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Iraqi Sentiment and Emotion Analysis Using Deep Learning
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Analyzing sentiment and emotions in Arabic texts on social networking sites has gained wide interest from researchers. It has been an active research topic in recent years due to its importance in analyzing reviewers' opinions. The Iraqi dialect is one of the Arabic dialects used in social networking sites, characterized by its complexity and, therefore, the difficulty of analyzing sentiment. This work presents a hybrid deep learning model consisting of a Convolution Neural Network (CNN) and the Gated Recurrent Units (GRU) to analyze sentiment and emotions in Iraqi texts. Three Iraqi datasets (Iraqi Arab Emotions Data Set (IAEDS), Annotated Corpus of Mesopotamian-Iraqi Dialect (ACMID), and Iraqi Arabic Dataset (IAD)) collected from Facebook are used to evaluate the model. Experiments showed that the model obtained good results, as the accuracy of the model was 91.1, 92.4, and 92.5% for IADS, ACMID, and IAD, respectively. The results of the model outperformed previous works for all datasets.

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Publication Date
Sun Dec 31 2017
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Study and Analysis of Concentric Shell and Double Tube Heat Exchanger Using Tio2 Nanofluid
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In this paper, nanofluid of TiO2/water of concentrations of 0.002% and 0.004% volume was used. This nanofluid was flowing through heat exchanger of shell and concentric double tubes with counter current flow to the hot oil. The thermal conductivity of nanofluid is enhanced with increasing concentrations of the TiO2, this increment was by 19% and 16.5% for 0.004% and 0.002% volume respectively relative to the base fluid (water). Also the heat transfer coefficient of the nanofluid is increased as Reynold's number and nanofluid concentrations increased too. The heat transfer coefficient is increased by 66% and 49% for 0.004% and 0.002% volume respectively relative to the base fluid. This study showed that the friction

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Publication Date
Fri Feb 28 2025
Journal Name
International Journal Of Intelligent Engineering And Systems
MCNet: Mask Cell of Multi Class Deep Network for Blood Cells Detection and Classification
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Physicians are likely to expend significant labor and time while manually calculating blood smears. Automatic computer-based methods for classifying acute lymphoblastic leukemia have trouble correctly lighting stained white blood cell microscopy images and accurately separating cells that touch or overlap. Additionally, incorporating machine learning techniques into medical services is very hard because doctors can deal with rough guesses as long as the results aren't too bad, but they can't use these calculations for actual medical care. Enabling a A deep network having knowledge of the accuracy of its own predictions is a fascinating and crucial issue. Most instances segmentation frameworks weigh the mask quality during the instance

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Publication Date
Mon Feb 14 2022
Journal Name
Journal Of Educational And Psychological Researches
E-Learning (Benefits and management systems)
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E-learning seeks to create an interactive learning environment between the teacher and the learner through electronic media conveying in more than one direction, regardless of how the environment and its variables are identified. It also develops skills necessary to deal with technology in order to be able to take into account the individual differences between them and helps e-learning teacher and learner to achieve the goals set in advance and identify educational objectives in a clear manner. The research aims to identify e-learning in its benefits and management systems. It has three sections dealt with in the current research. Chapter II concentrates on the research Methodology, which consisted of three sections: The first s

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Publication Date
Mon Oct 30 2023
Journal Name
Aro-the Scientific Journal Of Koya University
Enhancing Upper Limb Prosthetic Control in Amputees Using Non-invasive EEG and EMG Signals with Machine Learning Techniques
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Amputation of the upper limb significantly hinders the ability of patients to perform activities of daily living. To address this challenge, this paper introduces a novel approach that combines non-invasive methods, specifically Electroencephalography (EEG) and Electromyography (EMG) signals, with advanced machine learning techniques to recognize upper limb movements. The objective is to improve the control and functionality of prosthetic upper limbs through effective pattern recognition. The proposed methodology involves the fusion of EMG and EEG signals, which are processed using time-frequency domain feature extraction techniques. This enables the classification of seven distinct hand and wrist movements. The experiments conducte

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Publication Date
Tue Aug 19 2025
Journal Name
Scientific Reports
Predictive modeling of asthma drug properties using machine learning and topological indices in a MATLAB based QSPR study
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Publication Date
Wed Feb 01 2023
Journal Name
Baghdad Science Journal
Breast Cancer MRI Classification Based on Fractional Entropy Image Enhancement and Deep Feature Extraction
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Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature

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Publication Date
Mon Dec 15 2025
Journal Name
Amecj
Rapid analysis and separation of fifteen beta-lactam drugs using reversed-phase high-performance liquid chromatography
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Beta-lactam medications are among the commonly used antibiotics. These drugs kill germs by disrupting cell wall formation. This drug treats bacterial infections in numerous body sections. A new, quick, high-performance liquid chromatography approach has been developed and verified by the FDA and EMA for the simultaneous estimation of drugs in their medicinal and pure forms. This study deals with the determination of beta-lactam drugs (Amoxicillin, Ampicillin, Cephalexin, Cefotaxime, Cefoxitin, Cefamandole, Cephalothin, Piperacillin, Penicillin, Oxacillin, Cloxacillin, Nafcillin, Carbenicillin, Mezlocillin, Dicloxacillin) by a Reversed-Phase High-Performance Liquid Chromatography (RP-HPLC) technique based on an UV detector using a

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Publication Date
Wed Nov 08 2023
Journal Name
Technologies And Materials For Renewable Energy, Environment, And Sustainability: Tmrees23fr
Analysis of x-ray diffraction lines of cuprous oxide nanoparticles by using variance analysis method
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In this study, the results of x-ray diffraction methods were used to determine the Crystallite size and Lattice strain of Cu2O nanoparticles then to compare the results obtained by using variance analysis method, Scherrer method and Williamson-Hall method. The results of these methods of the same powder which is cuprous oxide, using equations during the determination the crystallite size and lattice strain, It was found that the results obtained the values of the crystallite size (28.302nm) and the lattice strain (0.03541) of the variance analysis method respectively and for the Williamson-Hall method were the results of the crystallite size (21.678nm) and lattice strain (0.00317) respectively, and Scherrer method which gives the value of c

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Publication Date
Fri Oct 02 2026
Journal Name
Journal Of Physical Education
The Effect of Special Exercises Using with Assisting Aids According to Differentiated Learning (Visual Learners) in Learning Crescent Kick in Fighters of Specialized Taekwondo schools
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Publication Date
Sat Feb 01 2025
Journal Name
Chemistryselect
Synthesis of Polypyrrole‐Graphene Oxide (PPy/GO) from Deep Eutectic Solvent and Its Characterization for Determination of Metronidazole Pharmaceutical Substance Using Spectrofluorometric Technique
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Abstract<p> A polypyrrole‐graphene oxide (PPy/GO) nanocomposite was made chemically using a polymerization method in deep eutectic solvents made up of choline chloride and propionic acid in a 1:2 molar ratio. The purpose of this study is to examine the feasibility and efficacy of PPy/GO nanocomposite in the detection of metronidazole in pharmaceutical formulations utilizing spectrofluorometric techniques. Characterization of the synthesized PPy/GO nanocomposite was conducted using several methods such as transmission electron microscopy (TEM), scanning electron microscopy (SEM), Fourier‐transform infrared spectroscopy (FTIR), thermal gravimetric analysis (TGA), and X</p> ... Show More
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