Article Per Year (5 Year)
p-Index From 2021 - 2026
0.659
P-Index
This Author published in this journals
All Journal International Journal of Electrical and Computer Engineering Bulletin of Electrical Engineering and Informatics
Saad, Mohammed Ayad
Unknown Affiliation
Computer Science & IT Electrical & Electronics Engineering

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
Secured node detection technique based on artificial neural network for wireless sensor network Hasan, Bassam; Alani, Sameer; Saad, Mohammed Ayad
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 1: February 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i1.pp536-544

Abstract

The wireless sensor network is becoming the most popular network in the last recent years as it can measure the environmental conditions and send them to process purposes. Many vital challenges face the deployment of WSNs such as energy consumption and security issues. Various attacks could be subjects against WSNs and cause damage either in the stability of communication or in the destruction of the sensitive data. Thus, the demands of intrusion detection-based energy-efficient techniques rise dramatically as the network deployment becomes vast and complicated. Qualnet simulation is used to measure the performance of the networks. This paper aims to optimize the energy-based intrusion detection technique using the artificial neural network by using MATLAB Simulink. The results show how the optimized method based on the biological nervous systems improves intrusion detection in WSN. In addition to that, the unsecured nodes are affected the network performance negatively and trouble its behavior. The regress analysis for both methods detects the variations when all nodes are secured and when some are unsecured. Thus, Node detection based on packet delivery ratio and energy consumption could efficiently be implemented in an artificial neural network.
Performance evaluation of software defined networking into vanets system Taher, Younus Hasan; Alsaadi, Israa; Saad, Mohammed Ayad; Ali, Adnan Hussein; Essa, Mohammed; Rashid, Ahmed Hashim
Bulletin of Electrical Engineering and Informatics Vol 13, No 5: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i5.4675

Abstract

Vehicular ad hoc networks (VANETs) is an important topic nowadays. A lot of research deal and attracts consideration owing to potential for increasing traffic and travel efficiency, improving road safety for vehicles, providing convenience and comfort to both drivers and passengers. The need for a packet delivery ratio (PDR) and low delivery delay time in communication are the key elements in modern life especially when traveling in vehicles. To satisfy these demands; researchs in VANET systems aims to develop some new technologies. One of these technologies is using software-defined- network (SDN) to enhance communication between vehicles on the road. Because of this, project evaluates using SDN protocol with two most viable VANET protocols which are ad hoc on demand distance vector (AODV) and optimized link state routing (OLSR) in LTE communication. Two performance metrics are used to evaluate the performances, the PDR and the delivery delay time. The simulation is performed in the varying density network and varying speed vehicles. The simulation results show that SDN displays better performance than AODV and OLSR in both PDR and delivery delay time. SDN uses global views of SDN controller to determine the shortest route with the highest vehicle density. Additionally, it solves the local maximum issue and adds dense connectivity.
Jumping particle swarm optimization algorithm framework for content-based image retrieval system Bassel, Atheer; Jameel, Mohammed; Saad, Mohammed Ayad
Bulletin of Electrical Engineering and Informatics Vol 12, No 6: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i6.5024

Abstract

Content-based image retrieval (CBIR) has been studied well in the last decades in numerous research fields such as medicine, journalism, and private life. Applications of CBIR have been widely employed in medical images due to their direct impact on human life. With continues growing of digital libraries, there is a need for an efficient method to retrieve images from large datasets. In this paper, a new method was developed for CBIR based on the jumping particle swarm optimization (JPSO) algorithm. The proposed algorithm represents a developed instant of particle swarm optimization (PSO). However, JPSO the approach does not consider the velocity components to guide particle movements in the problem space. Instead of relying on inertia and velocity, intermittently random jumps (moves) occur from one solution to another within the discrete search space. To test the performance of the proposed algorithm, three types of medical image databases were used in the experiment which are the endoscopy 100, dental 100, and 50 skull image databases. The results show that the proposed algorithm could achieve high accuracy in image extraction and retrieve the accurate image category compared with other research works.
Co-Authors Alani, Sameer Ali, Adnan Hussein Alsaadi, Israa Bassel, Atheer Essa, Mohammed Hasan, Bassam Jameel, Mohammed Rashid, Ahmed Hashim Taher, Younus Hasan