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Evaluation of the Accuracy of Machine Learning Classifiers and Spectral Indices in Land Cover Classification
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Population growth and economic and industrial development coupled have significantly accelerated the rate of Land Use and Land Cover (LULC) changes, particularly in developing countries, so finding optimum ways to observe these change has become a pressing issue. Quantification evaluation of these changes is crucial to comprehend and oversee land management conversion, therefore, it is necessary to evaluate the accuracy of various algorithms for LULC classification to determine the most effective classifier for Earth observation applications. The performance of Maximum Likelihood (ML), Support Vector Machines (SVM), Random Forest (RF), and K-Nearest Neighbors (KNN) was examined in this study, based on Sentinel 2A satellite images. The accuracy of those classifiers was evaluated using the Kappa Coefficient and normalized difference index-based verification. The findings indicate that all classifiers exhibit high accuracy levels with variations. The RF algorithm had the highest Kappa coefficient of 0.90, while the KNN algorithm the lowest of 0.76. The accuracy values for RF, SVM, ML, and KNN were 93.1%, 91.2%, 86.2%, and 82.5%, respectively. Results from this study using index-based LULC show that the RF classifier outperforms the others. The results of this study can be used in monitoring LULC change tasks.

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Publication Date
Wed Aug 13 2025
Journal Name
Mechanics Of Time-dependent Materials
Performance evaluation of highly modified asphalt binders using elastomeric and plastomeric polymers
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Highly Modified Asphalt (HiMA) binders have garnered significant attention due to their superior resistance to rutting, fatigue cracking, and thermal distress under heavy traffic loads and extreme environmental conditions. While elastomeric polymers such as Styrene- Butadiene-Styrene (SBS) have been extensively used in HiMA applications, the potential of plastomeric polymers, including Polyethylene (PE) and Ethylene Vinyl Acetate (EVA), remains largely unexplored. This study aims to evaluate the performance of reference binder (RB) modified with plastomeric HiMA asphalt in comparison to SBS-modified binders and determine the optimal polymer dosage for achieving an optimal balance between rutting resistance and fatigue durability. The experi

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Publication Date
Thu Jun 25 2020
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Synthesis and Preliminary Biological Activity Evaluation of New N- Substituted Phthalimide Derivatives
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A new series of bases of Schiff (H2-H4) derived from phthalic anhydrideweresynthesized. These Schiff bases were prepared by the reaction of different amines (tyrosine methyl ester, phenylalanine methyl ester, and isoniazid) with the phthalimide derived aldehyde with the aid of glacial acetic acid or triethylamine ascatalysts. All the synthesized compounds were characterized by (FT-IR and 1HNMR) analyses and were in vitro evaluated for their antimicrobial activity against six various kinds of microorganisms. All the synthesized compounds had been screened for their antimicrobial activity against two Gram-positive bacteria “Staph. Aureus, and Bacillus subtilis

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Publication Date
Tue Oct 13 2026
Journal Name
Journal Of Baghdad College Of Dentistry
Cone Beam Computed Tomography in an Evaluation and Diagnosis of Anatomical Variations and Pathological Lesions in Maxillary Sinus Prior to Maxillary Sinus Lift Surgery
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Abstract: Thorough assessment of the Maxillary,Sinus is very important. Recently 3-dimensional imagewith Cone Beam Computed Tomography (CBCT) is very dependable in Maxillary Sinus diagnosis. The aim of this study is to: shade light on the role of (CBCT) diagnosis of the maxillary sinus anatomical variation and pathological finding among smokers and nonsmokers prior to maxillary sinus lift techniques. Materials and Method: In this study 60 males with age ranged between 20-50 years old, referred for (CBCT) assessment of maxillary sinus in the Specialist Health Center of AL-Sadder city. The scanning were performed using Kodak 9500 (CBCT), the KV was 90, mA10 and scanning time 10 s. Voxel size 0.3mm with( DICOM ) software on a multiplaner re

