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Supervised Classification Accuracy Assessment Using Remote Sensing and Geographic Information System
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Assessing the accuracy of classification algorithms is paramount as it provides insights into reliability and effectiveness in solving real-world problems. Accuracy examination is essential in any remote sensing-based classification practice, given that classification maps consistently include misclassified pixels and classification misconceptions. In this study, two imaginary satellites for Duhok province, Iraq, were captured at regular intervals, and the photos were analyzed using spatial analysis tools to provide supervised classifications. Some processes were conducted to enhance the categorization, like smoothing. The classification results indicate that Duhok province is divided into four classes: vegetation cover, buildings, water bodies, and bare lands. During 2013-2022, vegetation cover increased from 63% in 2013 to 66% in 2022; buildings roughly increased by 1% to 3% yearly; water bodies showed a decrease of 2% to 1%; the amount of unoccupied land showed a decrease from 34% to 30%. Therefore, the classification accuracy was assessed using the approach of comparison with field data; the classification accuracy was about 85%.

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Publication Date
Wed Sep 23 2020
Journal Name
Artificial Intelligence Research
Hybrid approaches to feature subset selection for data classification in high-dimensional feature space
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This paper proposes two hybrid feature subset selection approaches based on the combination (union or intersection) of both supervised and unsupervised filter approaches before using a wrapper, aiming to obtain low-dimensional features with high accuracy and interpretability and low time consumption. Experiments with the proposed hybrid approaches have been conducted on seven high-dimensional feature datasets. The classifiers adopted are support vector machine (SVM), linear discriminant analysis (LDA), and K-nearest neighbour (KNN). Experimental results have demonstrated the advantages and usefulness of the proposed methods in feature subset selection in high-dimensional space in terms of the number of selected features and time spe

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Publication Date
Wed Sep 16 2020
Journal Name
Al-kindy College Medical Journal
The importance of anatomical zonal classification in the early management of penetrating neck injuries
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Background: Penetrating neck injuries are common problem in our country due to increasing violence, terrorist bombing and military operations.
These injuries are potentially life threating and need great attention and proper management.
Objective: The aim of this study is to focus on the importance of anatomical zonal classification of the neck in the management of penetrating injuries of the visceral compartment of the Neck.
Methods :70 patients with various injuries who were managed at causality unit and Otolaryngology department in Al-Kindy Teaching Hospital during aperiod from January 1st 2015 to October 31st 2015.
The study carried on those patient depending on proper clinical examination and their urgent management.

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Publication Date
Fri Sep 27 2024
Journal Name
Journal Of Applied Mathematics And Computational Mechanics
Fruit classification by assessing slice hardness based on RGB imaging. Case study: apple slices
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Correct grading of apple slices can help ensure quality and improve the marketability of the final product, which can impact the overall development of the apple slice industry post-harvest. The study intends to employ the convolutional neural network (CNN) architectures of ResNet-18 and DenseNet-201 and classical machine learning (ML) classifiers such as Wide Neural Networks (WNN), Naïve Bayes (NB), and two kernels of support vector machines (SVM) to classify apple slices into different hardness classes based on their RGB values. Our research data showed that the DenseNet-201 features classified by the SVM-Cubic kernel had the highest accuracy and lowest standard deviation (SD) among all the methods we tested, at 89.51 %  1.66 %. This

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
Future Scenario of Global Climate Map change according to the Köppen -Geiger Climate Classification
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Earth’s climate changes rapidly due to the increases in human demands and rapid economic growth. These changes will affect the entire biosphere, mostly in negative ways. Predicting future changes will put us in a better position to minimize their catastrophic effects and to understand how humans can cope with the new changes beforehand. In this research, previous global climate data set observations from 1961-1990 have been used to predict the future climate change scenario for 2010-2039. The data were processed with Idrisi Andes software and the final Köppen-Geiger map was created with ArcGIS software. Based on Köppen climate classification, it was found that areas of Equator, Arid Steppes, and Snow will decrease by 3.9 %, 2.96%, an

