Preferred Language
Articles
/
ruassZ0BmraWrQ4dEVol
Evaluation of the Accuracy of Machine Learning Classifiers and Spectral Indices in Land Cover Classification
...Show More Authors

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.

Scopus Crossref
View Publication
Publication Date
Sun Jun 28 2026
Journal Name
Journal Of Physical Education
The Learning Gap between Classroom Education and Artificial Intelligence-Based Education in Curriculum Design among Students of the College of Physical Education and Sports Sciences from the Students' Perspective
...Show More Authors

       The present study aimed to identify the learning gap between classroom-based education and artificial intelligence (AI)-based education among students of Colleges of Physical Education and Sports Sciences. It also sought to determine the effectiveness of classroom education and AI-based education in reducing the learning gap among these students. The research problem addressed the following questions: Are there statistically significant differences in the learning gap between students who learn through traditional classroom education and those who learn through AI-based education in Colleges of Physical Education and Sports Sciences? What is the nature of the learning gap between classroom education and AI-based educati

... Show More
View Publication
Crossref
Publication Date
Sun Mar 04 2012
Journal Name
Baghdad Science Journal
Synthesis and Spectral Studies of ZnII,CdII and HgII Complexes with 5-(2-Benzoic acid azo)-8-hydroxy quinoline Ligand
...Show More Authors

Coupling reaction of 2-amino benzoic acid with 8-hydroxy quinoline gave bidentate azo ligand. The prepared ligand has been identified by Microelemental Analysis,1HNMR,FT-IR and UV-Vis spectroscopic techniques. Treatment of the prepared ligand with the following metal ions (ZnII,CdII and HgII) in aqueous ethanol with a 1:2 M:L ratio and at optimum pH, yielded a series of neutral complexes of the general formula [M(L)2]. The prepared complexes have been characterized by using flame atomic absorption, (C.H.N) Analysis, FT-IR and UV-Vis spectroscopic methods as well as conductivity measurements. The nature of the complexes formed were studied following the mole ratio and continuous variation methods, Beer's law obeyed over a concentration ra

... Show More
View Publication Preview PDF
Crossref
Publication Date
Thu May 17 2012
Journal Name
Baghdad Science Journal
Synthesis and Spectral Studies of ZnII,CdII and HgII Complexes with 5-(2-Benzoic acid azo)-8-hydroxy quinoline Ligand
...Show More Authors

Coupling reaction of 2-amino benzoic acid with 8-hydroxy quinoline gave bidentate azo ligand. The prepared ligand has been identified by Microelemental Analysis,1HNMR,FT-IR and UV-Vis spectroscopic techniques. Treatment of the prepared ligand with the following metal ions (ZnII,CdII and HgII) in aqueous ethanol with a 1:2 M:L ratio and at optimum pH, yielded a series of neutral complexes of the general formula [M(L)2]. The prepared complexes have been characterized by using flame atomic absorption, (C.H.N) Analysis, FT-IR and UV-Vis spectroscopic methods as well as conductivity measurements. The nature of the complexes formed were studied following the mole ratio and continuous variation methods, Beer's law obeyed over a concentration range

... Show More
Preview PDF
Publication Date
Sun Mar 04 2012
Journal Name
Baghdad Science Journal
Synthesis and Spectral Studies of ZnII,CdII and HgII Complexes with 5-(2-Benzoic acid azo)-8-hydroxy quinoline Ligand
...Show More Authors

Coupling reaction of 2-amino benzoic acid with 8-hydroxy quinoline gave bidentate azo ligand. The prepared ligand has been identified by Microelemental Analysis,1HNMR,FT-IR and UV-Vis spectroscopic techniques. Treatment of the prepared ligand with the following metal ions (ZnII,CdII and HgII) in aqueous ethanol with a 1:2 M:L ratio and at optimum pH, yielded a series of neutral complexes of the general formula [M(L)2]. The prepared complexes have been characterized by using flame atomic absorption, (C.H.N) Analysis, FT-IR and UV-Vis spectroscopic methods as well as conductivity measurements. The nature of the complexes formed were studied following the mole ratio and continuous variation methods, Beer's law obeyed over a concentration range

... Show More
Preview PDF
Publication Date
Wed Feb 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering
Classification of COVID-19 from CT chest images using Convolutional Wavelet Neural Network
...Show More Authors

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

... Show More
View Publication Preview PDF
Publication Date
Tue Aug 05 2014
Journal Name
International Journal Of Pharmacy And Pharmaceutical Sciences
FORMULATION AND EVALUATION OF FLOATING ORAL IN-SITU GEL OF METRONIDAZOLE
...Show More Authors

View Publication Preview PDF
Scopus (20)
Scopus
Publication Date
Fri Sep 15 2023
Journal Name
Journal Of Baghdad College Of Dentistry
Evaluation of alpha amylase and peroxidase in saliva of pregnant women
...Show More Authors

Background: Pregnancy is a natural physiological state that involves several biochemical modifications. Saliva is consisted of many types of proteins such as salivary alpha amylase and salivary peroxidase that might be affected by pregnancy. The former enzyme is considered one of the most prevalent proteins that is released by highly differentiated epithelial acinar cells and has been shown to have enzymatic activities while the latter has been approved that it  has a significant role in oral health. The purpose of this study was to the evaluate the salivary levels of alpha-amylase and peroxidase in pregnant and non-pregnant women. Materials and Methods: Sixty pregnant women were grouped according to the pregnancy trimesters. The first

... Show More
View Publication Preview PDF
Scopus (2)
Crossref (4)
Scopus Crossref
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
...Show More Authors

 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

... Show More
View Publication Preview PDF
Crossref
Publication Date
Tue Dec 03 2013
Journal Name
Baghdad Science Journal
Satellite Images Unsupervised Classification Using Two Methods Fast Otsu and K-means
...Show More Authors

Publication Date
Sun Jun 12 2011
Journal Name
Baghdad Science Journal
Satellite Images Unsupervised Classification Using Two Methods Fast Otsu and K-means
...Show More Authors

Two unsupervised classifiers for optimum multithreshold are presented; fast Otsu and k-means. The unparametric methods produce an efficient procedure to separate the regions (classes) by select optimum levels, either on the gray levels of image histogram (as Otsu classifier), or on the gray levels of image intensities(as k-mean classifier), which are represent threshold values of the classes. In order to compare between the experimental results of these classifiers, the computation time is recorded and the needed iterations for k-means classifier to converge with optimum classes centers. The variation in the recorded computation time for k-means classifier is discussed.

View Publication Preview PDF
Crossref