Industrial development has recently increased, including that of plastic industries. Since plastic has a very long analytical life, it will cause environmental pollution, so studies have resorted to reusing recycled waste plastic (sustainable plastic) to produce environmentally friendly concrete (green concrete). In this research, producing environmentally friendly load-bearing concrete masonry units (blocks) was considered where five concrete mixtures were compressed at the blocks producing machine. The cement content reduced from 400 kg/m³ (B-400) to 300 kg/m³ (B-300) then to 200 kg/m³ (B-200). While (B-380) was produced using 380 kg/m³ cement and 20 kg/m³ nano-sil

Material obtained from the demolition of concrete structures and milling of flexible pavements has the highest potential for recyclability. This study aimed to evaluate the performance of hot mix asphalt with the concurrent use of recycled asphalt pavement (RAP) and recycled concrete aggregate (RCA). Contents of RAP and RCA were varied from 0% to 50% by fixing the total recycling materials percentage to 50%. Penetration grade 40/50 virgin binder and waste engine oil (WEO) as rejuvenator were used in the present study. A series of tests, such as Scanning electron microscopy (SEM), Marshall stability, indirect tensile strength test, IDEAL CT, uniaxial compression test, and resilient modulus test, were carried out to assess the performance of

The aim of this study is to propose mathematical expressions for estimation of the flexural strength of plain concrete members from ultrasonic pulse velocity (UPV) measurements. More than two hundred pieces of precast concrete kerb units were subjected to a scheduled test program. The tests were divided into two categories; non-destructive ultrasonic and bending or rupture tests. For each precast unit, direct and indirect (surface) ultrasonic pulses were subjected to the concrete media to measure their travel velocities. The results of the tests were monitored in two graphs so that two mathematical relationships can be drawn. Direct pulse velocity versus the flexural strength was given in the first relationship while the second equation des

The aim of this study is to propose mathematical expressions for estimation of the flexural strength of plain concrete members from ultrasonic pulse velocity (UPV) measurements. More than two hundred
pieces of precast concrete kerb units were subjected to a scheduled test program. The tests were divided into two categories; non-destructive ultrasonic and bending or rupture tests. For each precast unit, direct and indirect (surface) ultrasonic pulses were subjected to the concrete media to measure their travel velocities. The results of the tests were mointered in two graphs so that two mathematical relationships can be drawn. Direct pulse velocity versus the flexural strength was given in the first relationship while the second equati

This paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n

Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye

This paper focuses on developing a self-starting numerical approach that can be used for direct integration of higher-order initial value problems of Ordinary Differential Equations. The method is derived from power series approximation with the resulting equations discretized at the selected grid and off-grid points. The method is applied in a block-by-block approach as a numerical integrator of higher-order initial value problems. The basic properties of the block method are investigated to authenticate its performance and then implemented with some tested experiments to validate the accuracy and convergence of the method.

<span lang="EN-GB">Transmitting the highest capacity throughput over the longest possible distance without any regeneration stage is an important goal of any long-haul optical network system. Accordingly, Polarization-Multiplexed Quadrature Phase-Shift-Keying (PM-QPSK) was introduced lately to achieve high bit-rate with relatively high spectral efficiency. Unfortunately, the required broad bandwidth of PM-QPSK increases the linear and nonlinear impairments in the physical layer of the optical fiber network. Increased attention has been spent to compensate for these impairments in the last years. In this paper, Single Mode Fiber (SMF), single channel, PM-QPSK transceiver was simulated, with a mix of optical and electrical (Digi