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Publication Date
Fri Jul 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Investing Information Technology and its Interactional Role in the Relationship between Value Added Intellectual Capital and Financial Performance An Analytical Comparative Rese
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 Abstract 

The basic aim of this research is to study the interactional effect of investing information technology on the relationship between value added intellectual capital and financial performance as literature review suggested on the theoretical level, including previous studies, with the deduction of its trends strongly predicted by research hypotheses and their content associated with the investment in intellectual capital after information technology tools being employed in this direction to improve the financial performance of the studied companies at the levels of both industrial and service sectors, a non-random sample was chosen included (40) forty Iraqi Joint-Stoc

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Publication Date
Sat Nov 10 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Assessment of Clinical Learning and Training Environment for Maternal and Child Health Nursing Students
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Objective: To assess the clinical learning environment and clinical training for students' in maternal and child
health nursing.
Methodology: A descriptive study was conducted on non probability sample (purposive) of (175) students' in
Nursing College/ University of Baghdad for the period of June 19th to July 18th 2013. A questionnaire was used as a
tool of data collection to fulfill with objective of the study and consisted of three parts, including demographic,
clinical learning environment and clinical training for students' in maternal and child health nursing. Descriptive
statistical analyses were used to analyze the data.
Results: The results of the study revealed that the 65.1% of student at age which ranged b

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Publication Date
Thu Jun 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
The Use of the Regression Tree and the Support Vector Machine in the Classification of the Iraqi Stock Exchange for the Period 2019-2020
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 The financial markets are one of the sectors whose data is characterized by continuous movement in most of the times and it is constantly changing, so it is difficult to predict its trends , and this leads to the need of methods , means and techniques for making decisions, and that pushes investors and analysts in the financial markets to use various and different methods in order to reach at predicting the movement of the direction of the financial markets. In order to reach the goal of making decisions in different investments, where the algorithm of the support vector machine and the CART regression tree algorithm are used to classify the stock data in order to determine

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Publication Date
Tue Jan 01 2019
Journal Name
World Journal Of Dentistry
Assessment of Implant Stability Changes and Success Rate of Narrow Dental Implants
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Aims: To assess the success rate and implant stability changes of narrow dental implants (NDIs) during the osseous healing period. Materials and methods: This prospective observational clinical study included 21 patients with narrow alveolar ridge of restricted mesiodistal interdental span who received NDIs. The alveolar ridge width was determined by the ridge mapping technique. Implant stability was measured using Periotest® M immediately after implant insertion then after 4 weeks, 8 weeks and 12 weeks postoperatively. The outcome variables were success rate and implant stability changes during the healing period. The statistical analysis included one-way analysis of variance (ANOVA) and Tukey\'s multiple comparisons test, values < 0.05 w

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Publication Date
Mon Oct 05 2026
Journal Name
Journal Of Baghdad College Of Dentistry
Assessment of serum and salivary malondialdehyde in patients with oral lichen planus
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Background: The aim of this study was to evaluate the expression of fibroblast growth factor-2 and Heparanase in salivary pleomorphic adenoma, and to correlate the two studied markers with each other and with clinicopathological parameters including: age, sex, tumor site and histopathological presentation. Methods: Sections of twenty five formalin-fixed paraffin embedded tissue blocks specimens of salivary pleomorphic adenoma were immunostained using monoclonal antibodies (Fibroblast growth factor-2 and Heparanase) to assess their expression in this tumor. Results: The expression of fibroblast growth factor-2 and Heparanase were positive in all pleomorphic adenoma cases (100%). The positive expression of fibroblast growth factor-2 was signi

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Publication Date
Tue Dec 01 2020
Journal Name
Journal Of Engineering Science And Technology
Quantitative and qualitative assessment of groundwater: The case of Khanaqin alluvial (Iraq
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