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All Journal Bulletin of Electrical Engineering and Informatics Indonesian Journal of Electrical Engineering and Computer Science
Mohanad Sameer Jabbar
Albayan University
Electrical & Electronics Engineering

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Improving WSNs execution using energy-efficient clustering algorithms with consumed energy and lifetime maximization Mohanad Sameer Jabbar; Samer Saeed Issa; Adnan Hussein Ali
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 2: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i2.pp1122-1131

Abstract

Wireless sensor networks (WSNs) has a major designing feature representing by energy. Specifically, the sensor nodes have limited battery energy and are deployed remote from base station (BS); therefore, the actual enhancement dealing with energy turns into the Clustering routing protocols fundamentals which concerned in network lifetime improvement. Though, unexpected and energy insensible of the clusters head (CH) selection is not the best of WSN for greatly lowering lifetime network. A presentation article of an WSNs incoming routing approach using a mix of the fuzzy approach besides hybrid energy-efficient distributing (HEED) algorithm for increasing the lifetime and node’s energy. The FLH-P proposal algorithm is split into two parts. The stable election protocol HEED approach is used to arrange WSNs into clusters. Then, using a combination of fuzzy inference and the low energy adaptive clustering hierarchy (LEACH) algorithm, metrics like residual energy, minimal hops, with node traffic counts are taken into account. A comparison of FLH-P proposal algorithm with LEACH algorithm, fuzzy approach, and HEED utilizing identical guiding standards was used for demonstrating the performance of the suggested technique from where corresponding consumed energy as well as lifetime maximization. The suggested routing strategy considerably increases the network lifetime and transmitted packet throughput, according to simulation findings.
A crypto-steganography healthcare management: towards a secure communication channel for data COVID-19 updating Mohanad Sameer Jabbar; Samer Saeed Issa
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 2: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i2.pp1102-1112

Abstract

Nowadays, secure transmission massive volumes of medical data (such as COVID-19 data) are crucial but yet difficult in communication between hospitals. The confidentiality and integrity are two concerning challenges must be addressing to healthcare data. Also, the data availability challenge that related to network fail which may reason concerns to the arrival the COVID-19 data. The second challenge solved with the different tools such as virtual privet network (VPN) or blockchain technology. Towards overcoming the aforementioned for first challenges, a new scheme based on crypto steganography is proposed to secure updating (COVID-19) data. Three main contributions have been consisted within this study. The first contribution is responsible to encrypt the COVID-19 data prior to the embedding process, called hybrid cryptography (HC). The second contribution is related with the security in random blocks and pixels selection in hosting image. Three iterations of the Hénon Map function used with this contribution. The last contribution called inversing method which used with embedding process. Three important measurements were used the peak signal-to-noise ratio (PSNR), the Histogram analysis and structural similarity index measure (SSIM). Based on the findings, the present scheme gives evidence to increase capacity, imperceptibility, and security to ovoid the existing methods problem.
MPPT implementation and simulation using developed P&O algorithm for photovoltaic system concerning efficiency Asaad A. H. AlZubaidi; Laith Abdul Khaliq; Hassan Salman Hamad; Waleed Khalid Al-Azzawi; Mohanad Sameer Jabbar; Thaer Abdulwahhab Shihab
Bulletin of Electrical Engineering and Informatics Vol 11, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i5.3949

Abstract

The great development witnessed by investments in renewable energy has made it the focus of researchers’ attention in order to increase its efficiency. This is due to the increase in demand for electrical energy due to rapid technological growth, increase in population numbers, and high fuel prices that are used in the production of traditional electrical energy, but it suffers from a problem that is greatly affected by two factors, namely, the change in the intensity of solar irradiation and temperature, which makes its electrical characteristics non-linear, which causes a decrease in its efficiency. To address the efficiency problem, the researchers developed several techniques for tracking the MPP point and extracting the maximum energy from the solar panels under various measurement conditions. Maximum power point tracking technology (MPPT) technology is the most widely used technology in solar energy systems. In this article, MPPT technology is simulated using MATLAB/Simulink for the purposes of extracting maximum power and managing the duty cycle of a DC-DC buck converter. The performance of the photovoltaic system under various irradiance fluctuations and settings of constant temperature could well be determined using simulation results. Under standard and varied test settings, allowing the inverter to convert over 99% of the electricity provided by the solar panels.
Developed cluster-based load-balanced protocol for wireless sensor networks based on energy-efficient clustering Mohanad Sameer Jabbar; Samer Saeed Issa
Bulletin of Electrical Engineering and Informatics Vol 12, No 1: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i1.4226

Abstract

One of the most pressing issues in wireless sensor networks (WSNs) is energy efficiency. Sensor nodes (SNs) are used by WSNs to gather and send data. The techniques of cluster-based hierarchical routing significantly considered for lowering WSN’s energy consumption. Because SNs are battery-powered, face significant energy constraints, and face problems in an energy-efficient protocol designing. Clustering algorithms drastically reduce each SNs energy consumption. A low-energy adaptive clustering hierarchy (LEACH) considered promising for application-specifically protocol architecture for WSNs. To extend the network's lifetime, the SNs must save energy as much as feasible. The proposed developed cluster-based load-balanced protocol (DCLP) considers for the number of ideal cluster heads (CHs) and prevents nodes nearer base stations (BSs) from joining the cluster realization for accomplishing sufficient performances regarding the reduction of sensor consumed energy. The analysis and comparison in MATLAB to LEACH, a well-known cluster-based protocol, and its modified variant distributed energy efficient clustering (DEEC). The simulation results demonstrate that network performance, energy usage, and network longevity have all improved significantly. It also demonstrates that employing cluster-based routing protocols may successfully reduce sensor network energy consumption while increasing the quantity of network data transfer, hence achieving the goal of extending network lifetime.
Behavioral drowsiness detection system execution based on digital camera and MTCNN deep learning Ali Hassan Majeed; Adnan Hussein Ali; Aqeel A. Al-Hilali; Mohanad Sameer Jabbar; Safiye Ghasemi; Mohammed G. S. Al-Safi
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.v12i6.5252

Abstract

Drowsy driving is a major cause of road accidents worldwide, necessitating the development of effective drowsiness detection systems. Each year, there are more accidents and fatalities than ever before for a variety of causes. For instance, there were 22,952 fatalities and 79,545 injuries as a result of nearly 66,500 vehicle accidents in the last 10 years. In this paper, we propose a novel approach for detecting drowsiness based on behavioral cues captured by a digital camera and utilizing the multi-task cascaded convolutional neural network (MTCNN) deep learning algorithm. A high-resolution camera records visual indications like closed or open eye movement to base the technique on the driver's behavior. In order to measure a car user's weariness in the present frame of reference, eyes landmarks are evaluated, which results in the identification of a fresh constraint known as "eyes aspect ratio." A picture with a frame rate of 60 frames per second (f/s) and a resolution of 4,320 eyeballs was used. The accuracy of sleepiness detection was more than 99.9% in excellent lighting and higher than 99.8% in poor lighting, according to testing data. The current study did better in terms of sleepiness detection accuracy than a lot of earlier investigations. 
Co-Authors Adnan Hussein Ali Ali Hassan Majeed Aqeel A. Al-Hilali Asaad A. H. AlZubaidi Hassan Salman Hamad Laith Abdul Khaliq Mohammed G. S. Al-Safi Safiye Ghasemi Samer Saeed Issa Samer Saeed Issa Samer Saeed Issa Thaer Abdulwahhab Shihab Waleed Khalid Al-Azzawi