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A New Proposed Hybrid Learning Approach with Features for Extraction of Image Classification
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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven classifiers. A hybrid supervised learning system that takes advantage of rich intermediate features extracted from deep learning compared to traditional feature extraction to boost classification accuracy and parameters is suggested. They provide the same set of characteristics to discover and verify which classifier yields the best classification with our new proposed approach of “hybrid learning.” To achieve this, the performance of classifiers was assessed depending on a genuine dataset that was taken by our camera system. The simulation results show that the support vector machine (SVM) has a mean square error of 0.011, a total accuracy ratio of 98.80%, and an F1 score of 0.99. Moreover, the results show that the LR classifier has a mean square error of 0.035 and a total ratio of 96.42%, and an F1 score of 0.96 comes in the second place. The ANN classifier has a mean square error of 0.047 and a total ratio of 95.23%, and an F1 score of 0.94 comes in the third place. Furthermore, RF, WKNN, DT, and NB with a mean square error and an F1 score advance to the next stage with accuracy ratios of 91.66%, 90.47%, 79.76%, and 75%, respectively. As a result, the main contribution is the enhancement of the classification performance parameters with images of varying brightness and clarity using the proposed hybrid learning approach.

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Publication Date
Sun Jun 30 2024
Journal Name
Modern Sport
Evaluating the Effectiveness of Using the Kinesthetic Teaching Style by Basketball Instructors in Practical Lessons from the Students' Perspective
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Advancements and modernizations introduced into the educational and pedagogical systems have significantly impacted teaching processes and how subjects are presented and explained to students. The focus has shifted to how learners interact with the material they need to learn, providing sufficient opportunities for learning and granting them freedom and self-confidence to achieve learning objectives. The research problem stems from the researcher's experience as a lecturer in the College of Physical Education and Sports Science, particularly in teaching basketball. She observed that some instructors were deficient in using the most effective teaching methods. The researcher formulated her research question based on these observations: "What

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Publication Date
Tue Nov 01 2022
Journal Name
Inorganic Chemistry Communications
Sustainable adsorptive removal of high concentration organic contaminants from water using biodegradable Gum-Acacia integrated magnetite nanoparticles hydrogel adsorbent
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Release of industrial effluents comprising dyes in water bodies is one of the foremost causes of water pollution. Therefore, the proper and proficient treatment of these dyes contaminated left-over material before their release is crucial. Herein, an eco-friendly biological macromolecule Gum-Acacia (GA) integrated Fe3O4 nanoparticles composite hydrogel was manufactured via co-precipitation technique for effective adsorption of Congo red (CR) dye existing in water bodies. The as-prepared magnetic GA/Fe3O4 composite hydrogel was characterized by FTIR, XRD, EDX, VSM, SEM, and BET techniques. These studies discovered the fruitful fabrication of biodegradable magnetic GA/Fe3O4 composite hydrogel possessing porous structure with large surface are

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Publication Date
Sun Jul 30 2023
Journal Name
Iraqi Journal Of Science
Ameliorative Potentials of Quercetin in Some Histo-Physiological and Biochemical Parameters Against Alterations Induced Benzene Inhalation in Albino Rats
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     Present study investigates the protective role of quercetin in reducing benzene-induced toxicity in rats. Sixteen adult rats, weighing 200-250 g, were selected. They were divided into four groups: 1. Control group, 2. Benzene inhaled group, 3. Quercetin group and 4. Group of benzene and quercetin in combination. Biochemical, spermatological parameters, and histopathological changes in lungs were recorded. Results of aspartate aminotransferase (AST), alanine aminotransferase (ALT), alkaline phosphatase (ALP), urea and creatinine levels in the serum of rats were higher in benzene exposed rats than in unexposed rats. Conversely, exposure to benzene led to a decrease in sperm quality compared to the unexposed rats. Histopathological

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Publication Date
Mon May 01 2017
Journal Name
The Journal Of Immunology
Protective effects of Δ9-Tetrahydrocannabinol (THC) results from alteration in lung dysbiosis mediated by SEB-induced acute lung injury
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Abstract<p>Inhalation of Staphylococcal Enterotoxin B (SEB) is known to induce acute lung injury (ALI) and studies from our laboratory have shown that THC, a psychoactive ingredient found in Cannabis sativa, can attenuate the ALI. In the current study, we investigated the role played by lung microbiota in ALI with or without THC treatment. A dual-dose of SEB was given to C3H/HeJ mice, which were then treated either with vehicle or THC. SEB-administration caused ALI and 100% mortality while all THC-treated mice survived and suppressed the inflammation in the lungs. Furthermore, lung microbiota was collected and 16S rRNA sequencing was performed. The data were analyzed to determine the alpha and b</p> ... Show More
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Publication Date
Thu Jul 20 2023
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Theoretical Analysis Of The Photon Production Rate in the Quark-Gluon Interaction According To The Quantum Cromodynamic QCD Theory
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           In this work, we have used the QCD dynamic scenario of the quark gluon interaction to investigate and study photon emission theoretically based on quantum theory. The QCD theory is implemented by deriving the photon emission rate equation of the state of ideal QGP at a  chemical potential. The photon rate of the quark-gluon interaction has to be calculated for the anti up-gluon interaction in the g →  γ system at the temperature of system  with critical temperature ( 132.38, ,  and 198.57) MeV and photon energy (  GeV. We investigated a significant effect of critical temperature, strength coupling, and photon energy on the photon rate contribution. Here, the increased photon emission rate and decreased streng

