Iran University of Science and Technology (IUST) Iranian Journal of Electrical and Electronic Engineering 1735-2827 1735-2827 21 4 2025 11 1 A study on the impact of various modulation and coding schemes on wireless (WiFi-6) performance 1 11 EN Ankit Saxena Electronics and Communication Department of Indore Institute of Science and Technology, Indore MP India, Rajiv Gandhi Proudyogiki Vishwavidyalaya, Bhopal India. ankitsaxena_17@hotmail.com Y 10.22068/IJEEE.21.4.3263 The performance of wireless networks depends on measuring the radio characteristics between the Access Point (AP) and Client Station (STA) within the same Base Service Set (BSS). In areas with high demand for wireless services, multiple wireless networks may overlap, causing interference and negatively impacting the performance of individual users and networks. This interference makes wireless radio channels more susceptible to interference from surrounding energy, directly affecting wireless networks' throughput. A new spatial reuse IEEE802.11ax standard has provided the solution to address this issue. This standard performs a clear channel assessment procedure between the AP and STA before assigning the channel for traffic, thus reducing channel collision and improving the effectiveness of radio resources in wireless networks. Additionally, the quality and availability of radio resources of overlaying networks would improve the usage of radio channels. This study assesses how spatial reuse, combined with different modulation with coding schemes and clear channel assessment, affects channel throughput. The results show that integrating spatial reuse can boost channel throughput by 18-20%, significantly enhancing network performance. IEEE802.11ax, OBSS, Wifi-6 http://ijeee.iust.ac.ir/article-1-3263-en.html http://ijeee.iust.ac.ir/article-1-3263-en.pdf
Iran University of Science and Technology (IUST) Iranian Journal of Electrical and Electronic Engineering 1735-2827 1735-2827 21 4 2025 11 1 Optimal Sink Node Placement and Routing Protocol Evaluation for 6LoWPAN Networks in IoT 12 26 EN Mahendra Shridhar Naik Department of ECE, New Horizon College of Engineering, Bengaluru, Karnataka, India. mahendrasnaik@gmail.com N Chaitra S N Department of ECE, GM University, Davangere, Karnataka, India. CHAITRASN48@GMAIL.COM N Amit Kumar K Department of ECE, Mangalore Institute of Technology and Engineering, Moodbidre, Karnataka, India. AMIT@MITE.AC.IN Y 10.22068/IJEEE.21.4.3376 6LoWPAN is a significant innovation for low-power devices such as sensors and motes, enabling efficient communication in IoT networks. This paper examines the impact of topology and sink node placement on data delivery within these networks, focusing on the Routing Protocol for Low-Power and Lossy Networks (RPL). Various network performance metrics are evaluated to determine optimal routing paths, revealing that increased node density and network size lead to higher delays and congestion. The study highlights that the central placement of the sink node enhances performance. Comparatively, mesh topology outperforms random topology in terms of efficiency. Simulations were conducted to evaluate the effectiveness of Objective Functions (OFs), specifically OF0 and MRHOF. The results indicate that MRHOF surpasses OF0, with performance improvements scaling with network size. 6LoWPAN, IoT, Routing Protocol, QoS, Network Topology. http://ijeee.iust.ac.ir/article-1-3376-en.html http://ijeee.iust.ac.ir/article-1-3376-en.pdf
Iran University of Science and Technology (IUST) Iranian Journal of Electrical and Electronic Engineering 1735-2827 1735-2827 21 4 2025 11 1 Evolutionary Fuzzy Force Control for Effective Mobile Robot Navigation 27 43 EN Majid Golkhatab Department of Electrical Engineering is part of the Faculty of Technical and Engineering at Imam Khomeini International University. Qazvin, Iran. ma.golkhatab@edu.ikiu.ac.ir N Aref Shahmansoorian Department of Electrical Engineering is part of the Faculty of Technical and Engineering at Imam Khomeini International University. Qazvin, Iran. shahmansoorian@ikiu.ac.ir Y Mohsen Davoudi Department of Electrical Engineering is part of the Faculty of Technical and Engineering at Imam Khomeini International