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Design optimal neural network based on new LM training algorithm for solving 3D - PDEs
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In this article, we design an optimal neural network based on new LM training algorithm. The traditional algorithm of LM required high memory, storage and computational overhead because of it required the updated of Hessian approximations in each iteration. The suggested design implemented to converts the original problem into a minimization problem using feed forward type to solve non-linear 3D - PDEs. Also, optimal design is obtained by computing the parameters of learning with highly precise. Examples are provided to portray the efficiency and applicability of this technique. Comparisons with other designs are also conducted to demonstrate the accuracy of the proposed design.

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Publication Date
Mon Jan 01 2024
Journal Name
International Journal Of Research In Science And Technology
Encryption of Medical Image Based on Cascaded Design of AES Block Algorithm and Chaotic Map
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Security concerns in the transfer of medical images have drawn a lot of attention to the topic of medical picture encryption as of late. Furthermore, recent events have brought attention to the fact that medical photographs are constantly being produced and circulated online, necessitating safeguards against their inappropriate use. To improve the design of the AES algorithm standard for medical picture encryption, this research presents several new criteria. It was created so that needs for higher levels of safety and higher levels of performance could be met. First, the pixels in the image are diffused to randomly mix them up and disperse them all over the screen. Rather than using rounds, the suggested technique utilizes a cascad

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Publication Date
Fri Mar 31 2023
Journal Name
Journal Of Al-qadisiyah For Computer Science And Mathematics
A Cryptosystem for Database Security Based on RC4 Algorithm
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Because of vulnerable threats and attacks against database during transmission from sender to receiver, which is one of the most global security concerns of network users, a lightweight cryptosystem using Rivest Cipher 4 (RC4) algorithm is proposed. This cryptosystem maintains data privacy by performing encryption of data in cipher form and transfers it over the network and again performing decryption to original data. Hens, ciphers represent encapsulating system for database tables

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Publication Date
Tue Nov 01 2016
Journal Name
2016 International Conference On Advances In Electrical, Electronic And Systems Engineering (icaees)
Efficient routing algorithm for VANETs based on distance factor
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There has been a great deal of research into the considerable challenge of managing of traffic at road junctions; its application to vehicular ad hoc network (VANET) has proved to be of great interest in the developed world. Dynamic topology is one of the vital challenges facing VANET; as a result, routing of packets to their destination successfully and efficiently is a non-simplistic undertaking. This paper presents a MDORA, an efficient and uncomplicated algorithm enabling intelligent wireless vehicular communications. MDORA is a robust routing algorithm that facilitates reliable routing through communication between vehicles. As a position-based routing technique, the MDORA algorithm, vehicles' precise locations are used to establish th

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Publication Date
Mon May 11 2020
Journal Name
Baghdad Science Journal
A Cryptosystem for Database Security Based on TSFS Algorithm
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Implementation of TSFS (Transposition, Substitution, Folding, and Shifting) algorithm as an encryption algorithm in database security had limitations in character set and the number of keys used. The proposed cryptosystem is based on making some enhancements on the phases of TSFS encryption algorithm by computing the determinant of the keys matrices which affects the implementation of the algorithm phases. These changes showed high security to the database against different types of security attacks by achieving both goals of confusion and diffusion.

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Publication Date
Sat Oct 25 2025
Journal Name
Iet Networks
An Effective Technique of Zero‐Day Attack Detection in the Internet of Things Network Based on the Conventional Spike Neural Network Learning Method
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ABSTRACT<p>The fast evolution of cyberattacks in the Internet of Things (IoT) area, presents new security challenges concerning Zero Day (ZD) attacks, due to the growth of both numbers and the diversity of new cyberattacks. Furthermore, Intrusion Detection System (IDSs) relying on a dataset of historical or signature‐based datasets often perform poorly in ZD detection. A new technique for detecting zero‐day (ZD) attacks in IoT‐based Conventional Spiking Neural Networks (CSNN), termed ZD‐CSNN, is proposed. The model comprises three key levels: (1) Data Pre‐processing, in this level a thorough cleaning process is applied to the CIC IoT Dataset 2023, which contains both malicious and t</p> ... Show More
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Publication Date
Thu Jun 30 2011
Journal Name
Al-khwarizmi Engineering Journal
Performance Improvement of Neural Network Based RLS Channel Estimators in MIMO-OFDM Systems
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The objective of this study was tointroduce a recursive least squares (RLS) parameter estimatorenhanced by using a neural network (NN) to facilitate the computing of a bit error rate (BER) (error reduction) during channels estimation of a multiple input-multiple output orthogonal frequency division multiplexing (MIMO-OFDM) system over a Rayleigh multipath fading channel.Recursive least square is an efficient approach to neural network training:first, the neural network estimator learns to adapt to the channel variations then it estimates the channel frequency response. Simulation results show that the proposed method has better performance compared to the conventional methods least square (LS) and the original RLS and it is more robust a

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Publication Date
Tue Oct 16 2018
Journal Name
Springer Science And Business Media Llc
MOGSABAT: a metaheuristic hybrid algorithm for solving multi-objective optimisation problems
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Publication Date
Thu Nov 21 2019
Journal Name
Journal Of Engineering
A Neural Networks based Predictive Voltage-Tracking Controller Design for Proton Exchange Membrane Fuel Cell Model
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In this work, a new development of predictive voltage-tracking control algorithm for Proton Exchange Membrane Fuel Cell (PEMFCs) model, using a neural network technique based on-line auto-tuning intelligent algorithm was proposed. The aim of proposed robust feedback nonlinear neural predictive voltage controller is to find precisely and quickly the optimal hydrogen partial pressure action to control the stack terminal voltage of the (PEMFC) model for N-step ahead prediction. The Chaotic Particle Swarm Optimization (CPSO) implemented as a stable and robust on-line auto-tune algorithm to find the optimal weights for the proposed predictive neural network controller to improve system performance in terms of fast-tracking de

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Publication Date
Fri May 01 2020
Journal Name
Journal Of Physics: Conference Series
New Approach for Solving Two Dimensional Spaces PDE
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Abstract<p>In this paper, new approach based on coupled Laplace transformation with decomposition method is proposed to solve type of partial differential equation. Then it’s used to find the accurate solution for heat equation with initial conditions. Four examples introduced to illustrate the accuracy, efficiency of suggested method. The practical results show the importance of suggested method for solve differential equations with high accuracy and easy implemented.</p>
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Publication Date
Mon Oct 01 2018
Journal Name
2018 Ieee/acs 15th International Conference On Computer Systems And Applications (aiccsa)
Utilizing Hopfield Neural Network for Pseudo-Random Number Generator
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