Al-Chibayish Marsh (CM) is considered as the major part of Central Marshes area of this marsh is 1050 Km². The water quality of these marshes is suffering from salt accumulation due to intensive dam construction, limited supply of water from sources, climate change impacts, and the absence of outlet flow from these marshes, specifically at low flow periods. So, the current research aims to assess and improve these marshes' hydraulic behavior and water quality and define the best location for outlet drains. Field measurements and laboratory tests were conducted for two periods (November 2020 and February 2021) to define the (TDS) concentrations at nine different locations. Samples were also examined for water's physical and chemical properties as pH, electrical conductivity, water temperature, dissolved oxygen, and turbidity. Simultaneously with the sampling process, the water depths were measured at 50 different locations within the marshes. Moreover, the observations of water quality parameters were analyzed for the previous ten years (2010-2020). Hydrodynamic and water quality simulations were conducted using (SMS-RMA2 and RMA4) software to specify the water depths and velocity variations and define the salt content distribution. The obtained results illustrated 4sediment and TDS and in the Central Marshes area in general and CM in specific. As well, numerical results showed that the use of these outlets would significantly improve water quality. The current outlets do not work, and they link the Euphrates River to the Chabayish Marsh.
This study investigates the effectiveness of mental games in enhancing shooting accuracy among young basketball players. Initially, baseline shooting accuracy was assessed through tests conducted prior to a three-week intervention involving mental games. A follow-up test revealed a significant improvement in participants' shooting accuracy following the intervention. Given the noticeable differences in the new shooting scores compared to the initial assessments, a second set of pre-intervention tests was conducted. These tests reaffirmed the significant enhancement in shooting accuracy, substantiating the hypothesis that mental games positively affect performance. The findings highlight the importance of these intervention programs
... Show MoreEco-friendly concrete is produced using the waste of many industries. It reduces the fears concerning energy utilization, raw materials, and mass-produced cost of common concrete. Several stress-strain models documented in the literature can be utilized to estimate the ultimate strength of concrete components reinforced with fibers. Unfortunately, there is a lack of data on how non-metallic fibers, such as polypropylene (PP), affect the properties of concrete, especially eco-friendly concrete. This study presents a novel approach to modeling the stress-strain behavior of eco-friendly polypropylene fiber-reinforced concrete (PFRC) using meta-heuristic particle swarm optimization (PSO) employing 26 PFRC various mixtures. The cement was partia
... Show MoreDuring COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
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