University. Qazvin, Iran. davoudi@ikiu.ac.ir N 10.22068/IJEEE.21.4.3395 This paper presents a novel hybrid navigation approach for autonomous mobile robots in obstacle-rich environments. The method integrates artificial potential fields for obstacle avoidance with fuzzy logic for path planning, which is optimized by a genetic algorithm to enhance adaptability and robustness to sensor uncertainties. Experimental results demonstrate significant improvements over traditional artificial potential field methods and are validated through real-time implementation on a ROS-based mobile robot. Autonomous Mobile Robot, Fuzzy Logic System Optimization, Hybrid Approach, Path Planning http://ijeee.iust.ac.ir/article-1-3395-en.html http://ijeee.iust.ac.ir/article-1-3395-en.pdf
Iran University of Science and Technology (IUST) Iranian Journal of Electrical and Electronic Engineering 1735-2827 1735-2827 21 4 2025 11 1 Enhancing Hepatitis C Diagnosis: The Impact of SMOTE, Optuna, and SHAP on Detection Methods 44 60 EN S.M Mehzabeen Department of Electronics and Communication Engineering, Sri Venkateswara College of Engineering, Sriperumbudur, India mehzabeen@svce.ac.in N R Gayathri Department of Electronics and Communication Engineering, Sri Venkateswara College of Engineering, Sriperumbudur, India rgayathri@svce.ac.in N Pattunnarajam Paramasaivam Department of Electronics and Communication Engineering, Sri Venkateswara College of Engineering, Sriperumbudur, India pattunarajamp@svce.ac.in Y Ramya A Department of Electronics and Communication Engineering, Sri Venkateswara College of Engineering, Sriperumbudur, India ramyaa@svce.ac.in N 10.22068/IJEEE.21.4.3418 Hepatitis C virus (HCV) detection is a critical aspect of early intervention and effective management of the disease. This paper presents a comprehensive study focused on enhancing the detection accuracy of HCV through the integration of advanced techniques - SMOTE, Optuna, and SHAP - alongside extensive exploratory data analysis (EDA). The study addresses class imbalance using Synthetic Minority Over-sampling Technique (SMOTE), optimizes model performance with Optuna for hyperparameter tuning, and provides model interpretability using SHAP (SHapley Additive exPlanations). EDA is leveraged to gain valuable insights into the dataset's characteristics, ensuring robust data preprocessing and feature engineering. The results show 97% improved HCV detection performance, highlighting the efficacy of the proposed methodology in medical diagnostics and aiding healthcare professionals in making informed clinical decisions. Hepatitis C virus, Synthetic Minority Over-sampling Technique, exploratory data analysis, SHapley Additive exPlanations, machine learning, classification algorithms, OPTUNA. http://ijeee.iust.ac.ir/article-1-3418-en.html http://ijeee.iust.ac.ir/article-1-3418-en.pdf
Iran University of Science and Technology (IUST) Iranian Journal of Electrical and Electronic Engineering 1735-2827 1735-2827 21 4 2025 11 1 A review Optimum Control of DC Motor Using Genetic Algorithm 61 77 EN Suhail Mahmoud Abdullah The authors is with the Department of Electrical Engineering, Tikrit University, Tikrit City, Iraq. sihel.m.abdullah43872@st.tu.edu.iq N Thamir Hassan Atyia The authors is with the Department of Electrical Engineering, Tikrit University, Tikrit City, Iraq. dr.thamir.atyia@tu.edu.iq Y 10.22068/IJEEE.21.4.3473 Optimal control of DC motors remains a critical research area in modern control systems, given their wide industrial applications and the need for accurate performance under variable conditions. This paper explores the application of genetic algorithms (GAs) to optimize the control parameters of DC motors, particularly PID controllers, with the goal of improving the dynamic response and robustness of DC motor systems. Compared to traditional constraint-based tuning methods, GAs, inspired by natural selection and evolution, offer comprehensive search capabilities that significantly improve parameter optimization, providing better speed regulation, reduced overshoot, and minimal steady-state error. This review highlights the key challenges faced when using GAs. Comparative results from various studies demonstrate that GA-based controllers consistently outperform