The purpose of this research is to investigate the impact of corrosive environment (corrosive ferric chloride of 1, 2, 5, 6% wt. at room temperature), immersion period of (48, 72, 96, 120, 144 hours), and surface roughness on pitting corrosion characteristics and use the data to build an artificial neural network and test its ability to predict the depth and intensity of pitting corrosion in a variety of conditions. Pit density and depth were calculated using a pitting corrosion test on carbon steel (C-4130). Pitting corrosion experimental tests were used to develop artificial neural network (ANN) models for predicting pitting corrosion characteristics. It was found that artificial neural network models were shown to be

Artificial Intelligence Algorithms have been used in recent years in many scientific fields. We suggest employing artificial TABU algorithm to find the best estimate of the semi-parametric regression function with measurement errors in the explanatory variables and the dependent variable, where measurement errors appear frequently in fields such as sport, chemistry, biological sciences, medicine, and epidemiological studies, rather than an exact measurement.

The Iraqi marshes are considered the most extensive wetland ecosystem in the Middle East and are located in the middle and lower basin of the Tigris and Euphrates Rivers which create a wetlands network and comprise some shallow freshwater lakes that seasonally swamped floodplains. Al-Hawizeh marsh is a major marsh located east of Tigris River south of Iraq. This study aims to assess water quality through water quality index (WQI) and predict Total Dissolved Solids (TDS) concentrations in Al-Hawizeh marsh based on artificial neural network (ANN). Results showed that the WQI was more than 300 for years 2013 and 2014 (Water is unsuitable for drinking) and decreased within the range 200-300 in years 2015 and 2016 (Very poor water). The develope

The Iraqi marshes are considered the most extensive wetland ecosystem in the Middle East and are located in the middle and lower basin of the Tigris and Euphrates Rivers which create a wetlands network and comprise some shallow freshwater lakes that seasonally swamped floodplains. Al-Hawizeh marsh is a major marsh located east of Tigris River south of Iraq. This study aims to assess water quality through water quality index (WQI) and predict Total Dissolved Solids (TDS) concentrations in Al-Hawizeh marsh based on artificial neural network (ANN). Results showed that the WQI was more than 300 for years 2013 and 2014 (Water is unsuitable for drinking) and decreased within the range 200-300 in years 2015 and 2016 (Very poor water). The

This research was conduct to evaluate the cytotoxic effect of exotoxin A (ETA) produced by Pseudomonas aeruginosa on mice in comparison with (phosphate buffer saline (PBS) as a negative control. The effect of the toxin was measured by employing the cytogenetic analysis which included (the mitotic index (MI), chromosomal aberrations (CAs), micronucleus (MN) and sperm abnormalities) parameters. In order to specify the cytotoxic effect of the toxin, three doses of ETA (125, 250 and 500 ng/ml) were used. Results showed that ETA was found to cause a significant decrease in mitotic index (MI) percentage, while significant increase in micronucleus (MN), chromosomal aberrations (CAs) and sperm abnormalities parameters in compression with control wa

Background: Opportunistic viral infections make an important threat to renal transplantation recipients (RTRs), and with the use of more intense newly-developed immunosuppressive drugs; the risk of renal allograft loss due to reactivation of these viruses has increased considerably. At the top priority of these viruses lie BK polyomavirus (BKV) and human cytomegalovirus (CMV). Reactivation of these viruses in these chronically immunosuppressed RTRs can lead to renal impairment and subsequently allograft loss, unless early detected and properly treated. Objectives: The study aimed to detect and quantify plasma viral load of BKV and CMV in RTRs using quantitative real time PCR (qRT-PCR), in order to study the prevalence of these two viruses i

In this paper, an algorithm is suggested to train a single layer feedforward neural network to function as a heteroassociative memory. This algorithm enhances the ability of the memory to recall the stored patterns when partially described noisy inputs patterns are presented. The algorithm relies on adapting the standard delta rule by introducing new terms, first order term and second order term to it. Results show that the heteroassociative neural network trained with this algorithm perfectly recalls the desired stored pattern when 1.6% and 3.2% special partially described noisy inputs patterns are presented.