Iraqi Journal for Electrical and Electronic Engineering
type: channel
publisher: College of Engineering, University of Basrah
language: en
publication name: Iraqi Journal for Electrical and Electronic Engineering
issn: 1814-5892
items: An Enhanced Deployment Approach of Adaptive Equalizer for Multipath Fading Channels
items: Feasibility Study of Off-Grid Rural Electrification in Iraq: A Case Study of the AL-Teeb Area
items: Chameleon Chaotic System-Based Audio Encryption Algorithm and FPGA Implementation
items: Design and Implementation of Monitoring System for Lethal Events of High-Risk COVID-19 Patients
items: License Plate Detection and Recognition in Unconstrained Environment Using Deep Learning
items: Mobile Robot Navigation with Obstacles Avoidance by Witch of Agnesi Algorithm with Minimum Power
items: Design of Dual-Passband Microstrip Filtering Antenna Using Dual-Mode Closed Loop Resonators and Defected Ground Structure
items: A Comparative Study of Deep Learning Methods-Based Object/Image Categorization
items: Design and Simulation of Reduced Switch 31-Level Multilevel Inverter Topology for PV Application
items: LabVIEW Venus Flytrap ANFIS Inverse Control System for Microwave Heating Cavity
items: The Effect of Sample Size on the Interpolation Algorithm of Frequency Estimation
items: Advanced Neural Network-Based Load Frequency Regulation in Two-Area Power Systems
items: Optimal Assimilation of Distributed Generation in Radial Power Distribution System Using Hybrid Approach
items: Enhancing PV Fault Detection Using Machine Learning: Insights from a Simulated PV System
items: Design and Validation of Super-Capacitor Assisted Photovoltaic Array for Roof-Top Solar Powered Electric Vehicle Applications
items: Design and FPGA Implementation of a Hyper-Chaotic System for Real-time Secure Image Transmission
items: An Efficient EHR Secure Exchange Among Healthcare Servers Using Light Weight Scheme
items: PLC/HMI Based Portable Workbench for PLC and Digital Logic Learning and Application Development
items: A Review of Algorithms and Platforms for Offloading Decisions in Mobile Cloud Computing
items: Patients Monitoring and Data Management System for Hospitals
items: Design and Implementation of the Soft Robot’s End-Effecter
items: Robust Low Pass Filter-PID Controller for 2-DOF Helicopter System
items: Lower Limb Rehabilitation Exoskeleton Robots, A review
items: The Beam Squint Effects in Antenna Arrays at Millimeter Bands
items: Integration of Fuzzy Logic and Neural Networks for Enhanced MPPT in PV Systems Under Partial Shading Conditions

An Enhanced Deployment Approach of Adaptive Equalizer for Multipath Fading Channels
type: item
description: Inter-symbol interference (ISI) exhibits major distortion effect often appears in digital storage and wireless communica- tion channels. The traditional decision feedback equalizer (DFE) is an efficient approach of mitigating the ISI effect using appropriate digital filter to subtract the ISI. However, the error propagation in DFE is a challenging problem that degrades the equalization due to the aliasing distorted symbols in the feedback section of the traditional DFE. The aim of the proposed approach is to minimize the error propagation and improve the modeling stability by incorporating adequate components to control the training and feedback mode of DFE. The proposed enhanced DFE architecture consists of a decision and controller components which are integrated on both the transmitter and receiver sides of communication system to auto alternate the DFE operational modes between training and feedback state based on the quality of the received signal in terms of signal-to-noise ratio SNR. The modeling architecture and performance validation of the proposed DFE are implemented in MATLAB using a raised-cosine pulse filter on the transmitter side and linear time-invariant channel model with additive gaussian noise. The equalizer capability in compensating ISI is evaluated during different operational stages including the training and DFE based on different channel distortion characteristics in terms of SNR using both 0.75 and 1.5 symbol duration in unit delay fraction of FIR filter. The simulation results of eye-diagram pattern showed significant improvement in the DFE equalizer when using a lower unit delay fraction in FIR filter for better suppressing the overlay trails of ISI. Finally, the capability of the proposed approach to mitigate the ISI is improved almost double the number of symbol errors compared to the traditional DFE.
subject: Articles
  topic: section
subject: Adaptive Equalizers
  topic: keywords
subject: Decision Feedback Learning
  topic: keywords
subject: Fading Channels
  topic: keywords
subject: Signal-to-Noise Ratio
  topic: keywords
subject: Electrical Engineering
  topic: disciplines
creator: Haider Al-Kanan
rights: Copyright (c) 2025 Iraqi Journal for Electrical and Electronic Engineering
date: 2025-05-02
publication date: 2025-05-02
starting page: 264
ending page: 273
doi: 10.37917/ijeee.21.1.25

Feasibility Study of Off-Grid Rural Electrification in Iraq: A Case Study of the AL-Teeb Area
type: item
description: In developing nations, such as Iraq, supplying power to isolated and rural border areas that are not connected to the grid continues to be a problem. At present, fossil fuels, which are significant causes of pollution, supply around 80% of the world’s energy demands. Nonetheless, drastically reducing reliance on fossil fuels has many reasons, including depleting global fossil fuel supplies, increasing costs and growing energy needs. The present study examines the electrical requirements of the Al-Teeb area, a city situated in the eastern region of Iraq, close to the Iranian border. This region has not been researched despite its tourism and oil significance. Despite the unpredictable expansion of many isolated locations in Iraq in recent years, the number of generation stations has not changed. Supplying energy to these places will require considerable time and money. Photovoltaics (PV), wind turbines (WTs), diesel generators (DGs), batteries and converters combined on the basis of their compatibility under three distinct scenarios comprise the system’s components. Considering the lowest net present cost (NPC) and cost of energy (COE) of all the examined scenarios, PV, WTs, batteries and DGs are the most economical solutions for the Al-Teeb area. Number of PV (1,215), number of WTs (59), number of DGs (13), number of batteries (3,138), number of converters (47), COE (0.155 US$/kWh), NPC (14.2 million US$) and initial capital cost (4.91 million US$) are revealed by the results. Finally, the results are confirmed using another global optimization method, namely, modified particle swarm optimization.
subject: Original Article
  topic: section
subject: Diesel Generators
  topic: keywords
subject: Feasibility Study
  topic: keywords
subject: HOMER Pro
  topic: keywords
subject: Al-Teeb Area
  topic: keywords
subject: Photovoltaics
  topic: keywords
subject: Wind Turbines
  topic: keywords
subject: Electrical Engineering
  topic: disciplines
creator: Husam A. Salim
creator: Jabbar R. Rashed
rights: Copyright (c) 2025 Iraqi Journal for Electrical and Electronic Engineering
date: 2025-04-24
publication date: 2025-04-24
starting page: 251
ending page: 263
doi: 10.37917/ijeee.21.1.24

