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.
Streamlined peristaltic transport patterns, bifurcations of equilibrium points, and effects of an inclined magnetic field and channel are shown in this study. The incompressible fluid has been the subject of the model's investigation. The Reynolds values for evanescence and an infinite wavelength are used to constrain the flow while it is being studied in a slanted channel with a slanted magnetic field. The topologies over their domestic and cosmopolitan bifurcations are investigated for the outcomes, and notion of the dynamical system are employed. The Mathematica software is used to solve the nonlinear autonomous system. The flow is found to have three different flow distributions namely augmented, trapping and backward flow. Outc
... Show MoreThe main objective of this study is to develop predictive models using SPSS software (version 18) for Marshall Test results of asphalt mixtures compacted by Hammer, Gyratory, and Roller compaction. Bulk density of (2.351) gm/cc, at OAC of (4.7) % was obtained as a benchmark after using Marshall Compactor as laboratory compactive effort with 75-blows. Same density was achieved by Roller and Gyratory Compactors using its mix designed methods.
A total of (75) specimens, for Marshall, Gyratory, and Roller Compactors have been prepared, based on OAC of (4.7) % with an additional asphalt contents of more and less than (0.5) % from the optimum value. All specimens have been subjected to Marshall Test. Mathematical model
... Show MoreMagical realism potential bulwark plastic art and literature، and won great fame and Research cash innumerable، and like other currents of literary found his outlet in the art of cinema، quoted cinema of literature magical realism and influenced his concepts، and Arab cinema، it was necessary to have a vulnerability to stream، either Tools employing magical realism، unintentionally since the early beginnings dating back to the time of World Wars I and II، or in deliberate more mature in the twenty-first century، due to the emergence of film-makers more aware and culture، and more friction global currents.
But this raises a number of problems that need to be addressed from the maker of
The support vector machine, also known as SVM, is a type of supervised learning model that can be used for classification or regression depending on the datasets. SVM is used to classify data points by determining the best hyperplane between two or more groups. Working with enormous datasets, on the other hand, might result in a variety of issues, including inefficient accuracy and time-consuming. SVM was updated in this research by applying some non-linear kernel transformations, which are: linear, polynomial, radial basis, and multi-layer kernels. The non-linear SVM classification model was illustrated and summarized in an algorithm using kernel tricks. The proposed method was examined using three simulation datasets with different sample
... Show MoreThe aim of this study was the discrimination of Salmonella isolated from chicken and their feed and drinking water for the epidemiological control of salmonellosis. Totally, 289 samples, including 217 chicken cloaca swabs, 46 water, and 26 feed samples were collected from five different farms in Karbala governorate, Iraq. Conventional bacteriology tests, API 20E, Vitek 2, and serology were used for bacterial identification. Random amplified polymorphic DNA (RAPD)-polymerase chain reaction (PCR) was applied to analyze the genetic relationships among Salmonella isolates. The isolation rate of Salmonella spp. was 21.1% (61/289). While the water samples constituted the highest rate (30.4%), a rate of
... Show MoreMultiple eliminations (de-multiple) are one of seismic processing steps to remove their effects and delineate the correct primary refractors. Using normal move out to flatten primaries is the way to eliminate multiples through transforming these data to frequency-wavenumber domain. The flatten primaries are aligned with zero axis of the frequency-wavenumber domain and any other reflection types (multiples and random noise) are distributed elsewhere. Dip-filter is applied to pass the aligned data and reject others will separate primaries from multiple after transforming the data back from frequency-wavenumber domain to time-distance domain. For that, a suggested name for this technique as normal move out- frequency-wavenumber domain
... Show MoreEconomic organizations operate in a dynamic environment, which necessitates the use of quantitative techniques to make their decisions. Here, the role of forecasting production plans emerges. So, this study aims to the analysis of the results of applying forecasting methods to production plans for the past years, in the Diyala State Company for Electrical Industries.
The Diyala State Company for Electrical Industries was chosen as a field of research for its role in providing distinguished products as well as the development and growth of its products and quality, and because it produces many products, and the study period was limited to ten years, from 2010 to 2019. This study used the descriptive approa
... Show MoreThe Asymmetrical Castellated concavely – curved soffit Steel Beams with RPC and Lacing Reinforcement improves compactness and local buckling (web and flange local buckling), vertical shear strength at gross section (web crippling and web yielding at the fillet), and net section ( net vertical shear strength proportioned between the top and bottom tees relative to their areas (Yielding)), horizontal shear strength in web post (Yielding), web post-buckling strength, overall beam flexure strength, tee Vierendeel bending moment and lateral-torsional buckling, as a result of steel section encasement. This study presents two concentrated loads test results for seven specimens Asymmetrical Castellated concavely – curved soffit Steel Be
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