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 %.
The detection for Single Escherichia Coli Bacteria has attracted great interest and in biology and physics applications. A nanostructured porous silicon (PS) is designed for rapid capture and detection of Escherichia coli bacteria inside the micropore. PS has attracted more attention due to its unique properties. Several works are concerning the properties of nanostructured porous silicon. In this study PS is fabricated by an electrochemical anodization process. The surface morphology of PS films has been studied by scanning electron microscope (SEM) and atomic force microscope (AFM). The structure of porous silicon was studied by energy-dispersive X-ray spectroscopy (EDX). Details of experimental methods and results are given and discussed
... Show MoreThe goal beyond this Research is to review methods that used to estimate Logistic distribution parameters. An exact estimators method which is the Moment method, compared with other approximate estimators obtained essentially from White approach such as: OLS, Ridge, and Adjusted Ridge as a suggested one to be applied with this distribution. The Results of all those methods are based on Simulation experiment, with different models and variety of sample sizes. The comparison had been made with respect to two criteria: Mean Square Error (MSE) and Mean Absolute Percentage Error (MAPE).
High cost of qualifying library standard cells on silicon wafer limits the number of test circuits on the test chip. This paper proposes a technique to share common load circuits among test circuits to reduce the silicon area. By enabling the load sharing, number of transistors for the common load can be reduced significantly. Results show up to 80% reduction in silicon area due to load area reduction.
Surface modeling utilizing Bezier technique is one of the more important tool in computer aided geometric design (CAD). The aim of this work is to design and implement multi-patches Bezier free-form surface. The technique has an effective contribution in technology domains and in ships, aircrafts, and cars industry, moreover for its wide utilization in making the molds. This work is includes the synthesis of these patches in a method that is allow the participation of these control point for the merge of the patches, and the confluence of patches at similar degree sides due to degree variation per patch. The model has been implemented to represent the surface. The interior data of the desired surfaces designed by M
... Show MoreThis paper derives the EDITRK4 technique, which is an exponentially fitted diagonally implicit RK method for solving ODEs . This approach is intended to integrate exactly initial value problems (IVPs), their solutions consist of linear combinations of the group functions and for exponentially fitting problems, with being the problem’s major frequency utilized to improve the precision of the method. The modified method EDITRK4 is a new three-stage fourth-order exponentially-fitted diagonally implicit approach for solving IVPs with functions that are exponential as solutions. Different forms of -order ODEs must be derived using the modified system, and when the same issue is reduced to a framework of equations that can be sol
... Show MoreThis paper proposes a new strategy to enhance the performance and accuracy of the Spiral dynamic algorithm (SDA) for use in solving real-world problems by hybridizing the SDA with the Bacterial Foraging optimization algorithm (BFA). The dynamic step size of SDA makes it a useful exploitation approach. However, it has limited exploration throughout the diversification phase, which results in getting trapped at local optima. The optimal initialization position for the SDA algorithm has been determined with the help of the chemotactic strategy of the BFA optimization algorithm, which has been utilized to improve the exploration approach of the SDA. The proposed Hybrid Adaptive Spiral Dynamic Bacterial Foraging (HASDBF)
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