The application of pultruded (GFRP) composite has become increasingly prominent in civil infrastructure projects. This study provides a comprehensive analysis of experimental and numerical studies conducted on the mechanical characteristics of (GFRP) composites across various temperature conditions, encompassing ambient and fire scenarios. The compilation comprises over 100 scholarly articles that examine the mechanical behavior of (GFRP) materials, specifically emphasizing their tensile and compressive strengths, showed the mechanical properties of (GFRP) materials are commonly compromised when exposed to high temperatures that approach or surpass the resin's glass transition temperature (Tg). In contrast, temperatures that are low

General Background: Deep image matting is a fundamental task in computer vision, enabling precise foreground extraction from complex backgrounds, with applications in augmented reality, computer graphics, and video processing. Specific Background: Despite advancements in deep learning-based methods, preserving fine details such as hair and transparency remains a challenge. Knowledge Gap: Existing approaches struggle with accuracy and efficiency, necessitating novel techniques to enhance matting precision. Aims: This study integrates deep learning with fusion techniques to improve alpha matte estimation, proposing a lightweight U-Net model incorporating color-space fusion and preprocessing. Results: Experiments using the AdobeComposition-1k

In this study, the effect of fire flame on the punching shear strength of steel fiber reinforced concrete flat plates was experimentally investigated using nine half-scale specimens with dimensions of 1500×1500 mm and a total thickness of 100 mm. The main investigated variables comprised the steel fiber volume fraction 0, 1, and 1.5% and the burning steady state temperature 500 and 600 °C. The specimens were divided into three groups, each group consists of three specimens. The specimens in the first group were tested with no fire effect to be the reference specimens, while the others of the second and third groups were tested after being exposed to fire-flame effect. The adopted characteristics of the fire test were; (one hour) b

Convection heat transfer in a horizontal channel provided with metal foam blocks of two numbers of pores per unit of length (10 and 40 PPI) and partially heated at a constant heat flux is experimentally investigated with air as the working fluid. A series of experiments have been carried out under steady state condition. The experimental investigations cover the Reynolds number range from 638 to 2168, heat fluxes varied from 453 to 4462 W/m², and Darcy number 1.77x10^-5, 3.95x10^-6. The measured data were collected and analyzed. Results show that the wall temperatures at each heated section are affected by the imposed heat flux variation, Darcy number, and Reynolds number variation. The var

The aim of this work is to enhance the mechanical properties of the glass ionomer cement GIC (dental materials) by adding Zirconium Oxide ZrO₂ in both micro and nano particles. GIC were mixed with (3, 5 and 7) wt% of both ZrO₂ micro and nanoparticles separately. Compressive strength (CS), biaxial flexural strength (BFS), Vickers Microhardness (VH) and wear rate losses (WR) were investigated. The maximum compression strength was 122.31 MPa with 5 wt. % ZrO₂ micro particle, while 3wt% nanoparticles give highest Microhardness and biaxial flexural strength of 88.8 VHN and 35.79 MPa respectively. The minimum wear rate losses were 3.776µg/m with 7 wt. % ZrO₂ nanoparticle. GIC-contai

Speech enhancement aims to improve speech quality and intelligibility in noisy environments and is important in applications such as hearing aids, mobile communications and automatic speech recognition (ASR). This paper shows a structured review of speech enhancement techniques, classified depending on the channel configuration and signal processing framework. Both traditional and modern approaches are discussed, including classical signal processing methods, machine learning techniques, and recent deep learning-based models. Furthermore, common noise types, widely used speech datasets, and standard evaluation metrics for evaluating speech quality and intelligibility are reviewed. Key challenges such as non-stationary noise, data li

Background This study establishes a mathematically consistent and computational framework for the simultaneous identification of two time-dependent coefficients in a one-dimensional second-order parabolic partial differential equation. The considered problem is governed by nonlocal initial, boundary, and integral overdetermination conditions. Methods The direct problem is solved using the Crank-Nicolson finite difference method (FDM), which ensures unconditional stability and second-order accuracy in both spatial and temporal discretizations. The corresponding inverse problem is reformulated as a nonlinear regularized least-squares optimization problem and efficiently solved used the MATLAB subroutine

A condense study was done to compare between the ordinary estimators. In particular the maximum likelihood estimator and the robust estimator, to estimate the parameters of the mixed model of order one, namely ARMA(1,1) model.

Simulation study was done for a varieties the model.  using: small, moderate and large sample sizes, were some new results were obtained. MAPE was used as a statistical criterion for comparison.