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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
Wed Jan 01 2025
Journal Name
Acta Facultatis Medicae Naissensis
Rhabdomyosarcoma in children in the five-year period in Oncology Unit in a pediatric Teaching Hospital
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Introduction/Aim. Rhabdomyosarcoma (RMS) is the most common soft tissue sarcoma in pediatric population and adolescents. Limited data is available on the characteristics of RMS in Iraqi pediatric patients. The aim of the study was to examine the clinical and histological aspects of RMS in Iraqi children, with a focus on their response to treatment, prognosis, and survival. Methods. A retrospective cohort study was conducted at the Oncology Unit of Children's Welfare Teaching Hospital, Medical City, Baghdad, Iraq and included patients who were newly diagnosed with RMS and received treatment during the period between January 1, 2015, and December 31, 2019. The patients were followed up from the time of diagnosis until October 1, 2020.

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Publication Date
Sat Dec 28 2024
Journal Name
Journal Of Physical Education
The effectiveness of using interactive harmonic exercises in improving the level of some physical and motor abilities and intelligence for students aged (9-10) years
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We discussed the proper preparation, directing, and implementation of physical education lessons, and clarification of the duties that fall upon the physical education teacher in addition to his physical and skill duties, which is the duty of the physical education lesson. The problem of the research lies in the fact that interactive harmonic exercises are not implemented accurately by physical education teachers because they require great experience, exceptional efforts, and accuracy in performance. The research aims to identify the level of some physical and motor abilities and intelligence among students aged (9-10) years, and to know the effect of some harmonic exercises. Interactivity at the level of some physical and motor abi

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Publication Date
Fri Mar 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
Integration The Cost Techniques with Balanced Scorecard for The Purposes of Measuring and Evaluating Performance
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The effective application of the method of measuring and evaluating performance according to the Balanced  Scorecard the need for an information system a comprehensive and integrated for internal and external environment, Which requires the need to develop accounting information system in general and cost management information systems to suit the particular requirements of the environment in terms of the development of modern methods of measurement to include the use of some methods that have proven effective in measuring and evaluating performance.

The research problem in need of management to develop methods of measuring and evaluating performance through the use of both financial measures and non

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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
Proposition of New Ensemble Data-Intelligence Models for Surface Water Quality Prediction
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Publication Date
Sun Dec 01 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Technical requirements for the application of economic intelligence and its impact On the dimensions of strategic success of banks: An applied research on a sample of Iraqi banks private
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This research sheds light on one of the important and vital topics for the banking sectors (technical requirements for the application of economic intelligence) namely by (Hardware, equipment, communication networks, software, databases). And the dimensions of the strategic success of the banks represented by(Customer satisfaction, customer trust, quality of service, growth) In the three Iraqi private banks, namely(Assyria International Investment, Mansour Investment, International Development Investment and Finance). Its implementation is an urgent necessity in order to improve the quality of its banking services to win the satisfaction of its customers and their confidence and then grow to achieve stra

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Publication Date
Sun Dec 30 2018
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of penetration Rate and cost with Artificial Neural Network for Alhafaya Oil Field
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Prediction of penetration rate (ROP) is important process in optimization of drilling due to its crucial role in lowering drilling operation costs. This process has complex nature due to too many interrelated factors that affected the rate of penetration, which make difficult predicting process. This paper shows a new technique of rate of penetration prediction by using artificial neural network technique. A three layers model composed of two hidden layers and output layer has built by using drilling parameters data extracted from mud logging and wire line log for Alhalfaya oil field. These drilling parameters includes mechanical (WOB, RPM), hydraulic (HIS), and travel transit time (DT). Five data set represented five formations gathered

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Publication Date
Tue Jan 01 2019
Journal Name
Spe Europec Featured At 81st Eage Conference And Exhibition
Development of Artificial Neural Networks and Multiple Regression Analysis for Estimating of Formation Permeability
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Publication Date
Tue Dec 31 2024
Journal Name
Iraqi Geological Journal
Geomechanical Modeling and Artificial Neural Network Technique for Predicting Breakout Failure in Nasiriyah Oilfield
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Wellbore instability is one of the major issues observed throughout the drilling operation. Various wellbore instability issues may occur during drilling operations, including tight holes, borehole collapse, stuck pipe, and shale caving. Rock failure criteria are important in geomechanical analysis since they predict shear and tensile failures. A suitable failure criterion must match the rock failure, which a caliper log can detect to estimate the optimal mud weight. Lack of data makes certain wells' caliper logs unavailable. This makes it difficult to validate the performance of each failure criterion. This paper proposes an approach for predicting the breakout zones in the Nasiriyah oil field using an artificial neural network. It

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Publication Date
Mon Jun 30 2025
Journal Name
Infotech Spectrum: Iraqi Journal Of Data Science
Evaluating AI Language Models in News Retrieval: A Comparative Study Of ChatGPT-Plus and DeepSeek (R1)
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The increasing complexity of how humans interact with and process information has demonstrated significant advancements in Natural Language Processing (NLP), transitioning from task-specific architectures to generalized frameworks applicable across multiple tasks. Despite their success, challenges persist in specialized domains such as translation, where instruction tuning may prioritize fluency over accuracy. Against this backdrop, the present study conducts a comparative evaluation of ChatGPT-Plus and DeepSeek (R1) on a high-fidelity bilingual retrieval-and-translation task. A single standardize prompt directs each model to access the Arabic-language news section of the College of Medicine, University of Baghdad, retrieve the three most r

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Analysis of the performance of a fiber optic sensor used to measure the intensity of the electric field
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In this research was conducted to provide a product to analyze the performance sensor fiber optic used to measure and feel the intensity of the electric field results showed obtained that use sensor long gives reactive high electric field strength and a high value for allergic sensor, but that is at the expense of reducing the intensity of the electric field that is detected

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