Hot mix recycling of asphalt pavements is increasingly being used as one of the major rehabilitation methods by various highway agencies. Besides general savings in costs and energy expended, it also saves our natural resources and environment.  Recycling process presents a sustainable pavement by using the old materials that could be reclaimed from the pavement; these materials could be mixed with recycling agents to produce recycled mixtures. The important expected benefits of recycling process are the conservation of natural resources and reduction of environmental impact. The primary objectives of this work are evaluating the Tensile and Shear Properties of recycled asphalt concrete mixtures, In addition to the

in this paper copper oxide (cuO thin films were prepared by the method of vacum thermal evaporation a pressure.

     This work is devoted to define new generalized gamma and beta functions involving the recently suggested seven-parameter Mittag-Leffler function, followed by a review of all related special cases. In addition, necessary investigations are affirmed for the new generalized beta function, including, Mellin transform, differential formulas, integral representations, and essential summation relations. Furthermore, crucial statistical application has been realized for the new generalized beta function.  

Silver sulfide and the thin films Ag2Se0.8Te0.2 and Ag2Se0.8S0.2 created by the thermal evaporation process on glass with a thickness of 350 nm were examined for their structural and optical properties. These films were made at a temperature of 300 K. According to the X-ray diffraction investigation, the films are polycrystalline and have an initial orthorhombic phase. Using X-ray diffraction research, the crystallization orientations of Ag2Se and Ag2Se0.8Te0.2 & Ag2Se0.8S0.2 (23.304, 49.91) were discovered (XRD). As (Ag2Se and Ag2Se0.8Te0.2 & Ag2Se0.8S0.2) absorption coefficient fell from (470-774) nm, the optical band gap increased (2.15 & 2 & 2.25eV). For instance, the characteristics of thin films made of Ag2Se0.8Te0.2 and Ag2Se0.8S0.2

This article reviews the construction of organic solar cell (OSC) and characterized their optical and electrical properties, where indium tin oxide (ITO) used as a transparent electrode, “Poly (3-hexylthiophene- 2,5-diyl) P3HT / Poly (9,9-dioctylfluorene-alt-benzothiadiazole) F8BT” as an active layer and “Poly(3,4-ethylenedioxythiophene)-poly (styrene sulfonate)” PEDOT: PSS which is referred to the hole transport layer. Spin coating technique was used to prepared polymers thin film layers under ambient atmosphere to make OSC.  The prepared samples were characterized after annealing process at (80 ͦ C) for (30 min) under non-isolated circumference. The results show a value of filling factor (FF) of (2.888), (0.233) and (0.28

      In this research, carbon nanotubes (CNTs) is prepared  through the Hummers method with a slight change in some of the work steps, thus, a new method has been created for preparing carbon nanotubes which is similar to the original Hummers method that is used to prepare graphene oxide. Then, the suspension carbon nanotubes is transferred to a simple electrode position platform consisting of two electrodes and the cell body for the coating and reduction of the carbon nanotubes on ITO glass which represents the cathode electrode while platinum represents the anode electrode. The deposited layer of carbon nanotubes is examined through the scanning electron microscope technique (SEM), and the images throughout the research show the

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.

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

The complexity and variety of language included in policy and academic documents make the automatic classification of research papers based on the United Nations Sustainable Development Goals (SDGs) somewhat difficult. Using both pre-trained and contextual word embeddings to increase semantic understanding, this study presents a complete deep learning pipeline combining Bidirectional Long Short-Term Memory (BiLSTM) and Convolutional Neural Network (CNN) architectures which aims primarily to improve the comprehensibility and accuracy of SDG text classification, thereby enabling more effective policy monitoring and research evaluation. Successful document representation via Global Vector (GloVe), Bidirectional Encoder Representations from Tra