It is not available for us to go back in time and see plays old and it plays giants tragedy ancient Greek (Aeschylus, Sofokls, and yourbedes) through the eyes of a generation ago, and if we were able to go back to Ntegathm play it is certain that we will not taste or Nstassig for much of what we see from these offers will not afford the traditional religious rituals, which was accompanied also dance and music in the style of ancient Greek play was representing a large part of the theater see manifestations Can our eyes and ears we twentieth century audience to accept those appearances, and it was then?
Inevitably it will look like a museum bycollection not only. So we find ourselves in the light of the foregoing forced When you do rem

The technological development in the field of information and communication has been accompanied by the emergence of security challenges related to the transmission of information. Encryption is a good solution. An encryption process is one of the traditional methods to protect the plain text, by converting it into inarticulate form. Encryption implemented can be occurred by using some substitute techniques, shifting techniques, or mathematical operations. This paper proposed a method with two branches to encrypt text. The first branch is a new mathematical model to create and exchange keys, the proposed key exchange method is the development of Diffie-Hellman. It is a new mathematical operations model to exchange keys based on prime num

: The Aluminium (Al) material emerged as a plasmonic material in the wavelength ranges from the ultraviolet to the visible bands in different on-chip plasmonic applications. In this paper, we demonstrate the effect of using Al on the electromagnetic (EM) field distribution of a compact hybrid plasmonic waveguide (HPW) acting as a polarization rotator. We compare the performance of Al with other familiar metals that are widely used as plasmonic materials, which are Silver (Ag) and Gold (Au). Furthermore, we study the effect of reducing the geometrical dimensions of the used materials on the EM field distributions inside the HPW and, consequently, on the efficiency of the polarization rotation. We perform the study based o

This study is concerned with the effect of adding two kinds of ceramic materials on the mechanical properties of (Al-7%Si- 0.3%Mg) alloy, which are zirconia with particle size (20μm > P.S ≥ 0.1μm) and alumina with particle size (20μm > P.S ≥ 0.1μm) and adding them to the alloy with weight ratios (0.2, 0.4, 0.6, 0.8 and 1%). Stirring casting method has been used to make composite material by using vortex technique which is used to pull the particles to inside the melted metals and distributed them homogenously.

After that solution treatment was done to the samples at (520ºC) and artificial ageing at (170ºC) in different times, it has been noticed that the values of hardness is increased with the aging time of the o

This work includes design, implementation and testing of a microcontroller – based spectrum analyzer system. Both hardware and software structures are built to verify the main functions that are required by such system. Their design utilizes the permissible and available tools to achieve the main functions of the system in such a way to be modularly permitting any adaptation for a specific changing in the application environment. The analysis technique, mainly, depends on the Fourier analysis based methods of spectral analysis with the necessary required preconditioning processes. The software required for waveform analysis has been prepared. The spectrum of the waveform has been displayed, and the instrument accuracy has been checked.

The paper proposes a methodology for predicting packet flow at the data plane in smart SDN based on the intelligent controller of spike neural networks(SNN). This methodology is applied to predict the subsequent step of the packet flow, consequently reducing the overcrowding that might happen. The centralized controller acts as a reactive controller for managing the clustering head process in the Software Defined Network data layer in the proposed model. The simulation results show the capability of Spike Neural Network controller in SDN control layer to improve the (QoS) in the whole network in terms of minimizing the packet loss ratio and increased the buffer utilization ratio.

Many financial institutions invest their surplus funds in stocks, either to obtain dividends or for trading purposes and to obtain profits from the difference between the cost and the selling price, and investment in shares represents an important part of the financial position of financial institutions applying to the common accounting system of banks and insurance companies, in addition to their impact It is clear on the result of the activity of these institutions.The aim of the research is to define what the shares and their types are, and to indicate the accounting treatments needed to move towards the process of adopting the International Financial Reporting Standard No. (9) and its reflection on its financial statements. I

       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

مفهوم معامل الارتباط كمقياس يربط بين متغيرين هذا يجلب انتباهنا إلى موضوع الإحصاء في كل المستويات. أكثر من ذلك هناك ثلاث نقاط خاصة هي اعتيادياً نشدد عليها كما يأتي:-

(1 معامل الارتباط هو الدليل المعياري والذي قيمته لا تعتمد على قياسات  

    المتغيرات الأصلية.

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Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature