In this study three inorganic nano additives, namely; CaCO3, Al2O3 and SiO2 were used to prepare nanocomposites of unsaturated polyester in order to modify their mechanical properties, i.e. tensile strength, elongation, impact and hardness. The results indicated that all the three additives were effective to improve the mechanical properties up to 4% by weight. The effectiveness of them follows the order : CaCO3 > Al2O3 > SiO2 This is due to their particle size in which CaCO3 (13nm), Al2O3 (20-30nm) and SiO2 (15-20nm).

This study aims to use claystone beds exposed in the Injana Formation (Late Miocene) at Karbala-Najaf plateau, middle of Iraq for the manufacturing of perforated and ordinary bricks. The claystone samples were assessed as an alternative material of the recent sediments, which are preferred to remain as agricultural land. The claystones are sandy mud composing of 29.1 - 39.1% clay, 37.2 - 54.8% silt and 14.1-26.8% sand. They consist of kaolinite, illite, chlorite, palygorskite, and montmorillonite with a lot of quartz, calcite, dolomite, gypsum and feldspar. Claystone samples were characterized by linear shrinkage 0.01 - 0.1%, volume shrinkage 0.1 - 0.9%, bulk density 1.2 - 2.11gm/cm3 (1.68 g / cm3 average), and the efflorescence is

Membrane distillation (MD) is a hopeful desalination technique for brine (salty) water. In this research, Direct Contact Membrane Distillation (DCMD) and  Air Gap Membrane Distillation (AGMD) will be used. The sample used is from Shat Al –Arab water (TDS=2430 mg/l). A polyvinylidene fluoride (PVDF) flat sheet membrane was used as a flat sheet form with a plate and frame cell. Several parameters were studied, such as; operation time, feed temperature, permeate temperature, feed flow rate. The results showed that with time, the flux decreases because of the accumulated fouling and scaling on the membrane surface. Feed temperature and feed flow rate had a positive effect on the permeate flux, while permeate temperatu

     The bound radial wave functions of Cosh potential which are the solutions to the radial part of Schrodinger equation are solved numerically and used to compute the size radii; i.e., the root-mean square proton, neutron, charge and matter radii, ground density distributions and elastic electron scattering charge form factors for nitrogen isotopes 14,16,18,20,22N. The parameters of such potential for the isotopes under study have been opted so as to regenerate the experimental last single nucleon binding energies on Fermi's level and available experimental size radii as well.

The analysis of the root cause techniques is a reasonable option to be made to assess the root causes of the funding of construction projects. There are a variety of issues related to financing in construction industries in Iraq. The root,cause analysis is the impact of security and social conditions on financial funding. Variety tools of root cause analysis have originated from literature, as common methods for the detection of root causes. The purpose of this study was to identify and diagnose causes that lead to obstruction of financial funding in the construction projects in the republic of Iraq from the contractors' point of view and their interaction with a number of variables. The study diagnosed nine causes of fi

The successful implementation of deep learning nets opens up possibilities for various applications in viticulture, including disease detection, plant health monitoring, and grapevine variety identification. With the progressive advancements in the domain of deep learning, further advancements and refinements in the models and datasets can be expected, potentially leading to even more accurate and efficient classification systems for grapevine leaves and beyond. Overall, this research provides valuable insights into the potential of deep learning for agricultural applications and paves the way for future studies in this domain. This work employs a convolutional neural network (CNN)-based architecture to perform grapevine leaf image classifi

Wellbore instability and sand production onset modeling are very affected by Sonic Shear Wave Time (SSW). In any field, SSW is not available for all wells due to the high cost of measuring. Many authors developed empirical correlations using information from selected worldwide fields for SSW prediction. Recently, researchers have used different Artificial Intelligence methods for estimating SSW. Three existing empirical correlations of Carroll, Freund, and Brocher are used to estimate SSW in this paper, while a fourth new empirical correlation is established. For comparing with the empirical correlation results, another study's Artificial Neural Network (ANN) was used. The same data t