Mineral fillers are a fundamental component of asphalt mastic and play a critical role in governing the mechanical performance and durability of flexible pavements. Variations in filler type and dosage can substantially alter mastic stiffness, deformation resistance, fatigue behavior, and adhesion. The objective of this study is to systematically evaluate the influence of mineral filler type and filler-to-asphalt (F/A) ratio on the rheological, fatigue, and adhesive performance of asphalt mastics. Three commonly used fillers; limestone dust, Portland cement, and hydrated lime were investigated at four F/A ratios (0.6, 0.8, 1.0, and 1.2). A comprehensive experimental program was conducted, including conventional binder characterization, Mult

In this article, Convolution Neural Network (CNN) is used to detect damage and no damage images form satellite imagery using different classifiers. These classifiers are well-known models that are used with CNN to detect and classify images using a specific dataset. The dataset used belongs to the Huston hurricane that caused several damages in the nearby areas. In addition, a transfer learning property is used to store the knowledge (weights) and reuse it in the next task. Moreover, each applied classifier is used to detect the images from the dataset after it is split into training, testing and validation. Keras library is used to apply the CNN algorithm with each selected classifier to detect the images. Furthermore, the performa

In this work, the spectra for plasma glow produced by pulse
Nd:YAG laser (λ=532 and 1064nm) on Ag:Al alloy with same molar
ratio samples in distilled water were analyzed by studying the atomic
lines compared with aluminum and silver strong standard lines. The
effect of laser energies of the range 300 to 800 mJ on spectral lines,
produced by laser ablation, were investigated using optical
spectroscopy. The electron temperature was found to be increased
from 1.698 to 1.899 eV, while the electron density decreased from
2.247×1015 to 5.08×1014 cm-3 with increasing laser energy from 300
to 800 mJ with wavelength of 1064 nm. The values of electron
temperature using second harmonic frequency are greater than of<

In this work, p-n junctions were fabricated from highly-pure nanostructured NiO and TiO2 thin films deposited on glass substrates by dc reactive magnetron sputtering technique. The structural characterization showed that the prepared multilayer NiO/TiO2 thin film structures were highly pure as no traces for other compounds than NiO and TiO2 were observed. It was found that the absorption of NiO-on-TiO2 structure is higher than that of the TiO2-on-NiO. Also, the NiO/TiO2 heterojunctions exhibit typical electrical characteristics, higher ideality factor and better spectral responsivity when compared to those fabricated from the same materials by the same technique and with larger particle size and lower structural purity.

  Numerous integral and local electron density’s topological parameters of significant metal-metal and metal-ligand bonding interactions in a trinuclear tetrahydrido cluster [(Cp* Ir) (Cp Ru)₂ (μ₃-H) (μ-H)₃]1 (Cp = η⁵ -C₅Me₅), (Cp* = η⁵ -C₅Me₄Et) were calculated and interpreted by using the quantum theory of atoms in molecules (QTAIM). The properties of bond critical points such as the delocalization indices δ (A, B), the electron density ρ(r), the local kinetic energy density G(r), the Laplacian of the electron density ∇²ρ(r), the local energy density

          The primary objective of this paper is to improve a biometric authentication and classification model using the ear as a distinct part of the face since it is unchanged with time and unaffected by facial expressions. The proposed model is a new scenario for enhancing ear recognition accuracy via modifying the AdaBoost algorithm to optimize adaptive learning. To overcome the limitation of image illumination, occlusion, and problems of image registration, the Scale-invariant feature transform technique was used to extract features. Various consecutive phases were used to improve classification accuracy. These phases are image acquisition, preprocessing, filtering, smoothing, and feature extraction. To assess the proposed

LA TRANSGRESSION CHEZ RIMBAUD Lecture de I' aspect de Transgression dans Marine