The quality of drinking water is considered among the most urgent issues worldwide nowadays. Ensuring safe water for human consumption remains the highest priority, while challenges also persist in meeting the water quality needs for industrial and agricultural uses. Most of the relevant studies lack accuracy in assessing water quality. Therefore, this study aims to forecast the quality of drinking water along the Tigris River in Iraq following a new approach. A developed forecasting model that utilizes the gravitational search algorithm (GSA) was deployed. The heuristic optimization tool was utilized for the prediction of the water quality index (WQI) in the research area. Out of twelve water stations, 575 samples were gather

Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d

Electromechanical actuators are used in a wide variety of aerospace applications such as missiles, aircrafts and spy-fly etc. In this work a linear and nonlinear fin actuator mathematical model has been developed and its response is investigated by developing an algorithm for the system using MATLAB. The algorithm used to the linear model is the state space algorithm while the algorithm used to the nonlinear model is the discrete algorithm. The huge moment constant is varied from (-3000 to 3000) and the damping ratio is varied from (0.4 to 0.8).        

 The comparison between linear and nonlinear fin actuator response results shows that for linear model, the maximum overshoot is about 10%,

   Due to their recalcitrant characteristics, Azo dyes such as methyl orange (MO) are extremely poisonous substances, making their removal from textile industry wastewater a major problem. By employing various EC-Adsorption combined system configurations and reusing alum sludge as an adsorbent, the current study seeks to investigate the efficiency of these various systems in removing MO dye. To estimate their benefits and limitations, experiments were carried out utilizing nickel foam (NiF) and aluminum plate (Al plate) as anodes, and stainless-steel mesh (SS mesh) as cathode in the presence of alum sludge as an adsorbent in all systems. The EC-Adsorption combined system with NiF as anode and two SS meshes as cathodes with 10 g/L