This research aims to determine the impact of the dimensions of artificial intelligence (AI) in improving the service quality  (SQ) provided in a sample of Iraqi banks in the public and private sectors and to indicate which sectors are more influential in improving the quality of their services provided to their customers for a random sample of employees and customers, as the banking sector faces major challenges in light of the technical changes in the business environment today, represented by the increased demand for services provided and their rapid development for different age groups of customers, and the security necessity of adopting modern technologies to hack bank accounts, by adopting the descriptive analytical approach

This research aims to clarify the advantages of using the regression method as analytical procedure in the tax audit to reducing the examination cost , time, effort, human and material resources, and represents an applied study in the General Commission of taxes. In order to achieve its objectives the research has used in the theoretical side the descriptive approach (analytical), and in the practical side regression method has been applied to the research sample represented by the soft drinks company that is subject to the tax settlement for the year 2014, where the value of sales has been verified by using the regression method without conductinga comprehensive examination. The most important results of the research indicate that the r

Background: Errors of horizontal condylar inclinations and Bennett angles had largely affected the articulation of teeth and the pathways of cusps. The aim of this study was to estimate and compare between the horizontal condylar (protrusive) angles and Bennett angles of full mouth rehabilitation patients using two different articulator systems. Materials and Methods: Protrusive angles and Bennett angles of 50 adult males and females Iraqi TMD-free full mouth rehabilitation patients were estimated by using two different articulator systems. Arbitrary hinge axis location followed by protrusive angles and Bennett angles, estimation was done by a semiadjustable articulator system. A fully adjustable articulator system was utilized to locate th

   The petroleum industry faces a significant problem in enhanced oil recovery (EOR) from carbonate reservoirs because of their mostly oil-wet character, which restricts hydrocarbon extraction. To better understand how surfactant-polymer techniques can enhance oil recovery, this study investigates the effectiveness of polyvinyl alcohol (PVA) as a stand-alone agent and the function of ionically modified smart water on carbonate properties. The study focuses on its effect on critical parameters essential for effective oil displacement and recovery, such as wettability alteration, interfacial tension, and surface tension (ST) using different brines (smart water). The ability of the polymer PVA to lower interfacial and surface tensi

Nanofluids, liquid suspensions of nanoparticles (NPs) dispersed in deionized (DI) water, brine, or surfactant micelles, have become a promising solution for many industrial applications including enhanced oil recovery (EOR) and carbon geostorage. At ambient conditions, nanoparticles can effectively alter the wettability of the strongly oil-wet rocks to water-wet. However, the reservoir conditions present the greatest challenge for the success of this application at the field scale. In this work, the performance of anionic surfactant-silica nanoparticle formulation on wettability alteration of oil-wet carbonate surface at reservoir conditions was investigated. A high-pressure temperature vessel was used to apply nano-modification of oil-wet

Nanoparticles (NPs) have been suggested for subsurface projects, including enhanced oil recovery (EOR), carbon capture and storage (CCS), and hydrogen storage, due to their small size, high surface energy, controlled surface properties, and significant effects on the underground formation properties. Silica is an excellent NP that efficiently modifies the surface properties of subsurface formations for incremental oil recovery and to derisk carbon and hydrogen leaks. However, the retention of injected NPs in a narrow area near the injection inlet can limit a project’s feasibility. In the present study, hydrophobic (hybrid) NPs were produced via silanization of silica NPs, and the mobility behavior of bare (hydrophilic) and hybrid

Machine learning is considered a powerful technique in many applications such as classification, clustering, recognition and prediction. Deep learning is a modern, vital and superior machine learning that gives stunning performance, especially with huge data. Stock market price prediction is the process of determining the future value of a prospect of a financial instrument traded in the market, to gain a great profit a successful prediction must be conducted, in order to achieve that machine learning is used, in this article, two approaches are proposed to predict the stock market prices and movement using two datasets, the first approach employs two machine learning models (J48 & logistic regression) while the second approach based on rec