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Prediction of sediment heavy metal at the Australian Bays using newly developed hybrid artificial intelligence models
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Publication Date
Tue Jul 09 2024
Journal Name
Diagnostics
A Novel Hybrid Machine Learning-Based System Using Deep Learning Techniques and Meta-Heuristic Algorithms for Various Medical Datatypes Classification
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Medicine is one of the fields where the advancement of computer science is making significant progress. Some diseases require an immediate diagnosis in order to improve patient outcomes. The usage of computers in medicine improves precision and accelerates data processing and diagnosis. In order to categorize biological images, hybrid machine learning, a combination of various deep learning approaches, was utilized, and a meta-heuristic algorithm was provided in this research. In addition, two different medical datasets were introduced, one covering the magnetic resonance imaging (MRI) of brain tumors and the other dealing with chest X-rays (CXRs) of COVID-19. These datasets were introduced to the combination network that contained deep lea

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Publication Date
Sun Jun 08 2025
Journal Name
J Nat Sc Biol Med
The Value of White Blood Cells and Platelets Indices in Prediction of Tubal Ectopic Pregnancy Rupture
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Publication Date
Sun Jun 08 2025
Journal Name
Journal Of Natural Science, Biology And Medicine
The Value of White Blood Cells and Platelets Indices in Prediction of Tubal Ectopic Pregnancy Rupture
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Publication Date
Wed Mar 29 2023
Journal Name
Materials
Prediction of the Bending Strength of a Composite Steel Beam–Slab Member Filled with Recycled Concrete
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This study investigated the structural behavior of a beam–slab member fabricated using a steel C-Purlins beam carrying a profile steel sheet slab covered by a dry board sheet filled with recycled aggregate concrete, called a CBPDS member. This concept was developed to reduce the cost and self-weight of the composite beam–slab system; it replaces the hot-rolled steel I-beam with a steel C-Purlins section, which is easier to fabricate and weighs less. For this purpose, six full-scale CBPDS specimens were tested under four-point static bending. This study investigated the effect of using double C-Purlins beams face-to-face as connected or separated sections and the effect of using concrete material that contains different recycled

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Publication Date
Wed Dec 01 2021
Journal Name
Journal Of Economics And Administrative Sciences
The Effect of Using Information and Communication Technology to Improving the Quality of Blended Learning Elements’, a Survey Study at the Technical College of Management /Baghdad
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 The research has been based on two main variables (information and communication technology) and the quality of blended education (physical and electronic), aiming to reveal the relationship between four dimensions (physical devices, software, databases, communication networks) and the elements of education represented by (the teacher, the student, the teaching process, curriculum).  The methodology and post-analysis-based research were conducted at the Technical College of Management / Baghdad through polling the opinions of a random sample that included (80) teachers out of (86) and the number of students (276) representing a random sample from all departments of the college (for the morning study) out of (3500) stud

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Publication Date
Sat Feb 09 2019
Journal Name
Journal Of The College Of Education For Women
Hybrid Transform Based Denoising with Block Thresholding
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A frequently used approach for denoising is the shrinkage of coefficients of the noisy signal representation in a transform domain. This paper proposes an algorithm based on hybrid transform (stationary wavelet transform proceeding by slantlet transform); The slantlet transform is applied to the approximation subband of the stationary wavelet transform. BlockShrink thresholding technique is applied to the hybrid transform coefficients. This technique can decide the optimal block size and thresholding for every wavelet subband by risk estimate (SURE). The proposed algorithm was executed by using MATLAB R2010aminimizing Stein’s unbiased with natural images contaminated by white Gaussian noise. Numerical results show that our algorithm co

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Publication Date
Thu Aug 01 2019
Journal Name
International Journal Of Machine Learning And Computing
Emotion Recognition System Based on Hybrid Techniques
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Emotion recognition has important applications in human-computer interaction. Various sources such as facial expressions and speech have been considered for interpreting human emotions. The aim of this paper is to develop an emotion recognition system from facial expressions and speech using a hybrid of machine-learning algorithms in order to enhance the overall performance of human computer communication. For facial emotion recognition, a deep convolutional neural network is used for feature extraction and classification, whereas for speech emotion recognition, the zero-crossing rate, mean, standard deviation and mel frequency cepstral coefficient features are extracted. The extracted features are then fed to a random forest classifier. In

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Publication Date
Wed Jun 01 2022
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Plasmonic hybrid terahertz photomixer of graphene nanoantenna and nanowires
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Due to their attractive properties, silver nanowires (Ag-NWs) are newly used as nanoelectrodes in continuous wave (CW) THz photomixer. However, since these nanowires have small contact area, the nanowires fill factor in the photomixer active region is low, which leads to reduce the nanowires conductivity. In this work, we proposed to add graphene nanoantenna array as nanoelectrodes to the silver nanowires-based photomixer to improve the conductivity. In addition, the graphene nanoantenna array and the silver nanowires form new hybrid nanoelectrodes for the CW-THz photomixer leading to improve the device conversion efficiency by the plasmonic effect. Two types of graphene nanoantenna array are proposed in two separate photomixer conf

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Publication Date
Mon May 19 2025
Journal Name
Retos
The effect of the cube model on visual-spatial intelligence and learning the skill of spiking in volleyball for female students
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Objective: To identify the effect of the cube model on visual-spatial intelligence and learning the skill of spikinging in volleyball for female students, The researchers used the experimental method by designing two equivalent groups with pre- and post-measurements. Research methodology: The main research sample of (30) female students was selected from the research community represented by second-stage students in the College of Physical Education and Sports Sciences - University of Baghdad for the academic year (2024-2025). The sample was divided equally into two control and experimental groups. The researchers conducted the sample homogenization process and the equivalence process between the two groups in the variables of visua

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Publication Date
Sun Jun 09 2024
Journal Name
2024 Ieee 52nd Photovoltaic Specialist Conference (pvsc)
Exploring the Capacitance-Voltage Response of Metal Halide Perovskite Solar Cells
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