In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial lung CT-scans into two groups (COVID-19 and NonCOVID-19) had been proposed. A dataset used is 960 slices of CT scan collected from Iraqi patients /Ibn Al-Nafis teaching hospital. The performance metrics are used in this study (accuracy, recall, precision, and F1 scores). The results indicate that the proposed approach generated a high-quality model for the collected dataset, with an overall accuracy of 98.95% and an overall recall of 97 %.
Aromaticity, antiaromaticity and chemical bonding in the ground (S0), first singlet excited (S1) and lowest triplet (T1) electronic states of disulfur dinitride, S2N2, were investigated by analysing the isotropic magnetic shielding, σiso(r), in the space surrounding the molecule for each electronic state. The σiso(r) values were calculated by state-optimized CASSCF/cc-pVTZ wave functions with 22 electrons in 16 orbitals constructed from gauge-including atomic orbitals (GIAOs). The S1 and T1 electronic states were confirmed as 11Au and 13B3u, respectively, through linear response CC3/aug-cc-pVTZ calculations of the vertical excitation energies for eight singlet (S1–S8) and eight triplet (T1–T8) electronic states. The aromaticities of S
... Show MoreSteel-concrete-steel (SCS) structural element solutions are rising due to their advantages over conventional reinforced concrete in terms of cost and strength. The impact of SCS sections with various core materials on the structural performance of composites has not yet been fully explored experimentally, and in this work, both slag and polypropylene fibers were incorporated in producing eco-friendly steel-concrete-steel composite sections. This study examined the ductility, ultimate strength, failure modes, and energy absorption capacities of steel-concrete-steel filled with eco-friendly concrete, enhanced by polypropylene fiber (PPF) to understand its impact on modern structural projects. Eco-friendly concrete was produced by the partial
... Show MoreA theoretical and protection study was conducted of the corrosion behavior of carbon steel surface with different concentrations of the derivative (Quinolin-2-one), namly (1-Amino-4,7-dimethyl-6-nitro-1H-quinolin-2-one (ADNQ2O)). Theoretically, Density Functional Theory (DFT) of B3LYP/ 6-311++G (2d, 2p) level was used to calculate the optimized geometry, physical properties and chemical inhibition parameters, with the local reactivity to predict both the reactive centers and to locate the possible sites of nucleophilic and electrophilic attacks, in vacuum, and in two solvents (DMSO and H2O), all at the equilibrium geometry. Experimentally, the inhibition efficiencies (%IE) in the saline solution (of 3.5%) NaCl were st
... Show MoreFisetin is a plant flavonoid found in strawberries and other fruits and vegetables such as apples, persimmons, and onions. It has many pharmacological effects like anti-inflammatory, antioxidant, cardioprotective, neuroprotective, and anti-carcinogenicity which are attributed to its ability to reduce oxidative stress which considers the main reason for different disease conditions. Genotoxicity refers to the genetic material destruction within the cell which can be caused by different chemicals as well as radiation. The present study evaluates the effect of orally-administered fisetin daily for seven constitutive days on genotoxicity induced by cyclophosphamide in rats’ bone marrow and spleen cells. Results showed that fisetin exh
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Multivariate GARCH Models take several forms , the most important DCC dynamic conditional correlation, and CCC constant conditional correlation , The Purpose of this research is the Comparison for both Models.Using three financial time series which is a series of daily Iraqi dinar exchange rate indollar, Global daily Oil price in dollar and Global daily gold price in dollarfor the period from 01/01/2014 till 01/01/2016, Where it has been transferred to the three time series returns to get the Stationarity, some tests were conducted including Ljung-Box , JarqueBera , Multivariate ARCH to Returns Series and Residuals Series for both models In Comparison
... Show MoreIn this research want to make analysis for some indicators and it's classifications that related with the teaching process and the scientific level for graduate studies in the university by using analysis of variance for ranked data for repeated measurements instead of the ordinary analysis of variance . We reach many conclusions for the
important classifications for each indicator that has affected on the teaching process. &nb
... Show MoreThis century is witnessing changes in various fields,which have become a challenge to the enterprises in the contemporary business environment, the most important of which is the importance of measurement and disclosure of the role of knowledge capital in the transition to the knowledge economy, which is no longer the land and labor and physical capital resources the basic. Knowledge-based capital has emerged that provides the enterprise with an area of excellence and enhances its position to achieve competitive advantage. The research tackled the concept, objectives, components and importance of knowledge capital, which is fundamental in knowledge management, creating value added and enhancing competitiveness, as well as an
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