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Evaluating the Performance and Behavior of CNN, LSTM, and GRU for Classification and Prediction Tasks
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     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning models for a variety of tasks under the control of a unified architecture for each proposed model.

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Publication Date
Mon Jul 06 2026
Journal Name
Bionanoscience
Effect of Magnesium Oxide Nanoparticles on the Structural, Thermal, and Mechanical Performance of Cured Epoxy Nanocomposites
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This work analyzes the impact of MgO nanoparticles on the properties of an epoxy resin solution with uniform structure and particular degree of cure synthesized by the reaction of epoxy resin and pyromellitic dianhydride. Various concentrations of epoxy/MgO nanocomposites were fabricated by mechanical mixing, ultrasonication-based dispersion and casting processes. FTIR results have shown clear differences in the vibrations of C-H, epoxide rings, and main amine N-H groups. This confirms the interaction between MgO particles and the epoxy polymer matrix. X-ray diffraction analysis detected prominent peak at 18.35 degrees, along with additional ones at 43.44 degrees and 62.56 degrees, associated with the (200) and (220) planes of MgO crystal,

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Publication Date
Sat Jan 13 2024
Journal Name
Journal Of Advanced Research In Fluid Mechanics And Thermal Sciences
Influence of Surrounding Air Temperature and Humidity upon the Performance of a Gas Turbine Power Plant
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Nowadays, energy demand continuously rises while energy stocks are dwindling. Using current resources more effectively is crucial for the world. A wide method to effectively utilize energy is to generate electricity using thermal gas turbines (GT). One of the most important problems that gas turbines suffer from is high ambient air temperature especially in summer. The current paper details the effects of ambient conditions on the performance of a gas turbine through energy audits taking into account the influence of ambient conditions on the specific heat capacity ( , isentropic exponent ( ) as well as the gas constant of air . A computer program was developed to examine the operation of a power plant at various ambient temperature

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Publication Date
Sat Mar 01 2025
Journal Name
Results In Engineering
Advancing asphalt binder performance through nanomaterial and polymer modification: Experimental and statistical insights
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Publication Date
Tue Mar 30 2021
Journal Name
Journal Of Economics And Administrative Sciences
Employing the indicators of stereotypes and the dimensions of organizational clarity and their role in achieving the planned organizational behavior Analytical study on a sample of workers in some departments of the Faculties of Engineering, University of
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The current research examines the employment of indicators of stereotypes and the dimensions of organizational clarification to achieve planned organizational behaviour on a sample of employees in a number of departments of the Faculties of Engineering, University of Kufa, for a sample of (122) teaching staff. This research proposes the use of positive indicators of stereotypes for both the organization and employees and their awareness of what they want to obtain and what should be done for both parties and the removal of organizational clarity represented by the functional dimension that explores to what degree the employee's understanding of the internal strategy of the organization and the strategic dimension that searches fo

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Publication Date
Thu Nov 02 2023
Journal Name
Journal Of Engineering
Verification and Parametric Analysis of Shear Behavior of Reinforced Concrete Beams using Non-linear Finite Element Analysis
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Many researchers have tackled the shear behavior of Reinforced Concrete (RC) beams by using different kinds of strengthening in the shear regions and steel fibers. In the current paper, the effect of multiple parameters, such as using one percentage of Steel Fibers (SF) with and without stirrups, without stirrups and steel fibers, on the shear behavior of RC beams, has been studied and compared by using Finite Element analysis (FE). Three-dimensional (3D) models of (RC) beams are developed and analyzed using ABAQUS commercial software. The models were validated by comparing their results with the experimental test. The total number of beams that were modeled for validation purposes was four. Extensive pa

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Publication Date
Wed Dec 01 2021
Journal Name
Journal Of Physics: Conference Series
A comparison and classification of land use land cover to estimate their effect on environment: case study in Baghdad city
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Abstract<p>This study compared and classified of land use and land cover changes by using Remote Sensing (RS) and Geographic Information Systems (GIS) on two cities (Al-Saydiya city and Al-Hurriya) in Baghdad province, capital of Iraq. In this study, Landsat satellite image for 2020 were used for (Land Use/Land Cover) classification. The change in the size of the surface area of each class in the Al-Saydiya city and Al-Hurriya cities was also calculated to estimate their effect on environment. The major change identified, in the study, was in agricultural area in Al-Saydiya city compare with Al-Hurriya city in Baghdad province. The results of the research showed that the percentage of the green </p> ... Show More
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Publication Date
Sun Apr 04 2010
Journal Name
Journal Of Educational And Psychological Researches
Translation & Adaptation of(Patterns) & (Assembly) Scales of The Flanagan Aptitude Classification Tests (FACT)
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The Flanagan Aptitude Classification Tests (FACT) assesses aptitudes that are important for successful performance of particular job-related tasks. An individual's aptitude can then be matched to the job tasks. The FACT helps to determine the tasks in which a person has proficiency. Each test measures a specific skill that is important for particular occupations. The FACT battery is designed to provide measures of an individual's aptitude for each of 16 job elements.

The FACT consists of 16 tests used to measure aptitudes that are important for the successful performance of many occupational tasks. The tests provide a broad basis for predicting success in various occupational fields. All are paper and pen

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Publication Date
Thu Nov 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Total Quality Management and Its Role in the Development of Financial Performance "Reality and Obstacles" (Case Study on Diyala State Company)
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           This research aims to identify and measure the role of TQM in the process of developing  the financial  performance of  Diyala State Company and show the reality and obstacles, after applying the company's management to the requirements of ISO 9001: 2008 and compare it with its performance before applying this standard, The researcher measured the financial performance by conducting financial analysis of the financial statements and conducting a number of interviews at the company's headquarters, Diyala State Company (one of the Iraqi Ministry of Industry and Minerals formations) was sele

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Publication Date
Sun Jan 01 2023
Journal Name
International Journal Of Data And Network Science
The effects of big data, artificial intelligence, and business intelligence on e-learning and business performance: Evidence from Jordanian telecommunication firms
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This study sought to investigate the impacts of big data, artificial intelligence (AI), and business intelligence (BI) on Firms' e-learning and business performance at Jordanian telecommunications industry. After the samples were checked, a total of 269 were collected. All of the information gathered throughout the investigation was analyzed using the PLS software. The results show a network of interconnections can improve both e-learning and corporate effectiveness. This research concluded that the integration of big data, AI, and BI has a positive impact on e-learning infrastructure development and organizational efficiency. The findings indicate that big data has a positive and direct impact on business performance, including Big

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Publication Date
Tue Dec 27 2022
Journal Name
2022 3rd Information Technology To Enhance E-learning And Other Application (it-ela)
Diabetes Prediction Using Machine Learning
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Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att

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