Chameleon Chaotic System-Based Audio Encryption Algorithm and FPGA Implementation
type: item
description: Audio encryption has gained popularity in a variety of fields including education, banking over the phone, military, and private audio conferences. Data encryption algorithms are necessary for processing and sending sensitive information in the context of secure speech conversations. In recent years, the importance of security in any communications system has increased. To transfer data securely, a variety of methods have been used. Chaotic system-based encryption is one of the most significant encryption methods used in the field of security. Chaos-based communication is a promising application of chaos theory and nonlinear dynamics. In this research, a chaotic algorithm for the new chaotic chameleon system was proposed, studied, and implemented. The chameleon chaotic system has been preferred to be employed because it has the property of changing from self-excited (SA) to hidden-attractor (HA) which increases the complexity of the system dynamics and gives strength to the encryption algorithm. A chaotic chameleon system is one in which, depending on the parameter values, the chaotic attractor alternates between being a hidden attractor and a self-excited attractor. This is an important feature, so it is preferable to use it in cryptography compared to other types of chaotic systems. This model was first implemented using a Field Programmable Gate Array (FPGA), which is the first time it has been implemented in practical applications. The chameleon system model was implemented using MATLAB Simulink and the Xilinx System Generator model. Self-excited, hidden, and coexisting attractors are shown in the proposed system. Vivado software was used to validate the designs, and Xilinx ZedBoard Zynq-7000 FPGA was used to implement them. The dynamic behavior of the proposed chaotic system was also studied and analysis methods, including phase portrait, bifurcation diagrams, and Lyapunov exponents. Assessing the quality of the suggested method by doing analyses of many qualit…
subject: Original Article
  topic: section
subject: Audio Encryption Algorithm
  topic: keywords
subject: FPGA
  topic: keywords
subject: Chameleon Chaotic System
  topic: keywords
subject: Self-Excited Attractor
  topic: keywords
subject: Hidden Attractor
  topic: keywords
subject: Electrical Engineering
  topic: disciplines
creator: Alaa Shumran
creator: Abdul-Basset A. Al-Hussein
rights: Copyright (c) 2025 Iraqi Journal for Electrical and Electronic Engineering
date: 2025-02-06
publication date: 2025-02-06
starting page: 232
ending page: 250
doi: 10.37917/ijeee.21.1.23

Design and Implementation of Monitoring System for Lethal Events of High-Risk COVID-19 Patients
type: item
description: The monitoring of COVID-19 patients has been greatly aided by the Internet of Things (IoT). Vital signs, symptoms, and mobility data can be gathered and analyzed by IoT devices, including wearables, sensors, and cameras. This information can be utilized to spot early infection symptoms, monitor the illness’s development, and stop the virus from spreading. It’s critical to take vital signs of hospitalized patients in order to assess their health. Although early warning scores are often calculated three times a day, they might not indicate decompensation symptoms right away. Death rates are higher when deterioration is not properly diagnosed. By employing wearable technology, these ongoing assessments may be able to spot clinical deterioration early and facilitate prompt therapies. This research describes the use of Internet of Things (IoT) to follow fatal events in high-risk COVID-19 patients. These patients’ vital signs, which include blood pressure, heart rate, respiration rate, blood oxygen level, and fever, are taken and fed to a central server on a regular basis so that information may be processed, stored, and published instantly. After processing, the data is utilized to monitor the patients’ condition and send Short Message Service (SMS) alerts when the patients’ vital signs rise above predetermined thresholds. The system’s design, which is based on two ESP32 controllers, sensors for the vital signs listed above, and a gateway, provides real-time reports, high-risk alerts, and patient status information. Clinicians, the patient’s family, or any other authorized person can keep an eye on and follow the patient’s status at any time and from any location. The main contribution in this work is the designed algorithm used in the gateway and the manner in which this gateway collects, analyze, process, and send the patient’s data to the IoT server from one side and the manner in which the gateway deals with the IoT server in the other side. The proposed method leads…
subject: Original Article
  topic: section
subject: Covid-19
  topic: keywords
subject: ESP32
  topic: keywords
subject: Healthcare
  topic: keywords
subject: IoT
  topic: keywords
subject: Message Queuing Telemetry Transport (MQTT)
  topic: keywords
subject: Ubidots
  topic: keywords
subject: Electrical Engineering
  topic: disciplines
creator: Suhad Qasim Naeem
creator: Ammar Ibrahim Majeed
creator: Noor Nateq ALfaisaly
rights: Copyright (c) 2025 Iraqi Journal for Electrical and Electronic Engineering
date: 2025-02-06
publication date: 2025-02-06
starting page: 221
ending page: 231
doi: 10.37917/ijeee.21.1.22

License Plate Detection and Recognition in Unconstrained Environment Using Deep Learning
type: item
description: Real-time detection and recognition systems for vehicle license plates present a significant design and implementation challenge, arising from factors such as low image resolution, data noise, and various weather and lighting conditions.This study presents an efficient automated system for the identification and classification of vehicle license plates, utilizing deep learning techniques. The system is specifically designed for Iraqi vehicle license plates, adapting to various backgrounds, different font sizes, and non-standard formats. The proposed system has been designed to be integrated into an automated entrance gate security system. The system’s framework encompasses two primary phases: license plate detection (LPD) and character recognition (CR). The utilization of the advanced deep learning technique YOLOv4 has been implemented for both phases owing to its adeptness in real-time data processing and its remarkable precision in identifying diminutive entities like characters on license plates. In the LPD phase, the focal point is on the identification and isolation of license plates from images, whereas the CR phase is dedicated to the identification and extraction of characters from the identified license plates. A substantial dataset comprising Iraqi vehicle images captured under various lighting and weather circumstances has been amassed for the intention of both training and testing. The system attained a noteworthy accuracy level of 95.07%, coupled with an average processing time of 118.63 milliseconds for complete end-to-end operations on a specified dataset, thus highlighting its suitability for real-time applications. The results suggest that the proposed system has the capability to significantly enhance the efficiency and reliability of vehicle license plate recognition in various environmental conditions, thus making it suitable for implementation in security and traffic management contexts.
subject: Original Article
  topic: section
subject: Big Data
  topic: keywords
subject: Deep Learning
  topic: keywords
subject: Intelligent Systems
  topic: keywords
subject: License Plate Detection
  topic: keywords
subject: License Plate Recognition
  topic: keywords
subject: Electrical Engineering
  topic: disciplines
creator: Heba Hakim
creator: Zaineb Alhakeem
creator: Hanadi Al-Musawi
creator: Mohammed A. Al-Ibadi
creator: Alaa Al-Ibadi
rights: Copyright (c) 2025 Iraqi Journal for Electrical and Electronic Engineering
date: 2025-02-06
publication date: 2025-02-06
starting page: 210
ending page: 220
doi: 10.37917/ijeee.21.1.21

