In the present work a dynamic analysis technique have been developed to investigate and characterize the quantity of elastic module degradation of cracked cantilever plates due to presence of a defect such as surface of internal crack under free vibration. A new generalized technique represents the first step in developing a health monitoring system, the effects of such defects on the modal frequencies has been the main key quantifying the elasticity modulii due to presence any type of un-visible defect. In this paper the finite element method has been used to determine the free vibration characteristics for cracked cantilever plate (internal flaws), this present work achieved by different position of crack. Stiffness re

The applications of Multilevel Converter (MLC) are increased because of the huge demand for clean power; especially these types of converters are compatible with the renewable energy sources. In addition, these new types of converters have the capability of high voltage and high power operation. A Nine-level converter in three modes of implementation; Diode Clamped-MLC (DC-MLC), Capacitor Clamped-MLC (CC-MLC), and the Modular Structured-MLC (MS-MLC) are analyzed and simulated in this paper. Various types of Multicarrier Modulation Techniques (MMTs) (Level shifted (LS), and Phase shifted (PS)) are used for operating the proposed Nine level - MLCs. Matlab/Simulink environment is used for the simulation, extracting, and ana

In recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve

The research dealt with the topic ' the aesthetics of design shape of interior spaces for the syndicate of physicians' as it reflects visions evolving to the level of tasting and positive interpretation for the space of work to be on a high design level.The research consisting of four chapters as follow; The first chapter examined the problem of the research contracted in the following question: Have the design shapes any role in achieving and showing the aesthetic side for the syndicate of physicians? so the goal of the research was showing the aesthetics of design shape of interior spaces for the syndicate of physicians, The chapter also included the objective spatial and temporal limits of research .Finally the terms were specified. T

The dangers of (Israel's) integration with Arab countries in the middle east region will threaten the Arab security structure dimension, which the latter makes the Arab regional system vulnerable for distortion due to its nominal and symbolic value which is far from the Arab self and questioning with its effectiveness in comparing with the real capabilities to Arab countries in achieving the common targets. So, how to assess the different problems that began to hit the structure of the Arab regional system? and how to pledge an allegiance after putting forward what is known as the American Deal of the Century for the administration of former US President Donald Trump for making another step toward normalization with (Israel)?. The reveal

       In this work, the fractional damped Burger's equation (FDBE) formula    = 0,

       In this work, the fractional damped Burger's equation (FDBE) formula    = 0,

Abstract Software-Defined Networking (commonly referred to as SDN) is a newer paradigm that develops the concept of a software-driven network by separating data and control planes. It can handle the traditional network problems. However, this excellent architecture is subjected to various security threats. One of these issues is the distributed denial of service (DDoS) attack, which is difficult to contain in this kind of software-based network. Several security solutions have been proposed recently to secure SDN against DDoS attacks. This paper aims to analyze and discuss machine learning-based systems for SDN security networks from DDoS attack. The results have indicated that the algorithms for machine learning can be used to detect DDoS

KE Sharquie, AA Noaimi, WK Al-Janabi, Journal of Cosmetics, Dermatological Sciences and Applications, 2013