traditional tuning methods in terms of stability, efficiency, and adaptability. Key findings related to energy consumption and stability are highlighted. It is essential to analyze the system performance in terms of rise time (tr), settling time (ts), overshoot ratio (Mp%), and steady-state error (Ess). A proportional-integral-differential (PID) controller provides a stable response by tuning its parameters according to a specific methodology using a genetic algorithm. This paper concludes by emphasizing the potential of genetic generators as a powerful and flexible optimization tool for intelligent control of DC motors. Genetic algorithm (GA), PID control, DC Motor, Optimum technique, speed control. http://ijeee.iust.ac.ir/article-1-3473-en.html http://ijeee.iust.ac.ir/article-1-3473-en.pdf
Iran University of Science and Technology (IUST) Iranian Journal of Electrical and Electronic Engineering 1735-2827 1735-2827 21 4 2025 11 1 Advanced Maximum Power Point Tracking and DC-DC Converter Design for Enhanced Efficiency in Standalone PV Systems 78 89 EN Sivaprasad Kollati The author is with the Department of Electrical Engineering, Andhra University. AU-TDR Hub, Visakhapatnam, India. ksivaprasad22@gmail.com Y Satish Kumar Gudey The authors are with the Department of Electrical and Electronics Engineering, Gayatri Vidya Parishad College of Engineering (Autonomous), India. satishgudey5@gvpce.ac.in N 10.22068/IJEEE.21.4.3499 To maximize the efficiency of solar energy conversion into electricity, photovoltaic (PV) system optimization is crucial. This is especially true for off-grid solar installations in remote areas lacking grid access. In order to maximize energy extraction from freestanding PV systems, regardless of fluctuating external conditions, this research provides a modified DC-DC converter and a novel Maximum Power Point Tracking (MPPT) technique. To ensure the photovoltaic (PV) system operates at full capacity despite rapid changes in weather conditions, the proposed solution utilizes the Modified Incremental Conductance MPPT algorithm that dynamically adjusts the system's operational parameters. Extensive simulations run in the MATLAB/Simulink platform confirm that the MPPT technique is efficient and effective. The proposed method outperforms traditional MPPT approaches in both convergence speed and output power stability. This research also develops a novel DC-DC converter to address the challenges given by the fluctuating solar irradiation. The modified DC-DC converter exhibits high gain and shorter settling time, and the improved MPPT method enhances the feasibility of deploying solar energy systems in off-grid and remote regions by enhancing the autonomy of standalone PV systems. MPPT, PV Systems, Solar Systems, MATLAB, Renewable Energy, Zeta converter http://ijeee.iust.ac.ir/article-1-3499-en.html http://ijeee.iust.ac.ir/article-1-3499-en.pdf
Iran University of Science and Technology (IUST) Iranian Journal of Electrical and Electronic Engineering 1735-2827 1735-2827 21 4 2025 11 1 Deep Learning Approach for Forest Fire Detection: A CNN Classification Model on the DeepFire Dataset 90 104 EN Tara Sistani Department of Electrical and Computer Engineering, Babol Noshirvani University of Technology, Babol, Mazandaran, Iran. tarasistani@stu.nit.ac.ir N Seyed Javad Kazemitabar Department of Electrical and Computer Engineering, Babol Noshirvani University of Technology, Babol, Mazandaran, Iran. j.kazemitabar@nit.ac.ir Y 10.22068/IJEEE.21.4.3601 Forests play several vital roles in our lives and provide various resources. However, in recent years, the increasing frequency of wildfires has led to the widespread burning and destruction of many forests and wildlands. Therefore, detecting forest fires and finding suitable solutions to address this issue has become one of the critical challenges for researchers. Today, with the advancement of artificial intelligence, forest fire detection using deep learning is an important method with the aim of increasing the efficiency of forest fire detection and monitoring systems. In this article, a method based on a type of convolutional neural network called Xception is proposed for classifying forest fire images. In this method, transfer learning