This paper deals with the estimation of the stress strength reliability for a component which has a strength that is independent on opposite lower and upper bound stresses, when the stresses and strength follow Inverse Kumaraswamy Distribution. D estimation approaches were applied, namely the maximum likelihood, moment, and shrinkage methods. Monte Carlo simulation experiments were performed to compare the estimation methods based on the mean squared error criteria.

Abstract: This study aims to investigate the backscattering electron coefficient for SixGe1-x/Si heterostructure sample as a function of primary electron beam energy (0.25-20 keV) and Ge concentration in the alloy. The results obtained have several characteristics that are as follows: the first one is that the intensity of the backscattered signal above the alloy is mainly related to the average atomic number of the SixGe1-x alloy. The second feature is that the backscattering electron coefficient line scan shows a constant value above each layer at low primary electron energies below 5 keV. However, at 5 keV and above, a peak and a dip appeared on the line scan above Si-Ge alloy and Si, respectively, close to the interfacing line

ZnxNi1-x-yCuyFe2O4 spinel ferrite were prepared using solid state reaction method with (y=0.1, x=0.2, 0.3, 0.4, 0.5, 0.6 ) . X-ray diffraction with diffractometer CuKα analysis have been carried out and studied showing single phase spinel cubic with space group FD͞ 3m for all prepared samples . Lattice parameters and crystallite grain size and x-ray density(ρx-ray) bulk density and porosity ratio's were calculated and showed good agreement with the international data reported in the scientific research's.

Environmental controls, especially for temperature and humidity, are essential to maintain the safety, purity and effectiveness of drugs. The measurement of humidity can be particularly difficult and important in climatic and thermostatic chambers (warehouses, ovens, cold rooms, fridges, drying rooms, insulated boxes, etc.).
The old method of monitoring and qualification of climatic and thermostatic chambers requires placing a defined number of recorders, then programming and store them. After that, to examine the values recorded to revolve the status of the climatic and thermostatic chambers, if they are compliant or not-complaint at any time, so all that goes to waste time and efficiency of values.
We can do the monitoring and qu

With its rapid spread, the coronavirus infection shocked the world and had a huge effect on billions of peoples' lives. The problem is to find a safe method to diagnose the infections with fewer casualties. It has been shown that X-Ray images are an important method for the identification, quantification, and monitoring of diseases. Deep learning algorithms can be utilized to help analyze potentially huge numbers of X-Ray examinations. This research conducted a retrospective multi-test analysis system to detect suspicious COVID-19 performance, and use of chest X-Ray features to assess the progress of the illness in each patient, resulting in a "corona score." where the results were satisfactory compared to the benchmarked techniques.  T

Cancer constitutes a serious disease and a major health problem in worldwide, a lot of people were infected with this dangerous disease, Therefore, there must be attention to this disease through diagnosis and prevention there. In this study, we determined the relationship between the Cancer and the concentration of trace elements by comparing the concentration trace elements for infected and non-infected people. The trace elements concentrations to nails are one of the diagnostic criteria that easily to detect and dated this disease without any harm to the patient. Eight nails samples were collected from cancer-infected and eight samples from non-infected of the relatives of first-degree. All samples were measured by the concentrations

<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

Background: Radiotherapy, is therapy using ionizing radiation in order to deliver an optimal dose of either particulate or electromagnetic radiation to a particular area of the body with minimal damage to normal tissues. The source of radiation may be outside the body of the patient (external beam irradiation) or it may be an isotope that has been implanted or instilled into abnormal tissue or a body cavity. Called also radiotherapy. The aim of work studies the relationship between the depth dose and the high photon xray energies (6MeV and 10MeV). Patients and methods: in our work, we studied the dose distribution in water phantom given at different depths (zero-18) cm deep at1cm intervals treated with different field size (5×5-,10×1

We studied the effect of Ca- doping on the properties of Bi-based superconductors by
adding differ ent amounts of CaO
to the Bi
2
Sr2La2-xCaxCu3O10+δ
compound. consequently, we
obtained three samples A,B and C with x=0.0, 0.4 and 0.8 respectively. The usual solid-state
reaction method has been applied under optimum conditions. The x-ray diffraction analy sis
showed that the samples A and B have tetragonal structures conversely the sample C has an
orthorhombic structure. In addition XRD analysis show that decreasing the c-axis lattice
constant and thus decreasing the ratio c/a for samples A,B and C resp ectively. The X-ray
florescence proved that the compositions of samples A,B and C with the ra

Absorption properties (Attenuation coefficient, the percentage of the reflection, and the percentage of absorption) in x-band have been investigated in this paper for novolac – alumina- graphite mixture. Using novolac as the host material, the samples are prepared with alumina concentrations (5%,10%,15%,20%) and graphite concentrations (5%,10%) with thickness equal to 2.2mm .Network analyzer produced by HP-8510 was used in this work to measure the attenuation coefficient. The samples (3, 5) have good attenuation of wave with bandwidth of frequencies. The maximum of attenuation is -25dB at frequency 10.28GHZ in sample (3) which has concentrations (80%novolac,10%alumina,and 5% graphite) and -24 dB at frequency 10.56GHZ in sample (5) whic