Mobile Robot Navigation with Obstacles Avoidance by Witch of Agnesi Algorithm with Minimum Power
type: item
description: Obstacle avoidance in mobile robot path planning represents an exciting field of robotics systems. There are numerous algorithms available, each with its own set of features. In this paper a Witch of Agnesi curve algorithm is proposed to prevent a collision by the mobile robot’s orientation beyond the obstacles which represents an important problem in path planning, further, to achieve a minimum arrival time by following the shortest path which leads to minimizing power loss. The proposed approach considers the mobile robot’s platform equipped with the LIDAR 360o sensor to detect obstacle positions in any environment of the mobile robot. Obstacles detected in the sensing range of the mobile robot are dealt with by using the Witch of Agnesi curve algorithm, this establishes the obstacle’s apparent vertices’ virtual minimum bounding circle with minimum error. Several Scenarios are implemented and considered based on the identification of obstacles in the mobile robot environment. The proposed system has been simulated by the V-REP platform by designing several scenarios that emulate the behavior of the robot during the path planning model. The simulation and experimental results show the optimal performance of the mobile robot during navigation is obtained as compared to the other methods with minimum power loss and also with minimum error. It’s given 96.3 percent in terms of the average of the total path while the Bezier algorithm gave 94.67 percent. While in experimental results the proposed algorithm gave 93.45 and the Bezier algorithm gave 92.19 percent.
subject: Original Article
  topic: section
subject: Mobile Robot Navigation
  topic: keywords
subject: Obstacle Avoidance
  topic: keywords
subject: Lidar Sensor
  topic: keywords
subject: Path Planning
  topic: keywords
subject: Witch of Agnesi
  topic: keywords
subject: Minimum Power
  topic: keywords
subject: Electrical Engineering
  topic: disciplines
creator: Bayadir A. Issa
creator: Hayder D. Almukhtar
creator: Qabeela Q. Thabit
creator: Mofeed T. Rashid
rights: Copyright (c) 2025 Iraqi Journal for Electrical and Electronic Engineering
date: 2025-02-04
publication date: 2025-02-04
starting page: 199
ending page: 209
doi: 10.37917/ijeee.21.1.20

Design of Dual-Passband Microstrip Filtering Antenna Using Dual-Mode Closed Loop Resonators and Defected Ground Structure
type: item
description: This paper presents a new microstrip dual-mode closed-loop resonator (DMCLR) that is used to design lower insertion loss and better transmission dual-passband filtering antenna. The dual passband center frequencies of the presented filtering antenna are located at foI=5.52 GHz and foII= 6.65 GHz. The presented dual-mode, dual-passband microstrip filtering antenna results are simulated and optimized by using Computer Simulation Technology (CST) software and defected ground structure technique. Three modes of dual-mode resonators have been utilized to design the dual- passband microstrip filtering antenna and compare their results. The presented dual-mode, dual-passband microstrip filtering antenna is established on FR-4 epoxy dielectric material which has a relative permittivity εr= 4.3 which has height thickness h = 1.6 mm and loss tangent tan δ=0.002. Defected Ground Structure (DGS) technique has been utilized to improve the performance of the presented dual-mode, dual-passband microstrip filtering antenna.
subject: Original Article
  topic: section
subject: Filtering antenna
  topic: keywords
subject: CST
  topic: keywords
subject: DGS
  topic: keywords
subject: Dual-passband
  topic: keywords
subject: Dual-mode resonator
  topic: keywords
subject: Electrical Engineering
  topic: disciplines
creator: Mohammed K. Alkhafaji
creator: Mohammed Al-Momin
rights: Copyright (c) 2025 Iraqi Journal for Electrical and Electronic Engineering
date: 2024-12-27
publication date: 2024-12-27
starting page: 162
ending page: 167
doi: 10.37917/ijeee.21.1.16

A Comparative Study of Deep Learning Methods-Based Object/Image Categorization
type: item
description: In recent years, there has been a considerable rise in the applications in which object or image categorization is beneficial for example, analyzing medicinal images, assisting persons to organize their collections of photos, recognizing what is around self-driving vehicles, and many more. These applications necessitate accurately labeled datasets, in their majority involve an extensive diversity in the types of images, from cats or dogs to roads, landscapes, and so forth. The fundamental aim of image categorization is to predict the category or class for the input image by specifying to which it belongs. For human beings, this is not a considerable thing, however, learning computers to perceive represents a hard issue that has become a broad area of research interest, and both computer vision techniques and deep learning algorithms have evolved. Conventional techniques utilize local descriptors for finding likeness between images, however, nowadays; progress in technology has provided the utilization of deep learning algorithms, especially the Convolutional Neural Networks (CNNs) to auto-extract representative image patterns and features for classification The fundamental aim of this paper is to inspect and explain how to utilize the algorithms and technologies of deep learning to accurately classify a dataset of images into their respective categories and keep model structure complication to a minimum. To achieve this aim, must focus precisely and accurately on categorizing the objects or images into their respective categories with excellent results. And, specify the best deep learning-based models in image processing and categorization. The developed CNN-based models have been proposed and a lot of pre-training models such as (VGG19, DenseNet201, ResNet152V2, MobileNetV2, and InceptionV3) have been presented, and all these models are trained on the Caltech-101 and Caltech-256 datasets. Extensive and comparative experiments were conducted on this dataset, and the…
subject: Original Article
  topic: section
subject: Image Recognition
  topic: keywords
subject: Deep Learning Methods
  topic: keywords
subject: VGG19
  topic: keywords
subject: DenseNet201
  topic: keywords
subject: ResNet152V2
  topic: keywords
subject: MobileNetV2
  topic: keywords
subject: InceptionV3
  topic: keywords
subject: Developed CNN Models
  topic: keywords
subject: Electrical Engineering
  topic: disciplines
creator: Saad Albawi
creator: Layth Kamil Almajmaie
creator: Ali J. Abboud
rights: Copyright (c) 2025 Iraqi Journal for Electrical and Electronic Engineering
date: 2024-12-27
publication date: 2024-12-27
starting page: 168
ending page: 177
doi: 10.37917/ijeee.21.1.17

