Global warming and environmental damage have become major problems. The production of Portland cement releases large quantities of gas, which cause pollution to the atmosphere. This problem can be solved via the use of sustainable materials, such as glass powder. This study investigates the effect of partial replacement of cement with sustainable glass powder at various percentages (0, 15, 20, and 25%) by weight of cement on some mechanical properties (compressive strength, flexural strength, absorption, and dry density) of Reactive Powder Concrete (RPC) containing a percentage of Polypropylene fibers (PRPC) of 1% by weight. Furthermore, steam curing was performed for 5 hours at 90oC after hardening the sample directly. The RPC was

Expansive soil is one of the most serious problems that face engineers during the execution of any infrastructure projects. Soil stabilization using chemical admixture is one of the most traditional and widespread methods of soil improvement. Nevertheless, soil improvement on site is one of the most economical solutions for many engineering applications. Using construction and demolishing waste in soil stabilization is still under research., The aim of this study is to identify the effect of using concrete demolishing waste (CDW) in soil stabilization. Serious tests were conducted to investigate the changes in the geotechnical properties of the natural soil stabilized with CDW. From the results, it is concluded that the

Face Recognition Systems (FRS) are increasingly targeted by morphing attacks, where facial features of multiple individuals are blended into a synthetic image to deceive biometric verification. This paper proposes an enhanced Siamese Neural Network (SNN)-based system for robust morph detection. The methodology involves four stages. First, a dataset of real and morphed images is generated using StyleGAN, producing high-quality facial images. Second, facial regions are extracted using Faster Region-based Convolutional Neural Networks (R-CNN) to isolate relevant features and eliminate background noise. Third, a Local Binary Pattern-Convolutional Neural Network (LBP-CNN) is used to build a baseline FRS and assess its susceptibility to d

This research aimed to predict the permanent deformation (rutting) in conventional and rubberized asphalt mixes under repeated load conditions using the Finite Element Method (FEM). A three-dimensional (3D) model was developed to simulate the Wheel Track Testing (WTT) loading. The study was conducted using the Abaqus/Standard finite element software. The pavement slab was simulated using a nonlinear creep (time-hardening) model at 40°C. The responses of the viscoplastic model under the influence of the trapezoidal amplitude of moving wheel loadings were determined for different speeds and numbers of cycles. The results indicated that a wheel speed increase from 0.5Km/h to 1.0Km/h decreased the rut depth by about 22% and 24% in conv

The growing demand for sustainable and high-performance asphalt binders has prompted the exploration of waste-derived modifiers. This study investigates the performance enhancement of Natural Asphalt (NA) using Sugarcane Molasses (SM) and Waste Engine Oil (WEO). The modified blends were prepared by partially replacing 50 % NA with varying proportions of SM and WEO ranging from 10 % to 40 % of the total weight of NA. Comprehensive testing was conducted, including penetration, softening point, ductility, viscosity, Bending Beam Rheometer (BBR), Multiple Stress Creep Recovery (MSCR), Energy Dispersive X-ray Spectroscopy (EDX), Fourier Transform Infrared (FTIR) spectroscopy, and Scanning Electron Microscopy (SEM). The results demonstrated that

Investigation of the adsorption of acid fuchsin dye (AFD) on Zeolite 5A is carried out using batch scale experiments according to statistical design. Adsorption isotherms, kinetics and thermodynamics were demonstrated.  Results showed that the maximum removal efficiency was using zeolite at a temperature of 93.68751 mg/g. Experimental data was found to fit the Langmuir isotherm and pseudo second order kinetics with maximum  removal of about 95%.  Thermodynamic analysis showed an endothermic adsorption. Optimization was made for the most affecting operating variables and a model equation for the predicted efficiency was suggested.

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