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

Most recognition system of human facial emotions are assessed solely on accuracy, even if other performance criteria are also thought to be important in the evaluation process such as sensitivity, precision, F-measure, and G-mean. Moreover, the most common problem that must be resolved in face emotion recognition systems is the feature extraction methods, which is comparable to traditional manual feature extraction methods. This traditional method is not able to extract features efficiently. In other words, there are redundant amount of features which are considered not significant, which affect the classification performance. In this work, a new system to recognize human facial emotions from images is proposed. The HOG (Histograms of Or

In view of the huge and speedy development of the information and communications technology sectores which cover all the life aspects. The traditional government started to adopt the Electronic Government Concept to deliver the information, services and product marketing to the beneficiaries through the Internet and Computer system. The E-government became inevitable necessity that should be applied in every country wishes to face the Modern technical development.

E-government is not on alternative of the traditional government but a supporter which can increase its efficiency by keeping away from the routine and Beaurucratic complexity, this will save the efforts, increase achievement and reduce costs, in addition to Provide Man

Countries have faced the challenges of high levels of public debt and seek to define the optimum limits to reduce risks to which the financial system can be exposed and its impact on the economy as a whole. Hence the importance of research in studying the impact of internal and external public debt components on indicators of stability of the financial system for the period 2005-2017 for the purpose of knowing the extent of the financial stability indicators response to the high level of the public debt from its optimum ratio, as the aim of the research is to estimate and analyze the dynamic relationship of short and long term between the components of public debt and indicators of financial stability using the (ARDL) model that

The research aims to study the effect of an increase in funding the Equity by issuing new common shares on revenues ordinary shares, despite the issuance and marketing costs and the introduction of new shareholders that companies incur when issuing new common shares but it is the most important methods used to finance the Equity is funding the common shares it provides money sufficient to finance the large investments of the company and enhance the confidence of dealers with the company, so I designed this research in order to identify the impact of increased funding Equity issue new common shares to common shares revenues.

This research has included some of the theoretical concepts to each of the Equity

The significant shift in the Fine Arts, who led the avant-garde movements and creative which appeared in the modern, specifically in the mid-nineteenth century and early twentieth century era path, embodied in a clear show of new aesthetic value rejects traditional methods put in shape and color qualities She described the movements subjectivity or no formal, was intended to determine the direct function of expression and speech language in the visual arts away from the representation and simulation of reality was accompanied by the appearance of those fine movements directed towards a global approach to design carries features and clear in its organizations formalism of the most important move away from the symmetry and the adoption of

Crime is considered as an unlawful activity of all kinds and it is punished by law. Crimes have an impact on a society's quality of life and economic development. With a large rise in crime globally, there is a necessity to analyze crime data to bring down the rate of crime. This encourages the police and people to occupy the required measures and more effectively restricting the crimes. The purpose of this research is to develop predictive models that can aid in crime pattern analysis and thus support the Boston department's crime prevention efforts. The geographical location factor has been adopted in our model, and this is due to its being an influential factor in several situations, whether it is traveling to a specific area or livin

Nutrient agar medium with various concentrations of cefotaxime was used for isolation spontaneous mutants from wild type strain of P.aeruginosa PHA-1. Eighty-two mutants were successfully isolated with the viable count 52×107 , these mutants were confirmed as spontaneous not physiological adaption mutants by reculture on the same medium. Then, wild type PHA-1 and mutants were examined for production pyocyanin; a blue greenish pigment was clearly noticed on King A medium. Remarkably the mutant strain named S300-8 was distinguished in productivity in comparison with wild type strain PHA-1; the amount of pigment was 56.0667mg/l and 74.53mg/l respectively. In addition, pyocyanin produced by mutant strain S300-8 revealed a potent efficacy again

Researchers need to understand the differences between parametric and nonparametric regression models and how they work with available information about the relationship between response and explanatory variables and the distribution of random errors. This paper proposes a new nonparametric regression function for the kernel and employs it with the Nadaraya-Watson kernel estimator method and the Gaussian kernel function. The proposed kernel function (AMS) is then compared to the Gaussian kernel and the traditional parametric method, the ordinary least squares method (OLS). The objective of this study is to examine the effectiveness of nonparametric regression and identify the best-performing model when employing the Nadaraya-Watson