Dust storms are typical in arid and semi-arid regions such as the Middle East; the frequency and severity of dust storms have grown dramatically in Iraq in recent years. This paper identifies the dust storm sources in Iraq using remotely sensed data from Meteosat-spinning enhanced visible and infrared imager (SEVIRI) bands. Extracted combined satellite images and simulated frontal dust storm trajectories, using the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model, are used to identify the most influential sources in the Middle East and Iraq. Out of 132 dust storms in Iraq during 2020–2023, the most frequent occurred in the spring and summer. A dust source frequency percentage map (DSFPM) is generated using ArcGIS so

In recent years, the search for economic and environmentally friendly alternatives has become a global necessity to achieve sustainability and preserve raw materials. From this concept, natural bitumen (NB) derived from sulphur springs is now one of the most promising alternative energy resources for many applications, especially in asphalt pavement construction. Its low price and abundance characterise NB since sulphur springs produce thousands of tonnes of NB annually and are used in very limited fields. Two main objectives were adopted for this work. The first objective is to examine the virgin NB properties from five sulphur springs and compare them with petroleum asphalt. The second objective is to enhance NB properties by appl

The field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet

Length of plasma generated by dc gas discharge under different vacuum pressures was studied experimentally. The cylindrical discharge tube of length 2m was evacuated under vacuum pressure range (0.1-0.5) mbar at constant external working dc voltage 1500V. It was found that the plasma length (L) increased exponentially with increasing of background vacuum air pressure. Empirical equation has been obtained between plasma length and gas pressure by using Logistic model of curve fitting. As vacuum pressure increases the plasma length increases due to collisions, ionizations, and diffusions of electrons and ions.

The harmonic oscillator (HO) and Gaussian (GS) wave functions within the binary cluster model (BCM) have been employ to investigate the ground state neutron, proton and matter densities as well as the elastic form factors of two- neutron 6He and 16C halo nuclei. The long tail is a property that is clearly revealed in the density of the neutrons since it is found in halo orbits. The existence of a long tail in the neutron density distributions of 6He and 16C indicating that these nuclei have a neutron halo structure. Moreover, the matter rms radii and the reaction cross section (𝜎𝑅 ) of these nuclei have been calculated using the Glauber model.

Milling process is a common machining operation that is used in the manufacturing of complex surfaces. Machining-induced residual stresses (RS) have a great impact on the performance of machined components and the surface quality in face milling operations with parameter cutting. The properties of engineering material as well as structural components, specifically fatigue life, deformation, impact resistance, corrosion resistance, and brittle fracture, can all be significantly influenced by residual stresses. Accordingly, controlling the distribution of residual stresses is indeed important to protect the piece and avoid failure. Most of the previous works inspected the material properties, tool parameters, or cutting parameters, bu

This work represents the set of measurements of radon and thoron concentrations levels of soil-gas in Al-Kufa city in Iraq using electric Radon meter (RAD-7). Radon and thoron concentration were measured in soil-gas in 20 location for three depth of (50, 100 and 150) cm.
The results show that the emanation rate of radon and thoron gas varied from location to anther, depending on the geological formation. The Radon concentration in soil has been found to vary from (12775±400) Bq/m3 at 150 cm depth in location (sample K2) to (41.45±17) Bq/m3, for depth 150 cm in location (sample K20). The thoron concentration in soil has been found to vary from (198±8.5) Bq/m3 at 150 cm depth in location samples (K1 & K2) to undetected in the mos

Many researchers have tackled the shear behavior of Reinforced Concrete (RC) beams by using different kinds of strengthening in the shear regions and steel fibers. In the current paper, the effect of multiple parameters, such as using one percentage of Steel Fibers (SF) with and without stirrups, without stirrups and steel fibers, on the shear behavior of RC beams, has been studied and compared by using Finite Element analysis (FE). Three-dimensional (3D) models of (RC) beams are developed and analyzed using ABAQUS commercial software. The models were validated by comparing their results with the experimental test. The total number of beams that were modeled for validation purposes was four. Extensive pa