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A Methodology for Evaluating and Scheduling Preventive Maintenance for a Thermo-Electric Unit Using Artificial Intelligence
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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 relatively high for 2015-2016-2017. 2018 was utilized as a test year to assess the modeling work and validate the experimental results. In the second step, the artificial neural networks approach employs the python program as an AI, and the affinity ratio of real data using the performance measurement of the mean absolute error (MAE) was 0.005. To improve and reduce the value of absolute error, the genetic algorithm uses the python program and the convergence ratio became 0.001. It inferred that the algorithm is efficient in improving results. Thus, the genetic algorithm provided better results with fewer errors than the neural network alone. This concludes that the shown network has superior performance over others and the possibility of its long-term predictions for 2030. A Sing time series helped detect future cases by reading and inferring system data. The development of appropriate work plans will lower internal and external expenses of the systems and help integrate other capabilities by giving correct data sources of raw materials, costs, etc. To facilitate prediction for maintenance workers, an interface has been created that facilitates users to apply them using the python program represented by entering the times, an hour, a day, a month, a year, to predict the type and place of failure.

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Publication Date
Thu Mar 30 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Preventive Effects of Different Doses of Pentoxyfilline Against CCl4-Induced Liver Toxicity in Rats
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The liver protective effects of pentoxifylline were studied through pre-treatment of rats with various intraperitoneal (IP) doses (25, 50 and 100mg/kg/day) 14 days before induction of liver toxicity by carbon tetrachloride (CCl4). The parameters of oxidative stress, malondialdehyde (MDA) and reduced glutathione (GSH) were measured in liver homogenate in addition to histopathological examinations.  Analysis of data revealed significant amelioration of oxidative stress in groups of animals pre-treated with different doses of pentoxifylline (PTX) compared to group of animals intoxicated by CCl4 as evidenced by lowering MDA contents and elevation of GSH levels in liver tissue homogenate but the levels still signifi

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Publication Date
Wed Oct 02 2024
Journal Name
International Development Planning Review
THE EFFECT OF EXERCISES USING A MINI SQUASH COURT ON IMPROVING SOME MOTOR ABILITIES AND LEARNING SOME BASIC SKILLS FOR PLAYERS AGED 10-12 YEARS
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Publication Date
Wed Oct 02 2024
Journal Name
International Development Planning Review
THE EFFECT OF EXERCISES USING A MINI SQUASH COURT ON IMPROVING SOME MOTOR ABILITIES AND LEARNING SOME BASIC SKILLS FOR PLAYERS AGED 10-12 YEARS
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Publication Date
Fri Mar 28 2025
Journal Name
Journal Of Physical Education
Special exercises using tools and their effect on teaching the skill of a front shoulder circle on the rings apparatus in artistic gymnastics for students
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Sports skills in some individual games require physical and motor qualities to facilitate the process of skill performance and also require the instructor or trainer to use more than one strategy, method and way to bring the performance to the level of mastery and avoid injury. The aim of the research is to know the effect of using special exercises using tools and their effect on teaching the skill of a front shoulder circle. The research hypothesis is that using special exercises with tools has a positive effect on teaching the skill of a front shoulder circle on the rings apparatus. Research method: - The researchers used the experimental method by designing two equal groups, the control and the experimental, to suit the research

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Publication Date
Wed Jun 01 2022
Journal Name
Journal Of Sport Science Technology And Physical Activities
The effect of using Daniel's model and Driver’s model in learning a kinetic chain on the uneven bars in the artistic gymnastics for female students
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The aim of this study to identity using Daniel's model and Driver’s model in learning a kinetic chain on the uneven bars in the artistic gymnastics for female students. The researchers used the experimental method to design equivalent groups with a preand post-test, and the research community was identified with the students of the third stage in the college for the academic year 2020-2021 .The subject was, (3) class were randomly selected, so (30) students distributed into (3) groups). has been conducted pretesting after implementation of the curriculum for (4) weeks and used the statistical bag of social sciences(SPSS)to process the results of the research and a set of conclusions was reached, the most important of which is t

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Publication Date
Thu Jan 06 2022
Journal Name
Chemical Papers
A solvent collection technique using dispersive liquid–liquid microextraction coupled with spectrophotometry for the trace determination of folic acid in pure, dosage forms and flaxseed
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A simple, rapid and environmentally friendly dispersive liquid–liquid microextraction method-based spectrophotometric method for the trace determination of folic acid has been developed. The proposed method is based on the formation of a deep yellow product via reaction of folic acid and 1,2-naphthoquine-4-sulfonate at pH = 9. The formed complex was extracted using a mixture of chloroform and ethanol. Then, the tiny organic droplets were measured at λ = 520 nm. At the optimum conditions, linearity was ranged from 0.05 to 1.5 μg/mL for the standard and samples, with a linear correlation coefficient of 0.9996. The detection limits were 0.02, 0.027, 0.03, 0.02 and 0.04 μg/mL for standard, tablet (5 mg), tablet (1 mg), syrup and fl

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Publication Date
Thu Jan 03 2019
Journal Name
International Journal Of Civil Engineering And Technology (ijciet)
Condition Prediction Models of Deteriorated Trunk Sewer Using Multinomial Logistic Regression and Artificial Neural Network
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Sewer systems are used to convey sewage and/or storm water to sewage treatment plants for disposal by a network of buried sewer pipes, gutters, manholes and pits. Unfortunately, the sewer pipe deteriorates with time leading to the collapsing of the pipe with traffic disruption or clogging of the pipe causing flooding and environmental pollution. Thus, the management and maintenance of the buried pipes are important tasks that require information about the changes of the current and future sewer pipes conditions. In this research, the study was carried on in Baghdad, Iraq and two deteriorations model's multinomial logistic regression and neural network deterioration model NNDM are used to predict sewers future conditions. The results of the

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Publication Date
Sun May 01 2022
Journal Name
Journal Of Engineering
Estimating Pitting Corrosion Depth and Density on Carbon Steel (C-4130) using Artificial Neural Networks
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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

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Publication Date
Tue Jul 17 2018
Journal Name
International Journal Of Adaptive Control And Signal Processing
Single channel informed signal separation using artificial-stereophonic mixtures and exemplar-guided matrix factor deconvolution
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Publication Date
Thu Aug 31 2017
Journal Name
Journal Of Engineering
Optimum Dimensions of Hydraulic Structures and Foundation Using Genetic Algorithm coupled with Artificial Neural Network
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      A model using the artificial neural networks and genetic algorithm technique is developed for obtaining optimum dimensions of the foundation length and protections of small hydraulic structures. The procedure involves optimizing an objective function comprising a weighted summation of the state variables. The decision variables considered in the optimization are the upstream and downstream cutoffs lengths and their angles of inclination, the foundation length, and the length of the downstream soil protection. These were obtained for a given maximum difference in head, depth of impervious layer and degree of anisotropy. The optimization carried out is subjected to constraints that ensure a safe structure aga

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