The researcher aims to Diagnose the reality of research variables, strategic leadership and decision support systems, and their impact on crisis management in the General Company for Steel Industries because of their important role in preventing crises and reducing their occurrence for the research company in particular and other companies in general affiliated with the Ministry of Industry and Minerals, as well as clarifying theoretical concepts of research variables As it included the answer to questions related to the research problem, including (Is there an impact of the strategic leadership in managing crises if decision support systems are used), and the researcher adopted the descriptive and analytical approach in its comp

A Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twentyfour samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.

A Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twenty four samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.

Landfill and incineration are the most common and widely used methods to dispose of solid wastes; both of these techniques are considered the main sources of pollution in the world due to the harmful toxic emissions that are considered an environmental problem. Because of the large areas used by landfills, they are not always considered an economical method. With the increase in the production of solid materials, solid wastes increase the pressure on incinerators and landfills, making the environmental pollution hazard more serious. Instead, these waste materials can be used in some other applications. One of the most important of these applications is asphalt pavements, which are the most used types of pavements in the

Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twentyfour samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.

The impact of a Schiff base namely 2-((thiophen-2-ylmethylene)amino)benzenethiol  to corrode mild steel in 1 M HCl  resolved was evaluated using different weight loss technique and scanning electron microscopy (SEM).different weight measurements to expand that the 2-((thiophen-2-ylmethylene) amino) benzenethiol  inhibits  the corrosion of mild steel through adsorbing  of  top for mild steel and block the active locality. The inhibitive impacts of 2-((thiophen-2-ylmethylene)amino)benzenethiol  increase with increasing concentration and decrease with increasing temperature. SEM to checking revealed that the alloy surface was quite unaffected and formed protective film on its surface. The investigated

With the increasing demands to use remote sensing approaches, such as aerial photography, satellite imagery, and LiDAR in archaeological applications, there is still a limited number of studies assessing the differences between remote sensing methods in extracting new archaeological finds. Therefore, this work aims to critically compare two types of fine-scale remotely sensed data: LiDAR and an Unmanned Aerial Vehicle (UAV) derived Structure from Motion (SfM) photogrammetry. To achieve this, aerial imagery and airborne LiDAR datasets of Chun Castle were acquired, processed, analyzed, and interpreted. Chun Castle is one of the most remarkable ancient sites in Cornwall County (Southwest England) that had not been surveyed and explored