technique is used on the proposed neural network and a new classifier is designed for the problem. Also, various hyperparameters have been used to optimize the performance of the proposed model. The proposed method is performed on the DeepFire dataset, which contains 1900 images equally divided between fire and no-fire classes. The results obtained from the implementation of the proposed method show that this method with an accuracy of 99.47% has achieved a favorable performance in classifying forest fire images. Artificial Intelligence, Classification, Convolutional Neural Network, Deep Learning, Forest Fire Detection. http://ijeee.iust.ac.ir/article-1-3601-en.html http://ijeee.iust.ac.ir/article-1-3601-en.pdf
Iran University of Science and Technology (IUST) Iranian Journal of Electrical and Electronic Engineering 1735-2827 1735-2827 21 4 2025 11 1 4-18 GHz Zero-Bias Asymmetrical Spacer Layer Tunnel Diode Detector 105 114 EN Omar S Abdulwahid Department of Mechatronics Engineering, College of Engineering, University of Mosul, Mosul, Iraq. Omar.abdulwahid@uomosul.edu.iq Y Saad G Muttlak Department of Electrical Engineering, Tikrit University, Tikrit, Iraq. Saad.g.mutlak@tu.edu.iq N James Sexton Department of Electrical and Electronic Engineering, University of Manchester, Manchester, UK. j.sexton@manchester.ac.uk N Michael J Kelly Department of Electrical Engineering, Cambridge University, Cambridge, UK. mjk1@eng.cam.ac.uk N Mohamed Missous Department of Electrical and Electronic Engineering, University of Manchester, Manchester, UK. m.missous@manchester.ac.uk N 10.22068/IJEEE.21.4.3641 An analysis of 6×6 µm2 GaAs/AlAs Asymmetric Spacer Layer Tunnel diode has been conducted to evaluate the DC and RF characteristics at different bias conditions. At zero voltage operation, the diode exhibited a measured curvature coefficient of 22 V-1, corresponding to a junction resistance of 27 kΩ. The measured and simulated S11 reflection coefficient of the integrated detector including the diode, matching circuit, and output capacitance achieved to be less than -10 dB at the desired frequency. The extracted low series resistance and junction capacitance of the tunnel diode resulted a high voltage sensitivity of 3650 V/W and low noise equivalent power of 5.5 pW/  at 11 GHz resonant frequency and -27 dBm input power. The developed detector model can be extended to implement RF detectors operating at frequencies reaching mm-wave regime applications. This is with consideration of the requirements for sub-micrometer scale mesa devices, eliminating the effects of associated parasitic elements and improved matching network performance. ASPAT Detector, ADS Model, Reflection Coefficient, Noise Equivalent Power. http://ijeee.iust.ac.ir/article-1-3641-en.html http://ijeee.iust.ac.ir/article-1-3641-en.pdf
Iran University of Science and Technology (IUST) Iranian Journal of Electrical and Electronic Engineering 1735-2827 1735-2827 21 4 2025 11 1 Optimal PMUs placement considering measurement Redundancy & Zero Injection Bus (ZIB) using multi-objective Harris Hawks optimization algorithm 115 126 EN Masoud Hashemi Department of Electrical Engineering, Iran University of Science and Technology (IUST), Tehran, Iran. masoudhashemi1997@yahoo.com N Mohsen Kalantar Department of Electrical Engineering, Iran University of Science and Technology (IUST), Tehran, Iran. kalantar@iust.ac.ir Y 10.22068/IJEEE.21.4.3690 The basis of the extensive measurement systems is based on the placement of phasor measurement units (PMUs) in the power grids. With the ever increasing expansion of electric energy consumption and the emergence of the phenomenon of restructuring in power grids and the existence of problems such as extensive blackouts of the power grid has increased the desire of power grid operators to use a wide area monitoring system (WAMS). This paper discusses the problem of optimal placement of phasor measurement units (PMUs) in power grids, which is a critical issue for the reliable and safe operation of power systems. We proposed a multi-objective binary optimization algorithm called the Multi-Objective Binary Harris Hawks Optimization algorithm based on Region selection (MOBHHO/R) to solve this problem. One of the most important innovations of the proposed algorithm is to draw inspiration from feature called a repository or archive to store optimal responses at each stage of the simulation. The algorithm aims to minimize the number of PMUs required while maximizing the observability of the power grids. The proposed algorithm is implemented on the standard IEEE 14 and 30 bus power systems, and the results show its superiority compared to other algorithms. Optimal PMU Placement, Harris Hawks Optimization, multi-objective optimization algorithm, Observability. http://ijeee.iust.ac.ir/article-1-3690-en.html http://ijeee.iust.ac.ir/article-1-3690-en.pdf
