This paper investigates an effective computational method (ECM) based on the standard polynomials used to solve some nonlinear initial and boundary value problems appeared in engineering and applied sciences. Moreover, the effective computational methods in this paper were improved by suitable orthogonal base functions, especially the Chebyshev, Bernoulli, and Laguerre polynomials, to obtain novel approximate solutions for some nonlinear problems. These base functions enable the nonlinear problem to be effectively converted into a nonlinear algebraic system of equations, which are then solved using Mathematica®12. The improved effective computational methods (I-ECMs) have been implemented to solve three applications involving nonli

SCADA is the technology that allows the operator to gather data from one or more various facilities and to send control instructions to those facilities.  This paper represents an adaptable and low cost SCADA system for a particular sugar manufacturing process, by using Programmable Logic Controls (Siemens s7-1200, 1214Dc/ Dc/ Rly). The system will control and monitor the laboratory production line chose from sugar industry. The project comprises of two sections the first one is the hardware section that has been designed, and built using components suitable for making it for laboratory purposes, and the second section was the software as the PLC programming, designing the HMI, creating alarms and trending system. The system will ha

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