In this paper, the reliability and scheduling of maintenance of some medical devices were estimated by one variable, the time variable (failure times) on the assumption that the time variable for all devices has the same distribution as (Weibull distribution.

The method of estimating the distribution parameters for each device was the OLS method.

The main objective of this research is to determine the optimal time for preventive maintenance of medical devices. Two methods were adopted to estimate the optimal time of preventive maintenance. The first method depends on the maintenance schedule by relying on information on the cost of maintenance and the cost of stopping work and acc

After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings

Rationing is a commonly used solution for shortages of resources and goods that are vital for the citizens of a country. This paper identifies some common approaches and policies used in rationing as well asrisks that associated to suggesta system for rationing fuelwhichcan work efficiently. Subsequently, addressing all possible security risks and their solutions. The system should theoretically be applicable in emergency situations, requiring less than three months to implement at a low cost and minimal changes to infrastructure.

In this paper three techniques for image compression are implemented. The proposed techniques consist of three dimension (3-D) two level discrete wavelet transform (DWT), 3-D two level discrete multi-wavelet transform (DMWT) and 3-D two level hybrid (wavelet-multiwavelet transform) technique. Daubechies and Haar are used in discrete wavelet transform and Critically Sampled preprocessing is used in discrete multi-wavelet transform. The aim is to maintain to increase the compression ratio (CR) with respect to increase the level of the transformation in case of 3-D transformation, so, the compression ratio is measured for each level. To get a good compression, the image data properties, were measured, such as, image entropy (He), percent root-

An ingrowing toenail is a common problem affecting mainly adolescents and young adults, with a male predominance of 3:1. The disorder generally occurs in big toes. It is painful and often chronic and it affects work and social activities. Most patients initially complain of pain and later discharge, infection and difficulty in walking occur. The Objectives: The purpose of the study was to evaluate the efficacy and safety of (10600nm) CO2 laser in the treatment of ingrowing toe nail. Patients, Materials & Methods: This study was done in laser medicine research clinics from July 2013 to the end of December 2013; 10 patients including 7(70%) males and 3 (30%) females with age ranging from 18 years to 70 years with mean age of 44 years o

    This research aims to review the importance of estimating the nonparametric regression function using so-called Canonical Kernel which depends on re-scale the smoothing parameter, which has a large and important role in Kernel  and give the sound amount of smoothing .

We has been shown the importance of this method through the application of these concepts on real data refer to international exchange rates to the U.S. dollar against the Japanese yen for the period from January 2007 to March 2010. The results demonstrated preference the nonparametric estimator with Gaussian on the other nonparametric and parametric regression estima

4-methylaniline and its Schiff base derivative were intercalated into the Bentonite clay interlayers in a solid state reaction followed by a condensation reaction to produce two organo-clay composites. X-ray diffraction was used to identify the changes in basal spacing of montmorillonite layers which exhibited noticeable alteration before and after the formation of the composites. FT-IR spectra, on the other hand, were utilized for identifying the structural compositions of the prepared materials as well as the formation of the intercalated Schiff base derivative. The surface morphology of the composites was examined by Scanning Electron Microscopy SEM and Atomic Force Microscope AFM, which reflected some differences in the surface of prepa

       In this paper, we focus on designing feed forward neural network (FFNN) for solving Mixed Volterra – Fredholm Integral Equations (MVFIEs) of second kind in 2–dimensions. in our method, we present a multi – layers model consisting of a hidden layer which has five hidden units (neurons) and one linear output unit. Transfer function (Log – sigmoid) and training algorithm (Levenberg – Marquardt) are used as a sigmoid activation of each unit. A comparison between the results of numerical experiment and the analytic solution of some examples has been carried out in order to justify the efficiency and the accuracy of our method.

Abstract

This study aims to find the relationships between social capital (social network, social trust, shared goals) and knowledge sharing (knowledge Donating, knowledge collecting) as independent variables and their impact on improving the quality of educational services (academic staffs quality, Quality of teaching methods and study curriculums). This research is an important, because it attempts to identify the relationship between social capital and the knowledge sharing and their effect on improving the quality of educational service for universities. The study problem was determined in several questions related to the nature of the correlation relationship - the impact between the different independent variables (