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Improved thermal and mechanical properties of CdBa2-x SrxCa2Cu3O8+δ superconducting compounds
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Publication Date
Wed Aug 30 2023
Journal Name
Baghdad Science Journal
Comparative Analysis of MFO, GWO and GSO for Classification of Covid-19 Chest X-Ray Images
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Medical images play a crucial role in the classification of various diseases and conditions. One of the imaging modalities is X-rays which provide valuable visual information that helps in the identification and characterization of various medical conditions. Chest radiograph (CXR) images have long been used to examine and monitor numerous lung disorders, such as tuberculosis, pneumonia, atelectasis, and hernia. COVID-19 detection can be accomplished using CXR images as well. COVID-19, a virus that causes infections in the lungs and the airways of the upper respiratory tract, was first discovered in 2019 in Wuhan Province, China, and has since been thought to cause substantial airway damage, badly impacting the lungs of affected persons.

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Publication Date
Sun Aug 21 2022
Journal Name
International Journal Of Health Sciences
Effect of x- ray on the treatment of breast cancer combined with amygdalin and doxorubicin separately
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Background: Radiation therapy has the ability to destroy healthy cells in addition to cancer cells in the area being treated. However, when radiation combines with doxorubicin, it becomes more effective on breast cancer treatment. Objective: This study aims to clarify the effect of X-ray from LINAC combined with amygdalin and doxorubicin on breast cancer treatment, and the possibility of using amygdalin with X-ray instead of doxorubicin for the breast cancer treatment. Method: Two cell lines were used in this study, the first one was MCF-7 cell line and second one was WRL- 68 normal cell line. These cells were preserved in liquid nitrogen, prepared, developed and tested in the (place). The effect of three x-ray doses combined with a

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Publication Date
Mon Dec 30 2024
Journal Name
Modern Sport
Mechanical angle foot during jumping and correct landing method
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This article investigates the relationship between foot angle and jump stability, focusing on minimizing injury risk. Here are the key points: Importance: Understanding foot angle is crucial for improving jump stability, athletic performance, and reducing jump-related injuries like ankle sprains. Ideal Foot Angle: Research suggests a forward foot angle of around 15 degrees might be ideal for many people during jumps. This angle distributes forces evenly across the foot, lowers the center of gravity, and provides more surface area for pushing off the ground. Factors Affecting Ideal Angle: The optimal angle can vary depending on the type of jump (vertical vs. long jump), fitness level, and personal preference. Incorrect Foot Angles: Landing w

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Publication Date
Sat Aug 31 2019
Journal Name
Iraqi Journal Of Physics
The Effect of Laser And Thermal Treatment on the Hardness and Adhesion Force on the Cermet Coating By Thermal Spray Technique
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Ceramic coating compose from a ceramic mixture (MgO, Al2O3) and metall (Al-Ni) were produced by Thermal Spray Technique. The mixed ratio of used materials Al:Ni (50%) and 40% of Al2O3 and 10% MgO. This mixture was spray on a stainless steel substrate of type (316 L) by using thermal spray with flame method and at spraying distances (8, 12, 16 and 20) cm, then the prepared films were treated by laser and thermal treatment. After that performing a hardness and adhesion tests were eximined. The present study shows that the best value of the thermal treatment is 1000 ℃ for 30 mint; the optimum spray distance is 12 cm and most suitable laser is 500 mJ where the microscopic and mechanical character

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Publication Date
Tue Jun 01 2021
Journal Name
Baghdad Science Journal
Improved Image Security in Internet of Thing (IOT) Using Multiple Key AES
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Image is an important digital information that used in many internet of things (IoT) applications such as transport, healthcare, agriculture, military, vehicles and wildlife. etc. Also, any image has very important characteristic such as large size, strong correlation and huge redundancy, therefore, encrypting it by using single key Advanced Encryption Standard (AES) through IoT communication technologies makes it vulnerable to many threats, thus, the pixels that have the same values will be encrypted to another pixels that have same values when they use the same key. The contribution of this work is to increase the security of transferred image. This paper proposed multiple key AES algorithm (MECCAES) to improve the security of the tran

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Publication Date
Tue Mar 01 2022
Journal Name
Journal Of Engineering
Comparison of Seepage Trough Zoned Earth dam Using Improved Light-Textured Soils
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Seepage through earth dams is one of the most popular causes for earth dam collapse due to internal granule movement and seepage transfer. In earthen dams, the core plays a vital function in decreasing seepage through the dam body and lowering the phreatic line. In this research, an alternative soil to the clay soil used in the dam core has been proposed by conducting multiple experiments to test the permeability of silty and sandy soil with different additives materials. Then the selected sandy soil model was used to represent the dam experimentally, employing a permeability device to measure the amount of water that seeps through the dam's body and to represent the seepage line. A numerical model was adopted using Geo-Studio software i

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Publication Date
Wed Jun 16 2021
Journal Name
Cognitive Computation
Deep Transfer Learning for Improved Detection of Keratoconus using Corneal Topographic Maps
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Abstract <p>Clinical keratoconus (KCN) detection is a challenging and time-consuming task. In the diagnosis process, ophthalmologists must revise demographic and clinical ophthalmic examinations. The latter include slit-lamb, corneal topographic maps, and Pentacam indices (PI). We propose an Ensemble of Deep Transfer Learning (EDTL) based on corneal topographic maps. We consider four pretrained networks, SqueezeNet (SqN), AlexNet (AN), ShuffleNet (SfN), and MobileNet-v2 (MN), and fine-tune them on a dataset of KCN and normal cases, each including four topographic maps. We also consider a PI classifier. Then, our EDTL method combines the output probabilities of each of the five classifiers to obtain a decision b</p> ... Show More
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Publication Date
Wed May 10 2023
Journal Name
Diagnostics
A Deep Feature Fusion of Improved Suspected Keratoconus Detection with Deep Learning
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Detection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with

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Publication Date
Sun Oct 12 2025
Journal Name
Sustainability
Titanium Dioxide for Improved Performance of Reclaimed Asphalt Pavement Aggregates in Concrete
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This work presents an innovative approach to enhancing the performance of concrete with reclaimed asphalt pavement (RAP) aggregates using titanium dioxide (TiO2) nanoparticles. Traditional limestone coarse aggregates were partially replaced with 30% and 50% RAP aggregates; a subset of mixtures containing RAP aggregates was treated with TiO2 nanoparticles. The rheological, mechanical, and long-term properties of concrete, along with changes in its chemical composition following the addition of RAP and TiO2, were evaluated. Results revealed that using 30% and 50% RAP in concrete mixtures reduced their compressive strength by 18% and 27%, respectively. However, using TiO2 in those mixtures enhanced their compressive strength by 8.7% an

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Publication Date
Tue Jan 08 2019
Journal Name
Iraqi Journal Of Physics
First principles calculations of Al AsxP1-x ternary nanocrystal alloying composition
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III-V zinc-blende AlP, AlAs semiconductors and their alloy Aluminum Arsenide phosphide Al AsxP1-x ternary nanocrystals have been investigated using Ab- initio density functional theory (Ab-initio-DFT) at the generalized-gradient approximation (GGA) level with STO-3G basis set coupled with large unit cell method (LUC). The dimension of crystal is found around (1.56 – 2.24) nm at a function of increasing the sizes (8, 16, 54, 64) with different concentration of arsenide (x=0, 0.25, 0.5, 0.75 and 1) respectively. Gaussian 03 code program has been used throughout this study to calculate some of the physical properties such as the electronic properties energy gap, lattice constant, valence and conduction band as well as density of state. Re

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