Design and Simulation of Reduced Switch 31-Level Multilevel Inverter Topology for PV Application
type: item
description: This paper presents a design of a low cost, low loss 31-level multilevel inverter (MLI) topology with a reduce the number of switches and power electronic devices. The increase in the levels of MLI leads to limiting the THD to the desired value. The 31-level output voltage is created using four PV sources with a specific ratio. The SPWM is used to control the gating signals for the switches of MLI. The PV system is integrated into the MLI using a boost converter to maximize the power capacity of the solar cells and the Incremental Conductance (IC) algorithm is employed for maximum power point tracking (MPPT) of the PV system. Simulation results of 31-level MLI indicate the THD of voltage and current waveforms are 3.73% within an acceptable range of IEEE standards.
subject: Original Article
  topic: section
subject: Incremental Conductance (IC) Algorithm
  topic: keywords
subject: Multilevel Inverter (MLI)
  topic: keywords
subject: Photovoltaic (PV)
  topic: keywords
subject: Total Harmonic Distortion (THD)
  topic: keywords
subject: Electrical Engineering
  topic: disciplines
creator: Abdulhasan F. Abdulhasan
creator: Fatimah F. Jaber
creator: Yousif Abdulwahab Kheerallah
rights: Copyright (c) 2025 Iraqi Journal for Electrical and Electronic Engineering
date: 2024-12-27
publication date: 2024-12-27
starting page: 178
ending page: 188
doi: 10.37917/ijeee.21.1.18

LabVIEW Venus Flytrap ANFIS Inverse Control System for Microwave Heating Cavity
type: item
description: Growing interests in nature-inspired computing and bio-inspired optimization techniques have led to powerful tools for solving learning problems and analyzing large datasets. Several methods have been utilized to create superior performance-based optimization algorithms. However, certain applications, like nonlinear real-time, are difficult to explain using accurate mathematical models. Such large-scale combination and highly nonlinear modeling problems are solved by usage of soft computing techniques. So, in this paper, the researchers have tried to incorporate one of the most advanced plant algorithms known as Venus Flytrap Plant algorithm(VFO) along with soft-computing techniques and, to be specific, the ANFIS inverse model-Adaptive Neural Fuzzy Inference System for controlling the real-time temperature of a microwave cavity that heats oil. The MATLAB was integrated successfully with the LabVIEW platform. Wide ranges of input and output variables were experimented with. Problems were encountered due to heating system conditions like reflected power, variations in oil temperature, and oil inlet absorption and cavity temperatures affecting the oil temperature, besides the temperature’s effect on viscosity. The LabVIEW design followed and the results figure in the performance of the VFO- Inverse ANFIS controller.
subject: Original Article
  topic: section
subject: Venus Flytrap Algorithm
  topic: keywords
subject: ANFIS
  topic: keywords
subject: Microwave
  topic: keywords
subject: LabVIEW
  topic: keywords
subject: Electrical Engineering
  topic: disciplines
creator: Wasan A. Wali
creator: Atheel K. Abdul Zahra
creator: Hanady S. Ahmed
rights: Copyright (c) 2025 Iraqi Journal for Electrical and Electronic Engineering
date: 2025-01-05
publication date: 2025-01-05
starting page: 189
ending page: 198
doi: 10.37917/ijeee.21.1.19

The Effect of Sample Size on the Interpolation Algorithm of Frequency Estimation
type: item
description: Fast and accurate frequency estimation is essential in various engineering applications, including control systems, communications, and resonance sensing systems. This study investigates the effect of sample size on the interpolation algorithm of frequency estimation. In order to enhance the accuracy of frequency estimation and performance, we describe a novel method that provides a number of approaches for calculating and defending the sample size for of the window function designs, whereas, the correct choice of the type and the size of the window function makes it possible to reduce the error. Computer simulation using Matlab / Simulink environment is performed to investigate the proposed procedure’s performance and feasibility. This study performs the comparison of the interpolation algorithm of frequency estimation strategies that can be applied to improve the accuracy of the frequency estimation. Simulation results shown that the proposed strategy with the Parzen and Flat-top gave remarkable change in the maximum error of frequency estimation. They perform better than the conventional windows at a sample size equal to 64 samples, where the maximum error of frequency estimation is 2.13e-2 , and 2.15e-2 for Parzen and Flat-top windows, respectively. Moreover, the efficiency and performance of the Nuttall window also perform better than other windows, where the maximum error is 7.76×10-5 at a sample size equal to 8192. The analysis of simulation result showed that when using the proposed strategy to improve the accuracy of the frequency estimation, it is first essential to evaluate what is the maximum number of samples that can be obtained, how many spectral lines should be used in the calculations, and only after that choose a suitable window.
subject: Original Article
  topic: section
subject: Frequency Estimation
  topic: keywords
subject: Interpolation Algorithm
  topic: keywords
subject: Fast Fourier Transform
  topic: keywords
subject: Electrical Engineering
  topic: disciplines
creator: Husam Hammood
creator: Ameer H Ali
creator: Nabil Jalil Aklo
rights: Copyright (c) 2025 Iraqi Journal for Electrical and Electronic Engineering
date: 2024-12-06
publication date: 2024-12-06
starting page: 156
ending page: 161
doi: 10.37917/ijeee.21.1.15

