Patients infected with the COVID-19 virus develop severe pneumonia, which typically results in death. Radiological data show that the disease involves interstitial lung involvement, lung opacities, bilateral ground-glass opacities, and patchy opacities. This study aimed to improve COVID-19 diagnosis via radiological chest X-ray (CXR) image analysis, making a substantial contribution to the development of a mobile application that efficiently identifies COVID-19, saving medical professionals time and resources. It also allows for timely preventative interventions by using more than 18000 CXR lung images and the MobileNetV2 convolutional neural network (CNN) architecture. The MobileNetV2 deep-learning model performances were evaluated

Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Deci

Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Decision Tre

Botnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet

The attention of civil society organizations, governments and international non-governmental organizations in recent years has focused on the acute practices adopted by companies with the aim of reducing the tax burden, and the results of these practices have a negative impact on the tax revenues that the state uses to finance public needsThe aim of the research is to measure the impact of the voluntary disclosure of companies on tax planning for the period from 2011 to 2015 and the research community is in the General Tax Authority. The research sample is 6 companies within the private sector in the financial, banking, insurance and industrial fields. The research was based on a special model to measure the optional disclosure,

Abstract

      The changes that happened in the environment of  business have great effects upon organizations with different activities specially the banks  which requires the existence of an able opinion  resources can adapt with the changes . Accordingly importance put upon  intellectual  capital which become one of the basic resources for organizations and one of success and growth elements with the availability of expertise , skills and capability of making  essential changes in different process due to the presentation of innovations and creations of the to support banks activities .Therefore the intellectual  capital represents the more r

Organizations nowadays, whether public or private organizations, productive or service (such as banks), face major challenges as a result of rapid and continuous changes, and in front of these challenges traditional management operations and tools become unable to make the organization able to work, which makes it imperative for these organizations to follow the methods and management practices, including the proposed knowledge risk management and strategic direction so that it can elevate its actions at the level of developments in reality, in the sense that these organizations and in the light of environmental developments to characterize their strategic direction as an intellectual approach characterized by mo