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This Author published in this journals
All Journal International Journal of Electrical and Computer Engineering International Journal of Reconfigurable and Embedded Systems (IJRES) Buletin Ilmiah Sarjana Teknik Elektro Indonesian Journal of Electrical Engineering and Computer Science
Liqaa Saadi Mezher
Al-Mustansiriyah University
Computer Science & IT Economics, Econometrics & Finance Electrical & Electronics Engineering

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Mixed Hill Cipher methods with triple pass protocol methods Liqaa Saadi Mezher; Ayam Mohsen Abbass
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i5.pp4449-4457

Abstract

Hill Cipher is a reimbursement coding system that converts specific textual content codes into numbers and does no longer exchange the location of fixed symbols. The symbol modifications simplest in step with the English letter table inclusive of (26) characters handiest. An encoded Hill Cipher algorithm was used that multiplication the square matrix of the apparent text with a non-public key and then combined it with the Triple Pass Protocol method used to repeat the encryption three times without relying on a personal key. Also, you could decode the code and go back it to the express textual content. The cause of mixing algorithms is to cozy the message without any key change among the sender and the recipient.
Hamming neural network application with FPGA device Liqaa Saadi Mezher
International Journal of Reconfigurable and Embedded Systems (IJRES) Vol 10, No 1: March 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijres.v10.i1.pp37-46

Abstract

The Hamming neural network is a kind of counterfeit neural system that substance of two kinds of layers (feed forward layers and repetitive layer). In this study, two pattern entries are utilization in the binary number. In the first layer, two nerves were utilization as the pure line work. In the subsequent layer, three nerves and a positive line work were utilization. The Hamming Neural system calculation was also implemented in three reproduction strategies (logical gate technique, programming program encryption strategy and momentary square chart technique). In this study in programming of VHDL and FPGA machine was utilization.
Design and implementation hamming neural network with VHDL Liqaa Saadi Mezher
Indonesian Journal of Electrical Engineering and Computer Science Vol 19, No 3: September 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v19.i3.pp1469-1479

Abstract

Hamming Neural Network is type of artificial neural network consist of two types of layers (feed forward layers and recurrent layer). In this paper, two inputs of patterns in bianary number were used. In the first layer, two neurons and pure line function were used. In the second layer, three neurons and positive line function were used. Also applied Hamming Neural networks algorithm in three simulation methods (logical gate method, software program coding method and instant block diagram method). In this work in VHDL software program was used and FPGA hardware used.
Implementation of Vehicle Ad Hoc Networks for TPBFT on Latency and Fault Tolerance in Blockchain Systems Liqaa Saadi Mezher; Ayam Mohsen Abbass; Muna Hadi Saleh
Buletin Ilmiah Sarjana Teknik Elektro Vol. 8 No. 2 (2026): April
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v8i2.15227

Abstract

In this paper, examines the combination of Vehicle Ad hoc Networks (VANETs) and a new consensus mechanism called Trust Practical Byzantine Fault Tolerance (TPBFT) that is aimed at improving latency and fault tolerance of decentralized vehicular networks. The VANETs are described by dynamic topology and mobile node and pose special security as well as reliability issues especially in scalable networks. The conventional Byzantine Fault Tolerance (BFT) protocols are ineffective because they incur communication overhead and scaling problems. This paper suggests TPBFT as a powerful consensus mechanism that is suitable to use in vehicular networks and is effective even when malicious or malfunctioning nodes are involved. To model real-life traffic patterns and communication scenarios, the research methodology presupposes extensive simulations based on Simulation of Urban Mobility (SUMO) tool and real-world Open Street Map (OSM) data with the help of the Python program. The performance of TPBFT is strictly tested and compared to the classic Practical Byzantine Fault Tolerance (PBFT) protocol through the analysis of the consensus latency, system throughput, and fault tolerance resilience. The findings indicate TPBFT has a shorter consensus latency (16 to 28 ms) and a greater throughput compared to PBFT and was more effective in time-constrained vehicular usage. The present work makes TPBFT an effective decentralized mechanism that allows achieving low latency, high throughput, and high resistance to Byzantine failures, offering a safe platform to deploy the blockchain technology in smart transportation systems. The optimization of the energy consumption profile of network nodes, as well as the refinement of the consensus process on the application of blockchain-based VANET architecture into practice, will be the subject of future research.
Co-Authors Ayam Mohsen Abbass Muna Hadi Saleh