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

In data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the well known algorithms used in data mining classification are Backpropagation Neural Network (BNN) and Naïve Bayesian (NB). This paper investigates the performance of these two classification methods using the Car Evaluation dataset. Two models were built for both algorithms and the results were compared. Our experimental results indicated that the BNN classifier yield higher accuracy as compared to the NB classifier but it is less efficient because it is time-consuming and difficult to analyze due to its black-box implementation.

To perform a secure evaluation of Indoor Design data, the research introduces a Cyber-Neutrosophic Model, which utilizes AES-256 encryption, Role-Based Access Control, and real-time anomaly detection. It measures the percentage of unpredictability, insecurity, and variance present within model features. Also, it provides reliable data security. Similar features have been identified between the final results of the study, corresponding to the Cyber-Neutrosophic Model analysis, and the cybersecurity layer helped mitigate attacks. It is worth noting that Anomaly Detection successfully achieved response times of less than 2.5 seconds, demonstrating that the model can maintain its integrity while providing privacy. Using neutrosophic sim

The Catharanthus roseus plant was extracted and converted to nanoparticles in this work. The Soxhlet method extracted alkaloid compounds from the plant Catharanthus roseus and converted them to the nanoscale. Chitosan polymer was used as a linking material and converted to Chitosan nanoparticles using Sodium TriPolyPhosphate (STPP). The extracted alkaloids were linked with Chitosan nanoparticles CSNPs by maleic anhydride to get the final product (CSNPs- Linker- alkaloids). The synthesized (CSNPs- Linker- alkaloids) was characterized using SEM spectroscopy UV–Vis., Zeta Potential, and HPLC High-Performance Liquid Chromatography. Scanning electron microscope (SEM) analysis shows that the Chitosan nanoparticles (CSNPs) have small dim

In this work, nanostructure zinc sulfide (ZnS) thin films at temperature of substrate 450 oC and thickness (120) nm have been produced by chemical spray pyrolysis method. The X-Ray Diffraction (XRD) measurements of the film showed that they have a polycrystalline structure and possessed a hexagonal phase with strong crystalline orientation of (103). The grain size was measured using scanning electron microscope (SEM) which was approximately equal to 80 nm. The linear optical measurements showed that ZnS nanostructure has direct energy gap. Nonlinear optical properties experiments were performed using Q-switched 532 nm Nd:YAG laser Z-scan system. The nonlinear refractive index (n2) and nonlinear absorption coefficient (β) estimated for Z

This study includes synthesis of some nitrogenous heterocyclic compounds linked to amino acid esters or heterocyclic amines that may have a potential  activity as antimicrobial and/or cytotoxic.  Quinolines are an important group of organic compounds that possess useful biological activity as antibacterial, antifungal and antitumor .8-Hydroxyquinoline (8-HQ) and numerous of its derivatives exhibit potent activities against fungi and bacteria which make them good candidates for the treatment of many parasitic and microbial infection diseases.

These pharmacological properties of quinolones  aroused our  interest in synthesizing several new compounds featuring heterocyclic rings of the quinoline derivatives linke

         Beryllium Zinc Oxide (Be_xZn_1-xO) ternary nano thin films were deposited using the pulsed laser deposition (PLD) technique under a vacuum condition of 10^-3 torr at room temperature on glass substrates with different films thicknesses, (300, 600 and 900 nm). UV-Vis spectra study found the optical band gap for Be_0.2Zn_0.8O to be  (3.42, 3.51 and 3.65 eV) for the (300, 600 and 900nm) film thicknesses, respectively which is larger than the value of zinc oxide ZnO (3.36eV) and smaller than that of beryllium oxide BeO (10.6eV). While the X-ray diffraction (XRD) pattern analysis of ZnO, BeO and Be _0.2 Zn _0.8 O powder and nano-thin films indicated a hexa

Some azo compounds were prepared by coupling the diazonium salts of amines with 2,4-dimethylphenol The structure of azo compounds were determined on the basis of elemental analyses, 1HNMR, FT-IR and UV-Vis spectroscopic techniques. Complexes of nickel(II) and copper(II) have been synthesized and characterized. The composition of complexes has been established by using flame atomic absorption, (C.H.N) Analysis, FT-IR and UV-Vis spectroscopic methods as well as conductivity magnetic susceptibility measurements. The nature of the complexes formed were studied following the mole ratio and continuous variation methods, Beer's law obeyed over a concentration range (1×10-4 - 3×10-4 M). High molar absorbtivity of the complex solutions were observ