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Publication Date
Tue Oct 13 2026
Journal Name
Journal Of Baghdad College Of Dentistry
Evaluation of the stress concentration of different incisal ridge preparations of porcelain veneers (Finite element analysis)
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Background: Porcelain veneers are under a great deal of stress which may lead to clinical failure as fracture or dettachment. This study examined whether different finishing lines and lingual shoulder preparations in the incisal area of the maxillary central incisor affect the bond of the porcelain veneers. Materials and methods: A two- dimensional finite element model was made. Location and magnitude of maximum Von Mises stresses were calculated in porcelain veneer. Six types of preparations were drawn as:incisal overlap of 0.5mm, 1mm and 1.5mm depth and lingual shoulder, and incisal overlap of 0.5mm, 1mm and 1.5mm depth without shoulder preparation. Results: Stress formation is maximum in the incisal edge region. All the lingual shoulder

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Publication Date
Sat Sep 24 2022
Journal Name
International Journal Of Biomaterials
Histological Evaluation of the Effect of Local Application of Punica granatum Seed Oil on Bone Healing
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Background. Bone healing is a complex and dynamic process that represents a well-orchestrated series of biological events of cellular recruitment, proliferation, and differentiation. The use of medicinal plants in bone healing has attracted increasing interest because of their lower side effects. Punica granatum seed oil (PSO) contains high levels of phenolic compounds, promotes osteoblast function, and plays an important role in bone remodeling. A gelatin sponge (Spongostan) is a hemostatic agent that is extensively applied as scaffolds in engineering and as drug carriers in the medical field. This study aimed to evaluate the effectiveness of PSO for bone healing enhancement. Twenty adult male New Zealand rabbits, weighing an avera

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Publication Date
Sat Mar 01 2025
Journal Name
Al-khwarizmi Engineering Journal
Deep-Learning-Based Mobile Application for Detecting COVID-19
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Patients infected with the COVID-19 virus develop severe pneumonia, which typically results in death. Radiological data show that the disease involves interstitial lung involvement, lung opacities, bilateral ground-glass opacities, and patchy opacities. This study aimed to improve COVID-19 diagnosis via radiological chest X-ray (CXR) image analysis, making a substantial contribution to the development of a mobile application that efficiently identifies COVID-19, saving medical professionals time and resources. It also allows for timely preventative interventions by using more than 18000 CXR lung images and the MobileNetV2 convolutional neural network (CNN) architecture. The MobileNetV2 deep-learning model performances were evaluated

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Publication Date
Mon Jan 01 2024
Journal Name
Computers, Materials & Continua
Credit Card Fraud Detection Using Improved Deep Learning Models
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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
3D scenes semantic segmentation using deep learning based Survey
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Abstract<p>Semantic segmentation realization and understanding is a stringent task not just for computer vision but also in the researches of the sciences of earth, semantic segmentation decompose compound architectures in one elements, the most mutual object in a civil outside or inside senses must classified then reinforced with information meaning of all object, it’s a method for labeling and clustering point cloud automatically. Three dimensions natural scenes classification need a point cloud dataset to representation data format as input, many challenge appeared with working of 3d data like: little number, resolution and accurate of three Dimensional dataset . Deep learning now is the po</p> ... Show More
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Publication Date
Mon Jan 09 2023
Journal Name
2023 15th International Conference On Developments In Esystems Engineering (dese)
Deep Learning-Based Speech Enhancement Algorithm Using Charlier Transform
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Publication Date
Wed Nov 07 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Evaluation of the Hardness of Cold Cured Acrylic Resin Material by Processing at Different Temperature
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Objective(s): This study aims to evaluate the hardness of two commercially available cold cured acrylic resin material
(Vertex and PAN) when polymerized at different temperature in comparison to those polymerized by conventional
methods in air at 23C ± 5C.
Methodology: Eighty specimens, forty from cold cured acrylic (Vertex Type) and forty from cold cured acrylic (PAN
type) were prepared, flasking and packing procedure were done according to manufacturer direction and divided
according to processing as follow: 20 specimens (10 from Vertex type and 10 from PAN type) were processed in air for
two hours at 23C ± 5C under press (bench curing) as a control, and 60 specimens (30 from Vertex type and 30 from
PAN type) wer

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