Advanced Neural Network-Based Load Frequency Regulation in Two-Area Power Systems
type: item
description: In this paper, enhancing dynamic performance in power systems through load frequency control (LFC) is explored across diverse operating scenarios. A new Neural Network Model Predictive Controller (NN-MPC) specifically tailored for two-zone load frequency power systems is presented. ” Make your paper more scientific. The NN-MPC marries the predictive accuracy of neural networks with the robust capabilities of model predictive control, employing the nonlinear Levenberg-Marquardt method for optimization. Utilizing local area error deviation as feedback, the proposed controller’s efficacy is tested against a spectrum of operational conditions and systemic variations. Comparative simulations with a Fuzzy Logic Controller (FLC) reveal the proposed NN-MPC’s superior performance, underscoring its potential as a formidable solution in power system regulation.
subject: Original Article
  topic: section
subject: Neural Network Model Predictive Control (NN-MPC)
  topic: keywords
subject: Load Frequency Control (LFC)
  topic: keywords
subject: Power System Regulation
  topic: keywords
subject: Dynamic Performance Enhancement
  topic: keywords
subject: Levenberg-Marquardt Optimization
  topic: keywords
subject: Two-zone Power System Nonlinear Optimization
  topic: keywords
subject: Electrical Engineering
  topic: disciplines
creator: Mohammed Taha Yunis
creator: Mohamed DJEMEL
rights: Copyright (c) 2025 Iraqi Journal for Electrical and Electronic Engineering
date: 2024-12-06
publication date: 2024-12-06
starting page: 145
ending page: 155
doi: 10.37917/ijeee.21.1.14

Optimal Assimilation of Distributed Generation in Radial Power Distribution System Using Hybrid Approach
type: item
description: The performance of power distribution systems (PDS) has improved greatly in recent times ever since the distributed generation (DG) unit was incorporated in PDS. DG integration effectively cuts down the line power losses (PL) and strengthens the bus voltages (BV) provided the size and place are optimized. Accordingly, in the present work, a hybrid optimization technique is implemented for incorporating a single DG unit into radial PDS. The proposed hybrid method is formed by integrating the active power loss sensitivity (APLS) index and whale optimization meta-heuristic algorithm. The ideal place and size for DG are optimized to minimize total real power losses (TLP) and enhance bus voltages (BV). The applicability of the proposed hybrid technique is analyzed for Type I and Type III DG installation in a balanced IEEE 33-bus and 69-bus radial PDS. Optimal inclusion of type I and III DG in a 33-bus radial test system cut down TLP by 51.85% and 70.02% respectively. Likewise, optimal placement of type I and III DG reduced TLP by 65.18%, and 90.40%, respectively for 69-bus radial PDS. The impact of DG installation on the performance of radial PDS has been analyzed and a comparative study is also presented to examine the sovereignty of the proposed hybrid method. The comparative study report outlined that the proposed hybrid method can be a better choice for solving DG optimization in radial PDS.
subject: Original Article
  topic: section
subject: Distributed Generation
  topic: keywords
subject: Power Distribution System
  topic: keywords
subject: Power Losses
  topic: keywords
subject: Whale Optimization Algorithm
  topic: keywords
subject: Electrical Engineering
  topic: disciplines
creator: S K B Pradeepkumar CH
creator: Sakthidasan A
creator: Sundar R
creator: Senthil Kumar M
creator: Rajakumar P
creator: Baburao P
rights: Copyright (c) 2025 Iraqi Journal for Electrical and Electronic Engineering
date: 2024-12-05
publication date: 2024-12-05
starting page: 134
ending page: 144
doi: 10.37917/ijeee.21.1.13

Enhancing PV Fault Detection Using Machine Learning: Insights from a Simulated PV System
type: item
description: Recently, numerous researches have emphasized the importance of professional inspection and repair in case of suspected faults in Photovoltaic (PV) systems. By leveraging electrical and environmental features, many machine learning models can provide valuable insights into the operational status of PV systems. In this study, different machine learning models for PV fault detection using a simulated 0.25MW PV power system were developed and evaluated. The training and testing datasets encompassed normal operation and various fault scenarios, including string-to-string, on-string, and string-to-ground faults. Multiple electrical and environmental variables were measured and exploited as features, such as current, voltage, power, temperature, and irradiance. Four algorithms (Tree, LDA, SVM, and ANN) were tested using 5-fold cross-validation to identify errors in the PV system. The performance evaluation of the models revealed promising results, with all algorithms demonstrating high accuracy. The Tree and LDA algorithms exhibited the best performance, achieving accuracies of 99.544% on the training data and 98.058% on the testing data. LDA achieved perfect accuracy (100%) on the testing data, while SVM and ANN achieved 95.145% and 89.320% accuracy, respectively. These findings underscore the potential of machine learning algorithms in accurately detecting and classifying various types of PV faults. .
subject: Original Article
  topic: section
subject: PV Fault Detection; Standalone PV System; Machine Learning; Classifiers; Training and Testing Accuracy; Confusion Matrix
  topic: keywords
subject: Electrical Engineering
  topic: disciplines
creator: Halah Sabah Muttashar
creator: Amina Mahmoud Shakir
rights: Copyright (c) 2025 Iraqi Journal for Electrical and Electronic Engineering
date: 2024-12-05
publication date: 2024-12-05
starting page: 126
ending page: 133
doi: 10.37917/ijeee.21.1.12

Design and Validation of Super-Capacitor Assisted Photovoltaic Array for Roof-Top Solar Powered Electric Vehicle Applications
type: item
description: Upkeeping the Battery State-Of-Charge (SoC) and its life are of great significance in Battery Electric Vehicle (BEV) & Hybrid Electric Vehicles (HEV). This is possible by integrating Solar Photovoltaic Panels (PPs) on the Roof-top of the BEVs & HEVs. However, unlike Solar Powered Vehicle Charging stations and other PV applications where the solar panels are installed in such a way to extract the maximum Photon energy incident on the panel, vehicle Roof-top mount Solar PPs face many challenges in extracting maximum Power due to partial shading issues especially under dynamic conditions when passing under trees, high rise buildings and cloud passages. This paper proposes a new strategy called “Super-capacitor Assisted Photovoltaic Array”. In which Photovoltaic Modules are integrated with Super-capacitors to improve the transient performance of the Photovoltaic Array system. The design of proposed Super-capacitor Assisted PV array is validated & its performance is compared with conventional PV array in Matlab/ Simulink environment.
subject: Original Article
  topic: section
subject: Battery Electric Vehicle(BEC)
  topic: keywords
subject: Hybrid Electric Vehicles (HEV)
  topic: keywords
subject: Super-capacitor
  topic: keywords
subject: Solar Powered Vehicle Charging stations
  topic: keywords
subject: Electrical Engineering
  topic: disciplines
creator: Karunanithi K.
creator: S. Saravanan
creator: Ramesh S.
creator: S. P. Raja
creator: S. Kannan
creator: S. C. Vijayakumar
rights: Copyright (c) 2025 Iraqi Journal for Electrical and Electronic Engineering
date: 2024-12-05
publication date: 2024-12-05
starting page: 117
ending page: 125
doi: 10.37917/ijeee.21.1.11

