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.
The emergence of COVID-19 has resulted in an unprecedented escalation in different aspects of human activities, including medical education. Students and educators across academic institutions have confronted various challenges in following the guidelines of protection against the disease on one hand and accomplishing learning curricula on the other hand. In this short view, we presented our experience in implementing e-learning to the undergraduate nursing students during the present COVID-19 pandemic emphasizing the learning content, barriers, and feedback of students and educators. We hope that this view will trigger the preparedness of nursing faculties in Iraq to deal with this new modality of learning and improve it should t
... Show MoreWhat is important about this study is whether there is a relationship between the ability to balance and beating overwhelming for the Iraqi national team volleyball? The study aims to identify the percentage of the equilibrium contribution and its variables with the accuracy of the skill of beating the high spike Diagonal center (4) in the players. In the national volleyball team season (2016-2017), the researchers used the descriptive approach in the style of associative relationships to suit the problem of research. The research community included all the players specialized in the high beating of the Iraqi national team applicants in the ball The researchers concluded that the equilibrium variables contributed accurately and quickly to t
... Show MoreA study was conducted at the University of Baghdad-College of Agricultural Engineering Sciences - Department of Agricultural Machinery and Equipment for the agricultural season 2023 with the aim of designing, manufacturing and testing a machine used to planting agricultural nursery tray with different types of vegetable or horticultural seeds or forest seeds of various forms, and using different agricultural media where they are conducted The planting process is by pulling the seeds with a negative pressure vacuum system, and then they are feding to the dishes in their right place to complete the planting process. The study included three factors: The speed of the main belt in three l
CNC machine is used to machine complex or simple shapes at higher speed with maximum accuracy and minimum error. In this paper a previously designed CNC control system is used to machine ellipses and polylines. The sample needs to be machined is drawn by using one of the drawing software like AUTOCAD® or 3D MAX and is saved in a well-known file format (DXF) then that file is fed to the CNC machine controller by the CNC operator then that part will be machined by the CNC machine. The CNC controller using developed algorithms that reads the DXF file feeds to the machine, extracts the shapes from the file and generates commands to move the CNC machine axes so that these shapes can be machined.
Soil that has been contaminated by heavy metals is a serious environmental problem. A different approach for forecasting a variety of soil physical parameters is reflected spectroscopy is a low-cost, quick, and repeatable analytical method. The objectives of this paper are to predict heavy metal (Ti, Cr, Sr, Fe, Zn, Cu and Pb) soil contamination in central and southern Iraq using spectroscopy data. An XRF was used to quantify the levels of heavy metals in a total of 53 soil samples from Baghdad and ThiQar, and a spectrogram was used to examine how well spectral data might predict the presence of heavy metals metals. The partial least squares regression PLSR models performed well in pr
The lowest layer of the atmosphere is called the atmospheric mixed layer, characterized by small-scale, irregular air motions defined by winds that change in speed and direction. Aerosol radiative effects impact the atmospheric boundary layer (ABL), which holds most aerosols in the lower atmosphere. Aerosol absorption and scattering both lower the quantity of solar energy that reaches the ground, which has an impact on the spectral signature of the land coverings. In this study, 51 locations in downtown Baghdad were chosen for four different types of land cover (water bodies, farms, open areas, and residential areas) for Sentinel 2 satellite imagery, and the time the pictures were taken was 8:00 am ( 22 March, 22 June, 20 September,
... Show MoreThe field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet
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