In the present work, the feasibility of formation near-ideal ohmic behavior of In/n-Si contact efficiently by 300 s duration Nd:YAG pulsed laser processing has been recognized. Several laser pulses energy densities have been used, and the optimal energy density that gives best results is obtained. Topography of the irradiated region was extensively discussed and supported with micrographic illustrations to determine the surface condition that can play the important role in the ohmic contact quality. I-V characteristics in the forward and reverse bias and barrier height measurements have been studied for different irradiated samples to determine the laser energy density that gives best ohmic behavior. Comparing the current results with

This paper present a study about effect of the random phase and expansion of the scale sampling factors to improve the monochrome image hologram and compared it with previous produced others. Matlab software is used to synthesize and reconstruction hologram.

Many consumers of electric power have excesses in their electric power consumptions that exceed the permissible limit by the electrical power distribution stations, and then we proposed a validation approach that works intelligently by applying machine learning (ML) technology to teach electrical consumers how to properly consume without wasting energy expended. The validation approach is one of a large combination of intelligent processes related to energy consumption which is called the efficient energy consumption management (EECM) approaches, and it connected with the internet of things (IoT) technology to be linked to Google Firebase Cloud where a utility center used to check whether the consumption of the efficient energy is s

In this paper the nuclear structure of some of Si-isotopes namely, ^28,32,36,40Si have been studied by calculating the static ground state properties of these isotopes such as charge, proton, neutron and mass densities together with their associated rms radii, neutron skin thicknesses, binding energies, and charge form factors. In performing these investigations, the Skyrme-Hartree-Fock method has been used with different parameterizations; SkM*, S1, S3, SkM, and SkX. The effects of these different parameterizations on the above mentioned properties of the selected isotopes have also been studied so as to specify which of these parameterizations achieves the best agreement between calculated and experimental data. It can be ded

The toxic lead additives to gasoline are no longer used in many countries around the world. Many other countries are now phasing out the lead in gasoline. Although the lead fuel is still in use in Iraq, several plans are considered to phase out the lead. The use of organic compounds to replace the lead additives in gasoline is considered now as an option in Iraqi refineries. The main objective of this project was preparation of premium gasoline, by blending of gasoline with Alternative additives (alcohol, aromatic) to enhancing octane number of Al-Doura gasoline pool. Improved gasoline was tested by ASTM standard method which includes octane number measuring by CFR engine analyzer. Gasoline pool RON (80) was used and selective components

Soil stabilization with stone powder is a good solution for the construction of subgrade for road way and railway lines, especially under the platforms and mostly in transition zones between embankments and rigid structures, where the mechanical properties of supporting soils are very influential. Stone powder often has a unique composition which justifies the need for research to study the feasibility of using this stone powder type for ground improvement applications. This paper presents results from a comprehensive laboratory study carried out to investigate the feasibility of using stone powder for improvement of engineering properties of clays.

The stone powder contains bassanite (CaSO₄. ½ H

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