Medical images play a crucial role in the classification of various diseases and conditions. One of the imaging modalities is X-rays which provide valuable visual information that helps in the identification and characterization of various medical conditions. Chest radiograph (CXR) images have long been used to examine and monitor numerous lung disorders, such as tuberculosis, pneumonia, atelectasis, and hernia. COVID-19 detection can be accomplished using CXR images as well. COVID-19, a virus that causes infections in the lungs and the airways of the upper respiratory tract, was first discovered in 2019 in Wuhan Province, China, and has since been thought to cause substantial airway damage, badly impacting the lungs of affected persons. The virus was swiftly gone viral around the world and a lot of fatalities and cases growing were recorded on a daily basis. CXR can be used to monitor the effects of COVID-19 on lung tissue. This study examines a comparison analysis of k-nearest neighbors (KNN), Extreme Gradient Boosting (XGboost), and Support-Vector Machine (SVM) are some classification approaches for feature selection in this domain using The Moth-Flame Optimization algorithm (MFO), The Grey Wolf Optimizer algorithm (GWO), and The Glowworm Swarm Optimization algorithm (GSO). For this study, researchers employed a data set consisting of two sets as follows: 9,544 2D X-ray images, which were classified into two sets utilizing validated tests: 5,500 images of healthy lungs and 4,044 images of lungs with COVID-19. The second set includes 800 images, 400 of healthy lungs and 400 of lungs affected with COVID-19. Each image has been resized to 200x200 pixels. Precision, recall, and the F1-score were among the quantitative evaluation criteria used in this study.
A new and hybrid deep learning-based approach for diagnosing faults in electric vehicle (EV) drive motors is proposed in this article. This article presents a new and hybrid deep learning-based method of diagnosing faults in the drive motors of electric vehicles (EV). In contrast to standard CNNLSTM approaches that depend on SoftMax classification, the introduced framework combines a Random Forest (RF) classifier to enhance the generalization, interpretability, and robustness of fault prediction. Furthermore meant for use on edge computing equipment with IoT integration, the design allows for real-time monitoring in resource-limited settings. The introduced algorithm utilizes a Random Forest (RF) classifier for accurate fault classification
... Show MoreThis research is devoted to the effect of investigation of the ZnO content on the structural and electrical properties of (NiO)1-x (ZnO)x films prepared by pulsed laser precipitation on the glass substrate at room temperature. Thin-film (NiO)1-x (ZnO)x sediments were deposited with different composition ratios where x = 0, 0.2, 0.4, 0.6 and 1.0 with a thickness of n150nm. The diffraction pattern for X-ray analysis reveals that the structure of the prepared thin films is identical with the cubic phase and hexadecimal stage of x = 0 and 0.1, respectively while the structure is mixed with the remaining x
تعد الموازنة الأداة الأساسية لتنفيذ أولويات أية دولة، ويتوجب النظر إليها في ضوء المناخ الاجتماعي والسياسي والاقتصادي، لأنها تساعد في توجيه الاقتصاد لتحقيق النمو ورفع مستوى الرفاهية. اعتمدت وزارة المالية في أعداد الموازنة السنوية بعد 9/4/ 2003 أسلوباً مغايراً لما كان معتمداً في العقود الماضية، إذ كانت هناك موازنتين الأولى الموازنة الجارية، والثانية الموازنة الاستثمارية رغم وجود قانون يحتم إصدار موازنة
... Show MoreMany approaches of different complexity already exist to edge detection in
color images. Nevertheless, the question remains of how different are the results
when employing computational costly techniques instead of simple ones. This
paper presents a comparative study on two approaches to color edge detection to
reduce noise in image. The approaches are based on the Sobel operator and the
Laplace operator. Furthermore, an efficient algorithm for implementing the two
operators is presented. The operators have been applied to real images. The results
are presented in this paper. It is shown that the quality of the results increases by
using second derivative operator (Laplace operator). And noise reduced in a good
A roundabout is a highway engineering concept meant to calm traffic, increase safety, reduce stop-and-go travel, reduce accidents and congestion, and decrease traffic delays. It is circular and facilitates one-way traffic flow around a central point. The first part of this study evaluated the principles and methods used to compare the capacity methods of roundabouts with different traffic conditions and geometric configurations. These methods include gap acceptance, empirical, and simulation software methods. Previous studies mentioned in this research used various methods and other new models developed by several researchers. However, this paper's main aim is to compare different roundabout capacity models for acceptabl
... Show MoreThe alloys of CdSe1-xTex compound have been prepared from their elements successfully with high purity (99.9999%) which mixed stoichiometry ratio (x=0.0, 0.25, 0.5, 0.75 and 1.0) of (Cd, Se and Te) elements. Films of CdSe1-xTex alloys for different values of composition with thickness(0.5?m) have been prepared by thermal evaporation method at cleaned glass substrates which heated at (473K) under very low pressure (4×10-5mbar) at rate of deposition (3A?/s), after that thin films have been heat treated under low pressure (10-2mbar) at (523K) for two hours. The optical studies revealed that the absorption coefficient (?) is fairly high. It is found that the electronic transitions in the fundamental absorption edge tend to be allowed direct tr
... Show MoreThe availability of different processing levels for satellite images makes it important to measure their suitability for classification tasks. This study investigates the impact of the Landsat data processing level on the accuracy of land cover classification using a support vector machine (SVM) classifier. The classification accuracy values of Landsat 8 (LS8) and Landsat 9 (LS9) data at different processing levels vary notably. For LS9, Collection 2 Level 2 (C2L2) achieved the highest accuracy of (86.55%) with the polynomial kernel of the SVM classifier, surpassing the Fast Line-of-Sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) at (85.31%) and Collection 2 Level 1 (C2L1) at (84.93%). The LS8 data exhibits similar behavior. Conv
... Show MoreTin:antimony oxides composites have given great attention due to their unique properties and many application in various fields like optoelectronic devices, gas sensors. The synthesis and characterization of (SnO2)1-x(Sb2O3)x was conducted in order to comprehend the structure and discuss the optical and dielectric properties of this composites. The x-ray showed that the prepared pure tin oxide thin film was had a polycrystalline structure and that the peaks were identical with the tetragonal phase while the peaks were identical with antimony oxide for x=0.1 to x=0.5. The average crystal size along the preferred level of growth of tin oxide as well as of antimony oxide showed non regular change by i
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