Today the Genetic Algorithm (GA) tops all the standard algorithms in solving complex nonlinear equations based on the laws of nature. However, permute convergence is considered one of the most significant drawbacks of GA, which is known as increasing the number of iterations needed to achieve a global optimum. To address this shortcoming, this paper proposes a new GA based on chaotic systems. In GA processes, we use the logistic map and the Linear Feedback Shift Register (LFSR) to generate chaotic values to use instead of each step requiring random values. The Chaos Genetic Algorithm (CGA) avoids local convergence more frequently than the traditional GA due to its diversity. The concept is using chaotic sequences with LFSR to generate seed values for genetic algorithms, which can generate keys with a high degree of randomness. The quality of key (generated sequence) was tested using known standard tests, then a comparison table is presented to show the increase in ratios in the test before and after applying GA, demonstrating that the proposed system generates sequence (key) with high randomness degree, The proposed system achieved an increase in the randomness rate by four degrees on average and thus it solves the problem of repetition and linearity, Finally, The system is built in the Java environment.
In this paper, a numerical analysis was carried out using finite element method to analyse the mechanisms for streamer discharges. The hydrodynamic model was used with three charge carriers equations (positive ion, negative ion and electron) coupled with Poisson equation to simulate the dynamic of streamer discharge formation and propagation. The model was tested within a 2D axisymmetric tip-plate electrodes configuration using the transformer oil as the dielectric liquid. The distance between the electrodes was fixed at 1 mm and the applied voltage was 130 kV at 46 ns rising time. Simulation results showed that the time has a clear effect on the streamer propagation along the symmetry axis. In addition, it was observed that t
... Show MoreIn this paper, estimation of system reliability of the multi-components in stress-strength model R(s,k) is considered, when the stress and strength are independent random variables and follows the Exponentiated Weibull Distribution (EWD) with known first shape parameter θ and, the second shape parameter α is unknown using different estimation methods. Comparisons among the proposed estimators through Monte Carlo simulation technique were made depend on mean squared error (MSE) criteria
In this paper , an efficient new procedure is proposed to modify third –order iterative method obtained by Rostom and Fuad [Saeed. R. K. and Khthr. F.W. New third –order iterative method for solving nonlinear equations. J. Appl. Sci .7(2011): 916-921] , using three steps based on Newton equation , finite difference method and linear interpolation. Analysis of convergence is given to show the efficiency and the performance of the new method for solving nonlinear equations. The efficiency of the new method is demonstrated by numerical examples.
This book includes four main chapters: 1. Indefinite Integral. 2. Methods of Integration. 3. Definite Integral. 4. Multiple Integral. In addition to many examples and exercises for the purpose of acquiring the student's ability to think correctly in solving mathematical questions.
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
... Show MoreThe corrosion behavior of 2024 aluminium alloy was investigated in alkaline medium (pH=13) containing 0.6 . in absence and presence of different concentrations of three amino acids separately [Methionine, Glutamice acid and Lysine] as environmentally friendly corrosion inhibitors over the temperature range (293-308)K. Electrochemical polarization method using potentiostatic technique was employed. The inhibition efficiency increased with an increase of the inhibitor concentration but decreased with increase in temperature . The maximum efficiency value was found with lysine =80.4 of 293 k and 10 . concentration of lysine. The adsorption of the amino acids was found to obey Langmuir adsorption isotherm . Some thermodynamic parameter âˆ
... Show MoreCo-composting process can be acquired by combining organic fraction of municipal solid waste (OFMSW) with sewage sludge (SS) and mature compost (MC) as enhancement and bulking agent to overcome the problems of municipal solid waste and wastewater treatment plants besides the finally produced fertilizer usage for agriculture and horticulture. The effects of different mixture ratios of (OFMSW), (SS) and (MC) on the performance of composting process were investigated in this study. Piles of about 10 kg were prepared by mixing OFMSW, SS and MC in three different ratios (w/w) [OFMSW: SS: MC= 3:1:1, 3:2:1, and 3:3:1]. Results showed that the pile [3:1:1] was most beneficial to composting. The final compost products contained a
... Show MoreThis book includes three main chapters: 1. Functions & Their Derivatives. 2. Minimum, Maximum and Inflection points. 3. Partial Derivative. In addition to many examples and exercises for the purpose of acquiring the student's ability to think correctly in solving mathematical questions.
World statistics declare that aging has direct correlations with more and more health problems with comorbid conditions. As healthcare communities evolve with a massive amount of data at a faster pace, it is essential to predict, assist, and prevent diseases at the right time, especially for elders. Similarly, many researchers have discussed that elders suffer extensively due to chronic health conditions. This work was performed to review literature studies on prediction systems for various chronic illnesses of elderly people. Most of the reviewed papers proposed machine learning prediction models combined with, or without, other related intelligence techniques for chronic disease detection of elderly patie
... Show MoreTeen-Computer Interaction (TeenCI) stands in an infant phase and emerging in positive path. Compared to Human-Computer Interaction (generally dedicated to adult) and Child-Computer Interaction, TeenCI gets less interest in terms of research efforts and publications. This has revealed extensive prospects for researchers to explore and contribute in the region of computer design and evaluation for teen, in specific. As a subclass of HCI and a complementary for CCI, TeenCI that tolerates teen group, should be taken significant concern in the sense of its context, nature, development, characteristics and architecture. This paper tends to discover teen’s emotion contribution as the first attempt towards building a conceptual model for TeenC
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