 4% and 16.5%, respectively, for the optimized design when compared with the original design. The results showed that the proposed method is applicable and effective in topology optimization to obtain a lightweight (~3% weight saving) and structurally strong design. Full article

We propose and investigate two new methods to approximate $f\left(\mathbf{A}\right)\mathbf{b}$ for large, sparse, Hermitian matrices $\mathbf{A}$. Computations of this form play an important role in numerous signal processing and machine learning tasks. The main idea behind both methods is to first estimate the spectral density of $\mathbf{A}$, and then find polynomials of a fixed order that better approximate the function f on areas of the spectrum with a higher density of eigenvalues. Compared to state-of-the-art methods such as the Lanczos method and truncated Chebyshev expansion, the proposed methods tend to provide more accurate approximations of $f\left(\mathbf{A}\right)\mathbf{b}$ at lower polynomial orders, and for matrices $\mathbf{A}$ with a large number of distinct interior eigenvalues and a small spectral width. We also explore the application of these techniques to (i) fast estimation of the norms of localized graph spectral filter dictionary atoms, and (ii) fast filtering of time-vertex signals. Full article

We propose a numerical technique suitable for simulating the dynamics of reduced density matrix of a qubit interacting with its environment. Our approach, based on a combination of short-iterative Lanczos method (SIL) and a flexible truncation scheme, allows to include in the physical description multiple-excitation processes, beyond weak coupling and Markov approximations. We perform numerical simulations of two different model Hamiltonians, that are relevant in the field of adiabatic quantum computation (AQC), and we show that our technique is able to recover the correct thermodynamic behavior of the qubit-bath system, from weak to intermediate coupling regime. Full article