<p>Combating the COVID-19 epidemic has emerged as one of the most promising healthcare the world's challenges have ever seen. COVID-19 cases must be accurately and quickly diagnosed to receive proper medical treatment and limit the pandemic. Imaging approaches for chest radiography have been proven in order to be more successful in detecting coronavirus than the (RT-PCR) approach. Transfer knowledge is more suited to categorize patterns in medical pictures since the number of available medical images is limited. This paper illustrates a convolutional neural network (CNN) and recurrent neural network (RNN) hybrid architecture for the diagnosis of COVID-19 from chest X-rays. The deep transfer methods used were VGG19, DenseNet121, InceptionV3, and Inception-ResNetV2. RNN was used to classify data after extracting complicated characteristics from them using CNN. The VGG19-RNN design had the greatest accuracy of all of the networks with 97.8% accuracy. Gradient-weighted the class activation mapping (Grad-CAM) method was then used to show the decision-making areas of pictures that are distinctive to each class. In comparison to other current systems, the system produced promising findings, and it may be confirmed as additional samples become available in the future. For medical personnel, the examination revealed an excellent alternative way of diagnosing COVID-19.</p>
Addition of bioactive materials such as Titanium oxide (TiO2), and incorporation of bio inert ceramic such as alumina (Al2O3), into polyetheretherketone (PEEK) has been adopted as an effective approach to improve bone-implant interfaces. In this paper, hot pressing technique has been adopted as a production method. This technique gave a homogenous distribution of the additive materials in the proposed composite biomaterial. Different compositions and compounding temperatures have been applied to all samples. Mechanical properties and animal model have been studied in all different production conditions. The results of these new TiO2/Al2O3/PEEK biocomposites with different
... Show MoreThis paper proposes two hybrid feature subset selection approaches based on the combination (union or intersection) of both supervised and unsupervised filter approaches before using a wrapper, aiming to obtain low-dimensional features with high accuracy and interpretability and low time consumption. Experiments with the proposed hybrid approaches have been conducted on seven high-dimensional feature datasets. The classifiers adopted are support vector machine (SVM), linear discriminant analysis (LDA), and K-nearest neighbour (KNN). Experimental results have demonstrated the advantages and usefulness of the proposed methods in feature subset selection in high-dimensional space in terms of the number of selected features and time spe
... Show MoreIn this research a study of the effect of quality, sequential and directional layers for three types of fibers are:(Kevlar fibers-49 woven roving and E- glass fiber woven roving and random) on the fatigue property using epoxy as matrix. The test specimens were prepared by hand lay-up method the epoxy resin used as a matrix type (Quick mast 105) in prepared material composit . Sinusoidal wave which is formed of variable stress amplitudes at 15 Hz cycles was employed in the fatigue test ( 10 mm )and (15mm) value 0f deflection arrival to numbers of cycle failure limit, by rotary bending method by ( S-N) curves this curves has been determined ( life , limit and fa
... Show MoreNon uniform channelization is a crucial task in cognitive radio receivers for obtaining separate channels from the digitized wideband input signal at different intervals of time. The two main requirements in the channelizer are reconfigurability and low complexity. In this paper, a reconfigurable architecture based on a combination of Improved Coefficient Decimation Method (ICDM) and Coefficient Interpolation Method (CIM) is proposed. The proposed Hybrid Coefficient Decimation-Interpolation Method (HCDIM) based filter bank (FB) is able to realize the same number of channels realized using (ICDM) but with a maximum decimation factor divided by the interpolation factor (L), which leads to less deterioration in stop band at
... Show MoreThe concept of the active contour model has been extensively utilized in the segmentation and analysis of images. This technology has been effectively employed in identifying the contours in object recognition, computer graphics and vision, biomedical processing of images that is normal images or medical images such as Magnetic Resonance Images (MRI), X-rays, plus Ultrasound imaging. Three colleagues, Kass, Witkin and Terzopoulos developed this energy, lessening “Active Contour Models” (equally identified as Snake) back in 1987. Being curved in nature, snakes are characterized in an image field and are capable of being set in motion by external and internal forces within image data and the curve itself in that order. The present s
... Show MoreIn this work, some mechanical properties of the polymer coating were improved by preparing a hybrid system containing Graphene (GR) of different weight percentages (0.25, 0.5, 1, and 2wt%) with 5wt% carbon fibres (CF) and added to a polymer coating by using casting method. The properties were improved as GR was added with further improvement on adding 5wt% of CF. The impact strength of acrylic polymer with GR increases with increasing weight ratio of GR; maximum value was obtained when the polymer coating was incorporated with 1wt% GR and 5wt% CF. The impact strength of acrylic polymer with GR and GR/CF composites incorporated with GR at 1wt% and CF at 5wt%. Hardness increase with increasing weight ratio of Gr and a significant imp
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