<span>Dust is a common cause of health risks and also a cause of climate change, one of the most threatening problems to humans. In the recent decade, climate change in Iraq, typified by increased droughts and deserts, has generated numerous environmental issues. This study forecasts dust in five central Iraqi districts using machine learning and five regression algorithm supervised learning system framework. It was assessed using an Iraqi meteorological organization and seismology (IMOS) dataset. Simulation results show that the gradient boosting regressor (GBR) has a mean square error of 8.345 and a total accuracy ratio of 91.65%. Moreover, the results show that the decision tree (DT), where the mean square error is 8.965, comes in second place with a gross ratio of 91%. Furthermore, Bayesian ridge (BR), linear regressor (LR), and stochastic gradient descent (SGD), with mean square error and with accuracy ratios of 84.365%, 84.363%, and 79%. As a result, the performance precision of these regression models yields. The interaction framework was designed to be a straightforward tool for working with this paradigm. This model is a valuable tool for establishing strategies to counter the swiftness of climate change in the area under study.</span>
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
... Show MoreMetasurface polarizers are essential optical components in modern integrated optics and play a vital role in many optical applications including Quantum Key Distribution systems in quantum cryptography. However, inverse design of metasurface polarizers with high efficiency depends on the proper prediction of structural dimensions based on required optical response. Deep learning neural networks can efficiently help in the inverse design process, minimizing both time and simulation resources requirements, while better results can be achieved compared to traditional optimization methods. Hereby, utilizing the COMSOL Multiphysics Surrogate model and deep neural networks to design a metasurface grating structure with high extinction rat
... Show MoreThe deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv
... Show MoreMembrane manufacturing system was operated using dry/wet phase inversion process. A sample of hollow fiber membrane was prepared using (17% wt PVC) polyvinyl chloride as membrane material and N, N Dimethylacetamide (DMAC) as solvent in the first run and the second run was made using (DMAC/Acetone) of ratio 3.4 w/w. Scanning electron microscope (SEM) was used to predict the structure and dimensions of hollow fiber membranes prepared. The ultrafiltration experiments were performed using soluble polymeric solute poly ethylene glycol (PEG) of molecular weight (20000 Dalton) 800 ppm solution 25 °C temperature and 1 bar pressure. The experimental results show that pure water permeation increased from 25.7 to 32.2 (L/m2.h.bar) by adding a
... Show MoreForward osmosis (FO) process was applied to concentrate the orange juice. FO relies on the driving force generating from osmotic pressure difference that result from concentration difference between the draw solution (DS) and orange juice as feed solution (FS). This driving force makes the water to transport from orange juice across a semi-permeable membrane to the DS without any energy applied. Thermal and pressure-driven dewatering methods are widely used, but they are prohibitively energy intensive and hence, expensive. Effects of various operating conditions on flux have been investigated. Four types of salts were used in the DS, (NaCl, CaCl2, KCl, and MgSO4) as osmotic agent and the experiments were performed at the concentration of
... Show MoreThe objective of all planning research is to plan for human comfort and safety, and one of the most significant natural dangers to which humans are exposed is earthquake risk; therefore, earthquake risks must be anticipated, and with the advancement of global technology, it is possible to obtain information on earthquake hazards. GIS has been utilized extensively in the field of environmental assessment research due to its high potential, and GIS is a crucial application in seismic risk assessment. This paper examines the methodologies used in recent GIS-based seismic risk studies, their primary environmental impacts on urban areas, and the complexity of the relationship between the applied methodological approaches and the resulting env
... Show MoreThis research aims to distinguish the reef environment from the non-reef environment. The Oligocene-Miocene-succussion in western Iraq was selected as a case study, represented by the reefal limestone facies of the Anah Formation (Late Oligocene) deposited in reef-back reef environments, dolomitic limestone of the Euphrates Formation (Early Miocene) deposited in open sea environments, and gypsiferous marly limestone of the Fatha Formation (Middle Miocene) deposited in a lagoonal environment. The content of the rare earth elements (REEs) (La, Ce, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Er, Ho, Tm, Yb, Lu, and Y) in reef facies appear to be much lower than of those in the non-reef facies. The open sea facies have a low content of REEs due to bein
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