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Intrusion detection method for internet of things based on the spiking neural network and decision tree method
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The prevalence of using the applications for the internet of things (IoT) in many human life fields such as economy, social life, and healthcare made IoT devices targets for many cyber-attacks. Besides, the resource limitation of IoT devices such as tiny battery power, small storage capacity, and low calculation speed made its security a big challenge for the researchers. Therefore, in this study, a new technique is proposed called intrusion detection system based on spike neural network and decision tree (IDS-SNNDT). In this method, the DT is used to select the optimal samples that will be hired as input to the SNN, while SNN utilized the non-leaky integrate neurons fire (NLIF) model in order to reduce latency and minimize devices’ power usage. Also, a rand order code (ROC) technique is used with SNN to detect cyber-attacks. The proposed method is evaluated by comparing its performance with two other methods: IDS-DNN and IDS-SNNTLF by using three performance metrics: detection accuracy, latency, and energy usage. The simulation results have shown that IDS-SNNDT attained low power usage and less latency in comparison with IDS-DNN and IDS-SNNTLF methods. Also, IDS-SNNDT has achieved high detection accuracy for cyber-attacks in contrast with IDS-SNNTLF.

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Publication Date
Wed Oct 28 2020
Journal Name
Iraqi Journal Of Science
Approximate Solutions for Systems of Volterra Integro-differential Equations Using Laplace –Adomian Method
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Some modified techniques are used in this article in order to have approximate solutions for systems of Volterra integro-differential equations. The suggested techniques are the so called Laplace-Adomian decomposition method and Laplace iterative method. The proposed methods are robust and accurate as can be seen from the given illustrative examples and from the comparison that are made with the exact solution.

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Publication Date
Sun Sep 24 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Approximate Solution for Fuzzy Differential Algebraic Equations of Fractional Order Using Adomian Decomposition Method
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      In this paper we shall prepare an  sacrificial solution for fuzzy differential algebraic equations of fractional order (FFDAEs) based on the Adomian decomposition method (ADM) which is proposed to solve (FFDAEs) . The blurriness will appear in the boundary conditions, to be fuzzy numbers. The solution of the proposed pattern of  equations is studied in the form of a convergent series with readily computable components. Several examples are resolved as  clarifications, the numerical outcomes are obvious that the followed approach is simple to perform and precise when utilized to (FFDAEs).

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Publication Date
Mon Feb 04 2019
Journal Name
Iraqi Journal Of Physics
Microscopic study of nuclear structure for some Si-isotopes using Skyrme-Hartree-Fock-method
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In this paper the nuclear structure of some of Si-isotopes namely, 28,32,36,40Si have been studied by calculating the static ground state properties of these isotopes such as charge, proton, neutron and mass densities together with their associated rms radii, neutron skin thicknesses, binding energies, and charge form factors. In performing these investigations, the Skyrme-Hartree-Fock method has been used with different parameterizations; SkM*, S1, S3, SkM, and SkX. The effects of these different parameterizations on the above mentioned properties of the selected isotopes have also been studied so as to specify which of these parameterizations achieves the best agreement between calculated and experimental data. It can be ded

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Publication Date
Wed Oct 20 2021
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Zenali Iteration Method For Approximating Fixed Point of A δZA - Quasi Contractive mappings
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This article will introduce a new iteration method called the zenali iteration method for the approximation of fixed points. We show that our iteration process is faster than the current leading iterations  like Mann, Ishikawa, oor, D- iterations, and *-  iteration for new contraction mappings called  quasi contraction mappings. And we  proved that all these iterations (Mann, Ishikawa, oor, D- iterations and *-  iteration) equivalent to approximate fixed points of  quasi contraction. We support our analytic proof by a numerical example, data dependence result for contraction mappings type  by employing zenali iteration also discussed.

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Publication Date
Thu Jul 20 2023
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Constructing RKM-Method for Solving Fractional Ordinary Differential Equations of Fifth-Order with Applications
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This paper sheds the light on the vital role that fractional ordinary differential equations(FrODEs) play in the mathematical modeling and in real life, particularly in the physical conditions. Furthermore, if the problem is handled directly by using numerical method, it is a far more powerful and efficient numerical method in terms of computational time, number of function evaluations, and precision. In this paper, we concentrate on the derivation of the direct numerical methods for solving fifth-order FrODEs  in one, two, and three stages. Additionally, it is important to note that the RKM-numerical methods with two- and three-stages for solving fifth-order ODEs are convenient, for solving class's fifth-order FrODEs. Numerical exa

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Publication Date
Thu Oct 20 2016
Journal Name
Sociological Methods & Research
Mean Monte Carlo Finite Difference Method for Random Sampling of a Nonlinear Epidemic System
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In this article, a numerical method integrated with statistical data simulation technique is introduced to solve a nonlinear system of ordinary differential equations with multiple random variable coefficients. The utilization of Monte Carlo simulation with central divided difference formula of finite difference (FD) method is repeated n times to simulate values of the variable coefficients as random sampling instead being limited as real values with respect to time. The mean of the n final solutions via this integrated technique, named in short as mean Monte Carlo finite difference (MMCFD) method, represents the final solution of the system. This method is proposed for the first time to calculate the numerical solution obtained fo

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Publication Date
Sun Jan 01 2012
Journal Name
International Journal Of Astronomy And Astrophysics
Study the Radial Expansion of SN 1987A Using Counting Pixels Method
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Publication Date
Tue Dec 22 2020
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Cost Management of construction industries according to the fast-track method
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Construction projects have become a changing dramatically in recent decades and that the goal of the beneficiaries of the implementation of structural project is to complete the work with less time and within the cost of the specific and the best possible quality may sometimes happen that highlights the importance of time on the rest of the items at the implementation of projects for various reasons, including the need to use the project as soon as possible possible change rapidly to customer's requests, but the high cost of the project represents the biggest obstacle for entrepreneurs with its effects on the quality and the time workers, and is a measure of those elements in monetary terms is the key to integration between them, so the

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Publication Date
Mon Jul 01 2013
Journal Name
Journal Of Kerbala University
study the optimum conditions of synthesis AgNP by chemical reduction method
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Abstract :- In this paper, silver nanoparticles had been prepared by chemical reduction method. Many tests had been done to it such as UV-Visible spectrophotometer, XRD, AFM&SEM test. finally an attempt had been done to get the optimum condition to control the grain size of silver Nanoparticles by variation the heating period and other parameters which has an effect in silver Nanoparticles synthesis process. in this method we can get a silver nanoparticles in the size range from 52 to 97 nm.

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Publication Date
Fri Jun 01 2007
Journal Name
Journal Of Al-nahrain University Science
ON THE GREEDY RADIAL BASIS FUNCTION NEURAL NETWORKS FOR APPROXIMATION MULTIDIMENSIONAL FUNCTIONS
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The aim of this paper is to approximate multidimensional functions by using the type of Feedforward neural networks (FFNNs) which is called Greedy radial basis function neural networks (GRBFNNs). Also, we introduce a modification to the greedy algorithm which is used to train the greedy radial basis function neural networks. An error bound are introduced in Sobolev space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result is published in [16]).

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