For the duration of the last few many years many improvement in computer technology, software program programming and application production had been followed with the aid of diverse engineering disciplines. Those trends are on the whole focusing on synthetic intelligence strategies. Therefore, a number of definitions are supplied, which recognition at the concept of artificial intelligence from exclusive viewpoints. This paper shows current applications of artificial intelligence (AI) that facilitate cost management in civil engineering tasks. An evaluation of the artificial intelligence in its precise partial branches is supplied. These branches or strategies contributed to the creation of a sizable group of fashions s

That researchers in the play Science Find a theatrical form of an experimental creative, and these experiences taken from the innovation space aesthetic dialogue with the receiver, especially since with previous theatrical experience and is an extension of her, because the interactive theater theatrical terms that assume a pattern do from the depth of the relationship between supply playwright and the audience, which alters the receiving skills actually change, and to monitor these differing divided into three classes that include research, methodological framework (Chapter I) and includes, research problem, the importance of research and the need to him, the goal of the research, the limits Find it border, and the theoretical framework

Automation is one of the key systems in modern agriculture, providing potential solutions to the challenges related to the growing world population, demographic shifts, and economic situation. The present article aims to highlight the importance of precision agriculture (PA) and smart agriculture (SA) in increasing agricultural production and the importance of environmental protection in increasing production and reducing traditional production. For this purpose, different types of automation systems in the field of agricultural operations are discussed, as well as smart agriculture technologies including the Internet of Things (IoT), artificial intelligence (AI), machine learning (ML), big data analysis, in addition to agricultural robots,

The rapid rise in the use of artificially generated faces has significantly increased the risk of identity theft in biometric authentication systems. Modern facial recognition technologies are now vulnerable to sophisticated attacks using printed images, replayed videos, and highly realistic 3D masks. This creates an urgent need for advanced, reliable, and mobile-compatible fake face detection systems. Research indicates that while deep learning models have demonstrated strong performance in detecting artificially generated faces, deploying these models on consumer mobile devices remains challenging due to limitations in computing power, memory, privacy, and processing speed. This paper highlights several key challenges: (1) optimiz

This article suggests and explores a three-species food chain model that includes fear effects, refuges depending on predators, and cannibalism at the second level. The Holling type II functional response determines food consumption between stages of the food chain. This study examined the long-term behavior and impacts of the suggested model's essential elements. The model's solution properties were studied. The existence and stability of every probable equilibrium point were examined. The persistence needs of the system have been determined. It was discovered what conditions could lead to local bifurcation at equilibrium points. Appropriate Lyapunov functions are utilized to investigate the overall dynamics of the system. To support the a

Total dissolved solids are at the top of the parameters list of water quality that requires investigations for planning and management, especially for irrigation and drinking purposes. If the quality of water is sufficiently predictable, then appropriate management is possible. In the current study, Multiple Linear Regression (MLR) and Artificial Neural Network (ANN) models were used as indicators of water quality and for the prediction of Total Dissolved Solids (TDS) along the Tigris River, in Baghdad city. To build these models five water parameters were selected from the intakes of four water treatment plants on the Tigris River, for the period between 2013 and 2017. The selected water parameters were Total Dissolved Solids (TDS

This study aimed at comparing the performance of vertical, horizontal and hybrid subsurface flow systems in secondary treatment for the effluent wastewater from the primary basins at Al-Rustumia wastewater treatment plant, Baghdad, Iraq. The treatments were monitored for six weeks while the testsduration were from 4 to 12 September 2018 under continuous wastewater feeding for chemical oxygen demand (COD), total suspended solid (TSS),ammonia-nitrogen(NH₄-N) and phosphate (PO₄-P) in comparison with FAO and USEPA standards for effluent discharge to evaluate the suitability of treated water for irrigation purposes. Among the systems planted with Phragmites Australia, the hybrid subsurface flow system which cons

         The issue of penalized regression model has received considerable critical attention to variable selection. It plays an essential role in dealing with high dimensional data. Arctangent denoted by the Atan penalty has been used in both estimation and variable selection as an efficient method recently. However, the Atan penalty is very sensitive to outliers in response to variables or heavy-tailed error distribution. While the least absolute deviation is a good method to get robustness in regression estimation. The specific objective of this research is to propose a robust Atan estimator from combining these two ideas at once. Simulation experiments and real data applications show that the p

         The issue of penalized regression model has received considerable critical attention to variable selection. It plays an essential role in dealing with high dimensional data. Arctangent denoted by the Atan penalty has been used in both estimation and variable selection as an efficient method recently. However, the Atan penalty is very sensitive to outliers in response to variables or heavy-tailed error distribution. While the least absolute deviation is a good method to get robustness in regression estimation. The specific objective of this research is to propose a robust Atan estimator from combining these two ideas at once. Simulation experiments and real data applications show that the proposed LAD-Atan estimator