As a result of the development and global openness and the possibility of companies providing their services outside their spatial boundaries that were determined by them, and the transformation of the world due to the development of the means of communication into a large global market that accommodates all products from different regions and of the same type and production field, competition resulted between companies, and the race to obtain the largest market share It ensures the largest amount of profits, and it is natural for the advertising promotion by companies for their product to shift from an advertisement for one product to a competitive advertisement that calls on the recipient to leave the competing product and switch to it

This research utilized natural asphalt (NA) deposits from sulfur springs in western Iraq. Laboratory tests were conducted to evaluate the performance of an asphalt mixture incorporating NA and verify its suitability for local pavement applications. To achieve this, a combination of two types of NA, namely soft SNA and hard HNA, was blended to create a binder known as Type HSNA. The resulting HSNA exhibited a penetration grade that adhered to Iraqi specifications. Various percentages of NA (20%, 40%, 60%, and 80%) were added to petroleum asphalt. The findings revealed enhanced physical properties of HSNA, which also satisfied the requirements outlined in the Iraqi specifications for asphalt cement.

Consequently, HS

This paper is concerned with the numerical solutions of the vorticity transport equation (VTE) in two-dimensional space with homogenous Dirichlet boundary conditions. Namely, for this problem, the Crank-Nicolson finite difference equation is derived.  In addition, the consistency and stability of the Crank-Nicolson method are studied. Moreover, a numerical experiment is considered to study the convergence of the Crank-Nicolson scheme and to visualize the discrete graphs for the vorticity and stream functions. The analytical result shows that the proposed scheme is consistent, whereas the numerical results show that the solutions are stable with small space-steps and at any time levels.

Micro-perforated panel (MPP) absorber is increasingly gaining popularity as an alternative sound absorber in buildings compared to the well-known synthetic porous materials. A single MPP has a typical feature of a Helmholtz resonator with a high amplitude of absorption but a narrow absorption frequency bandwidth. To improve the bandwidth, a single MPP can be cascaded with another single MPP to form a double-layer MPP. This paper proposes the introduction of inhomogeneous perforation in the double-layer MPP system (DL-iMPP) to enhance the absorption bandwidth of a double-layer MPP. Mathematical models are proposed using the equivalent electrical circuit model and are validated with experiments with good agreement. It is revealed that the DL-

Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

Flexible joint robot (FJR) manipulators can offer many attractive features over rigid manipulators, including light weight, safe operation, and high power efficiency. However, the tracking control of the FJR is challenging due to its inherent problems, such as underactuation, coupling, nonlinearities, uncertainties, and unknown external disturbances. In this article, a terminal sliding mode control (TSMC) is proposed for the FJR system to guarantee the finite-time convergence of the systems output, and to achieve the total robustness against the lumped disturbance and estimation error. By using two coordinate transformations, the FJR dynamics is turned into a canonical form. A cascaded finite-time sliding mode observer (CFTSMO) is construct

Robot manipulator is a multi-input multi-output system with high complex nonlinear dynamics, requiring an advanced controller in order to track a specific trajectory. In this work, forward and inverse kinematics are presented based on Denavit Hartenberg notation to convert the end effector planned path from cartesian space to joint space and vice versa where a cubic spline interpolation is used for trajectory segments to ensure the continuity in velocity and acceleration.  Also, the derived mathematical dynamic model is based on Eular Lagrange energy method to contain the effect of friction and disturbance torques beside the inertia and Coriolis effect. Two types of controller are applied ; the nonlinear computed torque control (CTC

Increasing the power conversion efficiency (PCE) of silicon solar cells by improving their junction properties or minimizing light reflection losses remains a major challenge. Extensive studies were carried out in order to develop an effective antireflection coating for monocrystalline solar cells. Here we report on the preparation of a nanostructured cerium oxide thin film by pulsed laser deposition (PLD) as an antireflection coating for silicon solar cell. The structural, optical, and electrical properties of a cerium oxide nanostructure film are investigated as a function of the number of laser pulses. The X-ray diffraction results reveal that the deposited cerium oxide films are crystalline in nature and have a cubic fluorite. The field

Detection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with