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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
Fri Aug 07 2026
Journal Name
Current Drug Therapy
Formulation and In Vivo Evaluation of Ticagrelor-Loaded Spanlastic Nanovesicles to Enhance Intestinal Absorption
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Introduction:

Ticagrelor (TCG) is an effective P2Y12 receptor antagonist used to prevent atherothrombotic cardiovascular events; however, its poor solubility and limited permeability (BCS Class IV) restrict its oral bioavailability. Spanlastic Nanovesicles (SNVs), composed of nonionic surfactants and edge activators, offer a promising strategy to enhance drug solubility and permeability. This study aimed to develop and optimize TCG-loaded SNVs using the ethanol injection method, validate a sensitive HPLC method for TCG quantification, and evaluate the pharmacokinetic and antiplatelet performance of the optimized formulation in rats.

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Publication Date
Sat Dec 30 2023
Journal Name
Iraqi Journal Of Pharmaceutical Sciences( P-issn 1683 - 3597 E-issn 2521 - 3512)
Preparation, In-vitro, and Ex-vivo Evaluation of Ondansetron Loaded Invasomes for Transdermal Delivery
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Invasomes are newly developed types of nanovesicles. A vesicular drug delivery system is considered one of the approaches for transdermal delivery to enhance permeation and improve drug bioavailability. Ondansetron is a serotonin receptor antagonist used for treating vomiting associated with different clinical cases. The study aimed to prepare invasomal dispersions for improving permeation of ondansetron across the skin with a controlled release pattern. Twenty-seven formulas of ondansetron-loaded invasomes were prepared by a modified mechanical dispersion method. These formulas were optimized by studying the effect of variables on entrapment efficiency. Vesicle size, polydispersity, zeta potential, in-vitro release and ex-vivo perm

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Publication Date
Sat Oct 01 2022
Journal Name
Journal Of Engineering
Evaluation of ANFIS and Regression Techniques in Estimating Soil Compression Index for Cohesive soils
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Generally, direct measurement of soil compression index (Cc) is expensive and time-consuming. To save time and effort, indirect methods to obtain Cc may be an inexpensive option. Usually, the indirect methods are based on a correlation between some easier measuring descriptive variables such as liquid limit, soil density, and natural water content. This study used the ANFIS and regression methods to obtain Cc indirectly. To achieve the aim of this investigation, 177 undisturbed samples were collected from the cohesive soil in Sulaymaniyah Governorate in Iraq. Results of this study indicated that ANFIS models over-performed the Regression method in estimating Cc with R2 of 0.66 and 0.48 for both ANFIS and Regre

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Publication Date
Wed Jan 18 2017
Journal Name
International Journal Of Pharmacy Practice
Antimicrobial utilization in an Iraqi province: a comprehensive evaluation of antibiotic source and cost
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Publication Date
Thu Sep 01 2022
Journal Name
Neuroquantology
Evaluation of using of square flap in treatment of Postburn Contracture
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Background: One of the most common problems that encountered is postburn contracture which has both functional and aesthetic impact on the patients. Various surgical methods had being proposed to treat such problem. Aim: To evaluate the effectiveness of square flap in management of postburn contracture in several part of the body. Patients and methods: From April 2019 to June 2020 a total number of 20 patients who had postburn contracture in various parts of their body were subjected to scar contracture release using square flap. The follow up period was ranging between 6 months to 12 months. Results: All of our patients had achieved complete release of their band with maximum postoperative motion together with accepted aesthetic outcome. A

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Publication Date
Sat Jul 08 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Formulation and Evaluation of Sustained and Raft Forming Antacid Tablet
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Antacids have been widely used in the treatment of various gastric and duodenal disorders such as heartburn, reflux esophagitis, gastritis, irritable stomach, gastric and duodenal ulcers. A pH-responsive of bi-polymer of sodium alginate and pectin have been studied as raft-forming polymers using sodium bicarbonate and calcium carbonate as gas-generating and calcium ion sources. The aim of study was to formulate and evaluate mono and bilayer tablets of floating and sustained release antacid delivery systems using sodium carboxy methyl cellulose as a gel forming substance, calcium and magnesium carbonate as sources of acid neutralizing and carbon dioxide gas generators agents upon contact with acidic solution. The effect of the formulation

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Publication Date
Wed May 10 2017
Journal Name
Journal Of The College Of Languages (jcl)
РОЛЬ СРЕДСТВ НАГЛЯДНОСТИ В ПРОЦЕССЕ ОБУЧЕНИЯ РУССКОМУ ЯЗЫКУ КАК ИНОСТРАННОМУ В ИРАСКОЙ АУДИТОРИИ The Role of the Use of Visual Aids in the Process Of Learning Russian Language in Lraq as a Foreign Language
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В статье рассматриваются понятие наглядности и ее классификация, эффективное применение принципа наглядности, возможность и преимущество использования наглядности и современные инструменты ее реализации в ираке.

 

Вследствие глобальных изменений во всем мире изменилась и роль иностранного языка в системе образования. Современный человек, шагающий в ногу со временем, не мыслит себя без зна

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Publication Date
Mon Jan 01 2024
Journal Name
Aip Conference Proceedings
Comparative analysis of deep learning techniques for lung cancer identification
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One of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details p

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Publication Date
Fri Dec 01 2023
Journal Name
Al-khwarizmi Engineering Journal
An Overview of Audio-Visual Source Separation Using Deep Learning
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    In this article, the research presents a general overview of deep learning-based AVSS (audio-visual source separation) systems. AVSS has achieved exceptional results in a number of areas, including decreasing noise levels, boosting speech recognition, and improving audio quality. The advantages and disadvantages of each deep learning model are discussed throughout the research as it reviews various current experiments on AVSS. The TCD TIMIT dataset (which contains top-notch audio and video recordings created especially for speech recognition tasks) and the Voxceleb dataset (a sizable collection of brief audio-visual clips with human speech) are just a couple of the useful datasets summarized in the paper that can be used to t

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Publication Date
Tue Apr 30 2024
Journal Name
International Journal On Technical And Physical Problems Of Engineering
Deep Learning Techniques For Skull Stripping of Brain MR Images
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Deep Learning Techniques For Skull Stripping of Brain MR Images

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