Design and FPGA Implementation of a Hyper-Chaotic System for Real-time Secure Image Transmission
type: item
description: Recently, chaos theory has been widely used in multimedia and digital communications due to its unique properties that can enhance security, data compression, and signal processing. It plays a significant role in securing digital images and protecting sensitive visual information from unauthorized access, tampering, and interception. In this regard, chaotic signals are used in image encryption to empower the security; that’s because chaotic systems are characterized by their sensitivity to initial conditions, and their unpredictable and seemingly random behavior. In particular, hyper-chaotic systems involve multiple chaotic systems interacting with each other. These systems can introduce more randomness and complexity, leading to stronger encryption techniques. In this paper, Hyper-chaotic Lorenz system is considered to design robust image encryption/ decryption system based on master-slave synchronization. Firstly, the rich dynamic characteristics of this system is studied using analytical and numerical nonlinear analysis tools. Next, the image secure system has been implemented through Field-Programmable Gate Arrays (FPGAs) Zedboard Zynq xc7z020-1clg484 to verify the image encryption/decryption directly on programmable hardware Kit. Numerical simulations, hardware implementation, and cryptanalysis tools are conducted to validate the effectiveness and robustness of the proposed system.
subject: Original Article
  topic: section
subject: Chaos
  topic: keywords
subject: FPGA
  topic: keywords
subject: Hyper-chaotic System
  topic: keywords
subject: Image Encryption
  topic: keywords
subject: Xilinx System Generator
  topic: keywords
subject: Electrical Engineering
  topic: disciplines
creator: Abdul-Basset A. Al-Hussein
creator: Fadhil Rahma Tahir
creator: Ghaida A. Al-Suhail
rights: Copyright (c) 2025 Iraqi Journal for Electrical and Electronic Engineering
date: 2024-11-06
publication date: 2024-11-06
starting page: 55
ending page: 68
doi: 10.37917/ijeee.21.1.6

An Efficient EHR Secure Exchange Among Healthcare Servers Using Light Weight Scheme
type: item
description: This work addresses the critical need for secure and patient-controlled Electronic Health Records (EHR) migration among healthcare hospitals’ cloud servers (HHS). The relevant approaches often lack robust access control and leave data vulnerable during transfer. Our proposed scheme empowers patients to delegate EHR migration to a trusted Third-Party Hospital (TTPH); which is the Certification Authority (CA) while enforcing access control. The system leverages asymmetric encryption utilizing the Elliptic Curve Digital Signature Algorithm (ECDSA), EEC and ECDSA added robust security and lightness EHR sharing. Patient and user privacy is managed due to anonymity through cryptographic hashing for data protection and utilizes mutual authentication for secure communication. Formal security analysis using the Scyther tool and informal analysis was conducted to validate the system’s robustness. The proposed scheme achieved EHR integrity due to the verification of the communicated HHS and ensuring the integrity of the HHS digital certificate during EHR migration. Ultimately, the result achieved in the proposed work demonstrated the scheme’s high balance between data security and accuracy of communication, where the best result obtained represented 7.7/ ms as computational cost and 1248 /bits as communication cost compared with the relevant approaches.
subject: Original Article
  topic: section
subject: EHR
  topic: keywords
subject: EHR Migration
  topic: keywords
subject: ECDSA
  topic: keywords
subject: Login Authentication
  topic: keywords
subject: Security Analysis
  topic: keywords
subject: Electrical Engineering
  topic: disciplines
creator: Aqeel Adel Yaseen
creator: Kalyani Patel
creator: Abdulla J. Aldarwish
creator: Ali A. Yassin
rights: Copyright (c) 2025 Iraqi Journal for Electrical and Electronic Engineering
date: 2024-11-08
publication date: 2024-11-08
starting page: 69
ending page: 82
doi: 10.37917/ijeee.21.1.7

PLC/HMI Based Portable Workbench for PLC and Digital Logic Learning and Application Development
type: item
description: A Programmable logic controller (PLC) uses the digital logic circuits and their operating concepts in its hardware structure and its programming instructions and algorithms. Therefore, the deep understanding of these two items is staple for the development of control applications using the PLC. This target is only possible through the practical sensing of the various components or instructions of these two items and their applications. In this work, a user-friendly and re-configurable ladder, digital logic learning and application development design and testing platform has been designed and implemented using a Programmable Logic Controller (PLC), Human Machine Interface panel (HMI), four magnetic contactors, one Single-phase power line controller and one Variable Frequency Drive (VFD) unit. The PLC role is to implement the ladder and digital logic functions. The HMI role is to establish the virtual circuit wiring and also to drive and monitor the developed application in real time mode of application. The magnetic contactors are to play the role of industrial field actuators or to link the developed application control circuit to another field actuator like three phase induction motor. The Single -phase power line controller is to support an application like that of the soft starter. The VFD is to support induction motor driven applications like that of cut-to-length process in which steel coils are uncoiled and passed through cutting blade to be cut into required lengths. The proposed platform has been tested through the development of 14 application examples. The test results proved the validity of the proposed platform.
subject: Original Article
  topic: section
subject: Programmable logic controller (PLC)
  topic: keywords
subject: Variable Frequency Drive (VFD)
  topic: keywords
subject: Electrical Engineering
  topic: disciplines
creator: Jawad Radhi Mahmood
creator: Ramzy Salim Ali
rights: Copyright (c) 2025 Iraqi Journal for Electrical and Electronic Engineering
date: 2024-11-08
publication date: 2024-11-08
starting page: 83
ending page: 96
doi: 10.37917/ijeee.21.1.8

