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

Flow-production systems whose pieces are connected in a row may not have maintenance scheduling procedures fixed because problems occur at different times (electricity plants, cement plants, water desalination plants). Contemporary software and artificial intelligence (AI) technologies are used to fulfill the research objectives by developing a predictive maintenance program. The data of the fifth thermal unit of the power station for the electricity of Al Dora/Baghdad are used in this study. Three stages of research were conducted. First, missing data without temporal sequences were processed. The data were filled using time series hour after hour and the times were filled as system working hours, making the volume of the data relativel

The emphasis of Master Production Scheduling (MPS) or tactic planning is on time and spatial disintegration of the cumulative planning targets and forecasts, along with the provision and forecast of the required resources. This procedure eventually becomes considerably difficult and slow as the number of resources, products and periods considered increases. A number of studies have been carried out to understand these impediments and formulate algorithms to optimise the production planning problem, or more specifically the master production scheduling (MPS) problem. These algorithms include an Evolutionary Algorithm called Genetic Algorithm, a Swarm Intelligence methodology called Gravitational Search Algorithm (GSA), Bat Algorithm (BAT), T

The study investigates the water quality of the Orontes River, which is considered one of the important water recourses in Syria, as it is used for drinking, irrigation, swimming and industrial needs. A database of 660 measurements for 13 parameters concentrations used, were taken from 11 monitoring points distributed along the Orontes River for a period of five years from 2015-2019, and to study the correlation between parameters and their impact on water quality, statistical analysis was applied using (SPSS) program. Cluster analysis was applied in order to classify the pollution areas along the river, and two groups were given: (low pollution - high pollution), where the areas were classified according to the sources of pollution to w

The study aims to build a water quality index that fits the Iraqi aquatic systems and reflects the environmental reality of Iraqi water. The developed Iraqi Water Quality Index (IQWQI) includes physical and chemical components. To build the IQWQI, Delphi method was used to communicate with local and global experts in water quality indices for their opinion regarding the best and most important parameter we can use in building the index and the established weight of each parameter. From the data obtained in this study, 70% were used for building the model and 30% for evaluating the model. Multiple scenarios were applied to the model inputs to study the effects of increasing parameters. The model was built 4 by 4 until it reached 17 parame

This study presents an adaptive control scheme based on synergetic control theory for suppressing the vibration of building structures due to earthquake. The control key for the proposed controller is based on a magneto-rheological (MR) damper, which supports the building. According to Lyapunov-based stability analysis, an adaptive synergetic control (ASC) strategy was established under variation of the stiffness and viscosity coefficients in the vibrated building. The control and adaptive laws of the ASC were developed to ensure the stability of the controlled structure. The proposed controller addresses the suppression problem of a single-degree-of-freedom (SDOF) building model, and an earthquake control scenario was conducted and simulat

Magnetic levitation (Maglev) systems are employed in a wide range of applications and are therefore of significant practical importance, which has led to growing research interest. This paper presents the design of a terminal synergetic control (TSC) and feedback linearization-based proportional-integral-derivative plus second-order derivative (FL-PIDD2) controller for the Maglev system. For developing the control law of both controllers, the mathematical model of the Maglev system is converted into a canonical system where the expression of the nonlinearity is displayed in the last differential dynamic equation of the system. The determination of the TSC and FL-PIDD2 gains for achieving the desired dynamic response is carried out using the

The flexible joint robot (FJR) typically experiences parametric variations, nonlinearities, underactuation, noise propagation, and external disturbances which seriously degrade the FJR tracking. This article proposes an adaptive integral sliding mode controller (AISMC) based on a singular perturbation method and two state observers for the FJR to achieve high performance. First, the underactuated FJR is modeled into two simple second-order fast and slow subsystems by using Olfati transformation and singular perturbation method, which handles underactuation while reducing noise amplification. Then, the AISMC is proposed to effectively accomplish the desired tracking performance, in which the integral sliding surface is designed to reduce cha