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

This study investigates the performance of granular dead anaerobic sludge (GDAS) bio-sorbent as permeable reactive barrier in removing phenol from a simulated contaminated shallow groundwater. Batch tests have been performed to characterize the equilibrium sorption properties of the GDAS and sandy soil in phenol-containing aqueous solutions. The results of GDAS tests proved that the best values of operating parameters, which achieve the maximum removal efficiency of phenol (=85%), at equilibrium contact time (=3 hr), initial pH of the solution (=5), initial phenol concentration (=50 mg/l), GDAS dosage (=0.5 g/100 ml), and agitation speed (=250 rpm). Fourier transform infrared (FTIR) analysis proved that the carboxylic acid, aromatic, alk

The friendly-environment geophysical methods are commonly used in various engineering and near-surface environmental investigations. Electrical Resistivity Imaging technique was used to investigate the subsurface rocks, sediments properties of a proposed industrial site to characterize the lateral and vertical lithological changes. via the electrical resistivity, to give an overview about the karst, weak and robust subsoil zones. Nineteen 2D ERI profiles using Wenner array with 2 m electrode spacing have been applied to investigate the specific industry area. One of these profiles has been conducted with one-meter electrode spacing. The surveyed profiles are divided into a number of blocks, each block consists of several parallel pr

Feature selection (FS) constitutes a series of processes used to decide which relevant features/attributes to include and which irrelevant features to exclude for predictive modeling. It is a crucial task that aids machine learning classifiers in reducing error rates, computation time, overfitting, and improving classification accuracy. It has demonstrated its efficacy in myriads of domains, ranging from its use for text classification (TC), text mining, and image recognition. While there are many traditional FS methods, recent research efforts have been devoted to applying metaheuristic algorithms as FS techniques for the TC task. However, there are few literature reviews concerning TC. Therefore, a comprehensive overview was systematicall

Objective: The study aimed to 1) measure the prevalence of depression and anxiety among Iraqi pharmacy and medical students at a number of universities in Baghdad using Hospital Anxiety and Depression Scale (HADS) and 2) investigate the association between various sociodemographic factors and students’ HADS scores. Methods: This study was based on a cross-sectional descriptive design in four universities in Baghdad, Iraq. Depression and anxiety were screened using an Arabic version of the HADS. An online survey was administered via Qualtrics to convenience samples of students at four colleges of pharmacy and a college of medicine between March and June 2018. Multiple linear regression was used to identify factors associated

The world is keeping pace with evolution in all its fields as a result of scientists' pursuit of continuous scientific and technological development. This evolution included the sports field, which had a large space in the aspect of development and for all disciplines, Therefore, it's reflected today in what we see of records and advanced achievements in sporting events and activities. The development in the field of sports was the result of scientific research (Hussein and Jawad., 2022), where the interest in the training process has become one of the most important pillars of the development of achievement (Neamah and Altay., 2020). The shooting sport has also witnessed a remarkable development due to the diversity and development of its

The research aimed to modeling a structural equation for tourist attraction factors in Asir Region. The research population is the people in the region, and a simple random sample of 332 individuals were selected. The factor analysis as a reliable statistical method in this phenomenon was used to modeling and testing the structural model of tourism, and analyzing the data by using SPSS and AMOS statistical computerized programs. The study reached a number of results, the most important of them are: the tourist attraction factors model consists of five factors which explain 69.3% of the total variance. These are: the provision of tourist services, social and historic factors, mountains, weather and natural parks. And the differenc