A Review of Algorithms and Platforms for Offloading Decisions in Mobile Cloud Computing
type: item
description: With the substantial growth of mobile applications and the emergence of cloud computing concepts, therefore mobile Cloud Computing (MCC) has been introduced as a potential mobile service technology. Mobile has limited resources, battery life, network bandwidth, storage, and processor, avoid mobile limitations by sending heavy computation to the cloud to get better performance in a short time, the operation of sending data, and get the result of computation call offloading. In this paper, a survey about offloading types is discussed that takes care of many issues such as offloading algorithms, platforms, metrics (that are used with this algorithm and its equations), mobile cloud architecture, and the advantages of using the mobile cloud. The trade-off between local execution of tasks on end-devices and remote execution on the cloud server for minimizing delay time and energy saving. In the form of a multi-objective optimization problem with a focus on reducing overall system power consumption and task execution latency, meta-heuristic algorithms are required to solve this problem which is considered as NP-hardness when the number of tasks is high. To get minimum cost (time and energy) apply partial offloading on specific jobs containing a number of tasks represented in sequences of zeros and ones for example (100111010), when each bit represents a task. The zeros mean the task will be executed in the cloud and the ones mean the task will be executed locally. The decision of processing tasks locally or remotely is important to balance resource utilization. The calculation of task completion time and energy consumption for each task determines which task from the whole job will be executed remotely (been offloaded) and which task will be executed locally. Calculate the total cost (time and energy) for the whole job and determine the minimum total cost. An optimization method based on metaheuristic methods is required to find the best solution. The genetic algorithm is …
subject: Review Article
  topic: section
subject: MCC
  topic: keywords
subject: Mobile Cloud
  topic: keywords
subject: Offloading
  topic: keywords
subject: MAUI
  topic: keywords
subject: MEC
  topic: keywords
subject: Electrical Engineering
  topic: disciplines
creator: Fatima Haitham Murtadha
creator: Suhad Faisal Behadili
rights: Copyright (c) 2025 Iraqi Journal for Electrical and Electronic Engineering
date: 2024-11-11
publication date: 2024-11-11
starting page: 97
ending page: 106
doi: 10.37917/ijeee.21.1.9

Patients Monitoring and Data Management System for Hospitals
type: item
description: This work concerns creating a monitoring system for a smart hospital using Raspberry Pi to measure vital signs. The readings are continually sent to central monitoring units outside the room instead of being beside the patients, to ensure less contacting between the medical staff and patients, also the cloud is used for those who leave the hospital, as the design can track on their medical cases. Data presentation and analysis were accomplished by the LabVIEW program. A Graphical User Interface (GUI) has been created by the Virtual-Instrument (VI) of this program that offer real-time access to monitor patients’ measurements. If unhealthy states are detected, the design triggers alerts and sends SMS message to the doctor. Furthermore, the clinicians can scan a QR code (which is assigned to each patient individually) to access its real-time measurements. The system also utilizes Electrocardiography (ECG) to detect abnormalities and identify specific heart diseases based on its extracted parameters to encourage patients to seek timely medical attention, while aiding doctors in making well-informed decisions. To evaluate the system’s performance, it is tested in the hospital on many patients of different ages and diseases as well. According to the results, the accuracy measurement of SpO2 was about 98.39%, 97.7% for (heart rate) and 98.7% for body temperature. This shows that the system can offer many patients receiving health services from various facilities, and it ensures efficient data management, access control, real-time monitoring, and secure patient information aligning with healthcare standards.
subject: Original Article
  topic: section
subject: Health Monitoring
  topic: keywords
subject: Smart Hospital
  topic: keywords
subject: SPO2
  topic: keywords
subject: ECG
  topic: keywords
subject: Raspberry Pi
  topic: keywords
subject: LabVIEW
  topic: keywords
subject: Electrical Engineering
  topic: disciplines
creator: Shahad Abdulrahman Khuder
creator: Sura Nawfal Abdulrazzaq
rights: Copyright (c) 2025 Iraqi Journal for Electrical and Electronic Engineering
date: 2024-11-15
publication date: 2024-11-15
starting page: 107
ending page: 116
doi: 10.37917/ijeee.21.1.10

Design and Implementation of the Soft Robot’s End-Effecter
type: item
description: Soft robotics is a modern technique that allows robots to have more capabilities than conventional rigid robots. Pneumatic Muscle Actuators (PMAs), also known as McKibben actuators, are an example of soft actuators. This research covered the design and production of a pneumatic robot end effector. Smooth, elastic, flexible, and soft qualities materials have contributed to the creation of Soft Robot End-Effector (SREE). To give SREE compliance, it needs to handle delicate objects while allowing it to adapt to its surroundings safely. The research focuses on the variable stiffness SREE’s inspiration design, construction, and manufacturing. As a result, a new four-fingered variable stiffness soft robot end effector was created. SREE has been designed using two types of PMAs: Contractor PMAs (CPMAs) and Extensor PMAs (EPMAs). Through tendons and Contractor PMAs, fingers can close and open. SREE was tested and put into practice to handle various object types. The innovative movement of the suggested SREE allows it to grip with only two fingers and open and close its grasp with all of its fingers.
subject: Original Article
  topic: section
subject: Soft Robots
  topic: keywords
subject: Soft Robot End-Effecter (SREE)
  topic: keywords
subject: Contractor Pneumatic Muscle Actuator (CPMA)
  topic: keywords
subject: Extensor Pneumatic Muscle Actuator (EPMA)
  topic: keywords
subject: Electrical Engineering
  topic: disciplines
creator: Shahad A. Al-Ibadi
creator: Loai A. T. Al-Abeach
creator: Mohammed A. Al-Ibadi
rights: Copyright (c) 2025 Iraqi Journal for Electrical and Electronic Engineering
date: 2024-11-01
publication date: 2024-11-01
starting page: 44
ending page: 54
doi: 10.37917/ijeee.21.1.5

