In this study, the stress-strength model R = P(Y < X < Z)  is discussed as an important parts of reliability system by assuming that the random variables follow Invers Rayleigh Distribution. Some traditional estimation methods are used    to estimate the parameters  namely; Maximum Likelihood, Moment method, and Uniformly Minimum Variance Unbiased estimator and Shrinkage estimator using three types of shrinkage weight factors. As well as, Monte Carlo simulation are used to compare the estimation methods based on mean squared error criteria.  

Nanocrystalline copper sulphide (Cu2-xS) powders were synthesized by chemical precipitation from their aqueous solutions composed of different molar ratio of copper sulfate dehydrate (CuSO4.5H2O) and thiorea (NH2)2CS as source of Cu+2, S-2 ions respectively, and sodium ethylene diamine tetra acetic acid dehydrate (EDTA) as a complex agent. The compositions, morphological and structural properties of the nanopowders were characterized by energy dispersive spectroscopy (EDS), scanning electron microscope (SEM), and X-ray diffraction (XRD), respectively. The compositional results showed that the copper content was high and the Sulfur content was low for both CuS and Cu2S nanopowders. SEM images shows that all products consist of aggregate o

The annealing temperature (200–500 °C) effects of optical frequency response on the dielectric functions of sol–gel derived CuCoOx thin film coatings: experimental and modelling.

<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

In this research, a sensor for chemical solutions was designed and formed using optical fiber-based on a surface Plasmon resonance technology. A single-mode optical fiber with three different diameters (25, 45 and 65) µm was used, respectively.  The second layer of the low refractive fiber was replaced by gold, which was electrically deposited at 40 µm thickness. For each of the three types of optical fiber, different saline concentrations (different index of refraction) were used to evaluate the performance of the refractive index sensor (chemical sensor) by measuring its sensitivity and resolutions. The highest values we could get for these two parameters were 240mm/RIU, and 6*10^-5 RIU respectively, when the diameter of a