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Publication Date
Fri Jun 18 2021
Journal Name
International Journal Of Emerging Technologies In Learning (ijet)
The Effectiveness of Educational Pillars Based on Vygotsky's Theory in Achievement and Information Processing Among First Intermediate Class Students
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The aim of the research is to identify the effectiveness of the educational pillars strategy based on Vygotsky's theory in mathematical achievement and information processing of first-grade intermediate students. In pursuit of the research objectives, the experimental method was used, and the quasi-experimental design was used for two equivalent groups, one control group taught traditionally and the other experi-mental taught according to the educational pillars strategy. The research sample consisted of (66) female students from the first intermediate grade, who were inten-tionally chosen after ensuring their equivalence, taking into account several factors, most notably chronological age and their level of mathematics, and they we

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Publication Date
Fri Dec 06 2019
Journal Name
Ssociation Of Arab Universities Journal Of Engineering Sciences
Application of Artificial Neural Network and GeographicalInformation System Models to Predict and Evaluate the Quality ofDiyala River Water, Iraq
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This research discusses application Artificial Neural Network (ANN) and Geographical InformationSystem (GIS) models on water quality of Diyala River using Water Quality Index (WQI). Fourteen water parameterswere used for estimating WQI: pH, Temperature, Dissolved Oxygen, Orthophosphate, Nitrate, Calcium, Magnesium,Total Hardness, Sodium, Sulphate, Chloride, Total Dissolved Solids, Electrical Conductivity and Total Alkalinity.These parameters were provided from the Water Resources Ministryfrom seven stations along the river for the period2011 to 2016. The results of WQI analysis revealed that Diyala River is good to poor at the north of Diyala provincewhile it is poor to very polluted at the south of Baghdad City. The selected parameters wer

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Publication Date
Thu Dec 15 2022
Journal Name
Journal Of Petroleum Research And Studies
Selection of an Optimum Drilling Fluid Model to Enhance Mud Hydraulic System Using Neural Networks in Iraqi Oil Field
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In drilling processes, the rheological properties pointed to the nature of the run-off and the composition of the drilling mud. Drilling mud performance can be assessed for solving the problems of the hole cleaning, fluid management, and hydraulics controls. The rheology factors are typically termed through the following parameters: Yield Point (Yp) and Plastic Viscosity (μp). The relation of (YP/ μp) is used for measuring of levelling for flow. High YP/ μp percentages are responsible for well cuttings transportation through laminar flow. The adequate values of (YP/ μp) are between 0 to 1 for the rheological models which used in drilling. This is what appeared in most of the models that were used in this study. The pressure loss

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Publication Date
Wed Nov 11 2020
Journal Name
Journal Of Research In Medical And Dental Science
Effect of Topical Melatonin Application on the Peri-Implant Proximal Bone Level and Cortical Plate Thickness (Pilot Clinical Trial)
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Publication Date
Wed Apr 01 2020
Journal Name
Biochemical & Cellular Archives
SYNTHESIS, CHARACTERIZATION, ANTIOXIDANT, ANTICANCER HUMAN STUDIES AND BIOLOGICAL ACTIVITY OF MIXED LIGAND COMPLEXES USING SCHIFF BASE LIGAND AND HISTIDINE.
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الوصف Mixed ligand complexes of Cu (II), Co (II) and Zn (II) with 2-((4-(1-(4-chlorophenylimino) ethyl) phenylimino) methyl) phenol (L) and histidine (His) have been prepared and diagnosed by ¹H and13 C NMR, FT-IR and electronic spectral data, thermal gravimetric, molar conductance and metal analysis measurements. The ligand (L) shows a bidentate nature and the coordination occurs through N and O atoms of imine group and phenol group respectively whereas (His) behave as tridentate ligand, coordinating through the-NH2 group and carboxylate oxygen group and N atoms of imidazole ring. The analytical studies for three complexes have shown octahedral structure. The anticancer activity was screened against human cancer cell such Follicular

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