Robust Low Pass Filter-PID Controller for 2-DOF Helicopter System
type: item
description: In this article, a robust control technique for 2-DOF helicopter system is presented. The 2-DOF helicopter system is 2 inputs and 2 outputs system that is suffering from the high nonlinearity and strong coupling. This paper focuses on design a simple, robust, and optimal controller for the helicopter system. Moreover, The proposed control method takes into account effects of the measurement noise in the closed loop system that effect on the performance of controller as well as the external disturbance. The proposed controller combines low pass filter with robust PID controller to ensure good tracking performance with high robustness. A low pass filter and PID controller are designed based H∞weighted mixed sensitivity. Nonlinear dynamic model of 2-DOF helicopter system linearized and then decoupled into pitch and yaw models. Finally, proposed controller applied for each model. Matlab program is used to check effectiveness the proposed control method. Simulation results show that the proposed controllers has best tracking performance with no overshot and the smallest settling time with respect to standard H∞and optimized PID controller.
subject: Original Article
  topic: section
subject: Helicopter system
  topic: keywords
subject: H infinity
  topic: keywords
subject: Low pass filter
  topic: keywords
subject: PID
  topic: keywords
subject: Robust control
  topic: keywords
subject: Electrical Engineering
  topic: disciplines
creator: Shatha Abd Al Kareem Mohammed
creator: Ali Hussien Mary
rights: Copyright (c) 2025 Iraqi Journal for Electrical and Electronic Engineering
date: 2024-11-01
publication date: 2024-11-01
starting page: 36
ending page: 43
doi: 10.37917/ijeee.21.1.4

Lower Limb Rehabilitation Exoskeleton Robots, A review
type: item
description: Using a lower limb exoskeleton for rehabilitation (LLE) Lower limb exoskeleton rehabilitation robots (LER) are designed to assist patients with daily duties and help them regain their ability to walk. Even though a substantial portion of them is capable of doing both, they have not yet succeeded in conducting agile and intelligent joint movement between humans and machines, which is their ultimate goal. The typical LLE products, rapid prototyping, and cutting-edge techniques are covered in this review. Restoring a patient’s athletic prowess to its pr-accident level is the aim of rehabilitation treatment. The core of research on lower limb exoskeleton rehabilitation robots is the understanding of human gait. The performance of common prototypes might be used to match wearable robot shapes to human limbs. To imitate a normal stride, robot-assisted treatment needs to be able to control the movement of the robot at each joint and move the patient’s limb.
subject: Review Article
  topic: section
subject: Gait Training Device
  topic: keywords
subject: Rehabilitation Robot
  topic: keywords
subject: Mechanical Design
  topic: keywords
subject: Lower Limb Exoskeleton
  topic: keywords
subject: Electrical Engineering
  topic: disciplines
creator: Dina Ayad
creator: Alaa Al-Ibadi
creator: Maria Elena Giannaccini
rights: Copyright (c) 2025 Iraqi Journal for Electrical and Electronic Engineering
date: 2024-10-18
publication date: 2024-10-18
starting page: 23
ending page: 35
doi: 10.37917/ijeee.21.1.3

The Beam Squint Effects in Antenna Arrays at Millimeter Bands
type: item
description: Beam squint phenomenon is considered one of the most drawbacks that limit the use of (mm-waves) array antennas; which causes significant degradation in the BER of the system. In this paper, a uniform linear array (ULA) system is exemplified at millimeter (mm-waves) frequency bands to realize the effects of beam squint phenomena from different directions on an equivalent gain response to represent the channel performance in terms of bit error rate (BER). A simple QPSK passband signal model is developed and tested according to the proposed antenna array with beam squint. The computed results show that increasing the passband bandwidth and the number of antenna elements, have a significant degradation in BER at the receiver when the magnitude and phase errors caused by the beam squint at 26 GHz with various spectrum bandwidths.
subject: Original Article
  topic: section
subject: Millimeter Waves
  topic: keywords
subject: Passband
  topic: keywords
subject: Baseband
  topic: keywords
subject: QPSK
  topic: keywords
subject: Bandwidth
  topic: keywords
subject: Antenna Array
  topic: keywords
subject: Array Gain Response
  topic: keywords
subject: Electrical Engineering
  topic: disciplines
creator: Mariam Q. Abdalrazak
creator: Asmaa H. Majeed
creator: Raed A. Abd-Alhameed
rights: Copyright (c) 2025 Iraqi Journal for Electrical and Electronic Engineering
date: 2024-10-13
publication date: 2024-10-13
starting page: 16
ending page: 22
doi: 10.37917/ijeee.21.1.2

Integration of Fuzzy Logic and Neural Networks for Enhanced MPPT in PV Systems Under Partial Shading Conditions
type: item
description: Efficient energy collection from photovoltaic (PV) systems in environments that change is still a challenge, especially when partial shading conditions (PSC) come into play. This research shows a new method called Maximum Power Point Tracking (MPPT) that uses fuzzy logic and neural networks to make PV systems more flexible and accurate when they are exposed to PSC. Our method uses a fuzzy logic controller (FLC) that is specifically made to deal with uncertainty and imprecision. This is different from other MPPT methods that have trouble with the nonlinearity and transient dynamics of PSC. At the same time, an artificial neural network (ANN) is taught to guess where the Global Maximum Power Point (GMPP) is most likely to be by looking at patterns of changes in irradiance and temperature from the past. The fuzzy controller fine-tunes the ANN’s prediction, ensuring robust and precise MPPT operation. We used MATLAB/Simulink to run a lot of simulations to make sure our proposed method would work. The results showed that combining fuzzy logic with neural networks is much better than using traditional MPPT algorithms in terms of speed, stability, and response to changing shading patterns. This innovative technique proposes a dual-layered control mechanism where the robustness of fuzzy logic and the predictive power of neural networks converge to form a resilient and efficient MPPT system, marking a significant advancement in PV technology.
subject: Original Article
  topic: section
subject: Photovoltaic Systems
  topic: keywords
subject: Maximum Power Point Tracking (MPPT)
  topic: keywords
subject: Partial Shading Conditions (PSC)
  topic: keywords
subject: Fuzzy Logic Controller (FLC)
  topic: keywords
subject: Artificial Neural Networks (ANN)
  topic: keywords
subject: Global Maximum Power Point (GMPP)
  topic: keywords
subject: Electrical Engineering
  topic: disciplines
creator: Hayder Dakhil Atiya
creator: Mohamed Boukattaya
creator: Fatma Ben Salem
rights: Copyright (c) 2025 Iraqi Journal for Electrical and Electronic Engineering
date: 2024-09-19
publication date: 2024-09-19
starting page: 1
ending page: 15
doi: 10.37917/ijeee.21.1.1