Iran University of Science and Technology (IUST) Iranian Journal of Electrical and Electronic Engineering 1735-2827 1735-2827 21 4 2025 11 1 Design and Simulation of Marx Generators for Sustainable Hydrogen Production: A Focus on Stray Impedance Management 127 140 EN Hamid Reza Sezavar Department of Electrical and Computer Engineering, Qom University of Technology, Iran. sezavar@qut.ac.ir Y Saeed Hasanzadeh Department of Electrical and Computer Engineering, Qom University of Technology, Iran. hasanzadeh@qut.ac.ir N 10.22068/IJEEE.21.4.3708 Marx generators that produce output pulses in the range of a few kilovolts (kV) with energies of a few millijoules (mJ) and rise times of a few nanoseconds (ns) have a variety of applications, including enhancing hydrogen production through electrolysis. In these generators, bipolar junction transistors (BJTs) operating in avalanche breakdown mode are employed as switches. This study explores the use of transistors specifically designed for avalanche breakdown to improve hydrogen generation efficiency from renewable energy sources. For this purpose, the FMMT415 transistor was implemented in the generator. The designed circuit was simulated with the transistors in avalanche breakdown mode, and the effects of various parameters on the output voltage were examined, particularly in the context of optimizing electrolysis performance. Based on the simulation results, the circuit was constructed and tested, and the differences in transistor parameters were evaluated. The simulation outcomes were then compared with the actual results. From these investigations, criteria were developed to determine the parameters that ensure suitable output voltage for Marx generator applications in hydrogen production. The optimal number of stages for the Marx generator was estimated based on the findings, highlighting its potential role in advancing sustainable hydrogen energy systems. Avalanche breakdown mode, Bipolar junction transistors (BJTs), Circuit simulation, Hydrogen production, Marx generator, Plasma Science, Pulse generation. http://ijeee.iust.ac.ir/article-1-3708-en.html http://ijeee.iust.ac.ir/article-1-3708-en.pdf
Iran University of Science and Technology (IUST) Iranian Journal of Electrical and Electronic Engineering 1735-2827 1735-2827 21 4 2025 11 1 Facilitating Winding Design and Performance Evaluation of WR Synchro 141 150 EN Mohammad Reza Eesazadeh Electrical Engineering Department, Sharif University of Technology, Tehran, Iran mohammadreza.eesazadeh@ee.sharif.edu N Zahra Nasiri-Gheidari Electrical Engineering Department, Sharif University of Technology, Tehran, Iran znasiri@sharif.edu Y 10.22068/IJEEE.21.4.3792 This research focuses on electromagnetic position sensors, particularly synchros, which play a crucial role in the closed-loop control systems of permanent magnet synchronous machines (PMSMs). Compared to two-phase resolvers, three-phase synchros provide enhanced reliability by ensuring continued operation even in the event of an open-circuit fault. One of the key challenges in designing such sensors lies in selecting optimal windings and configurations while also developing efficient modeling techniques to minimize computational complexity. To address this issue, the study introduces a matrix-based method for designing wound rotor (WR) synchros. This approach allows for flexible configurations depending on the number of pole pairs and stator tooth counts. The proposed design methodology ensures adaptability and precision, making it a valuable tool for engineers working on electromagnetic sensor development. To validate the effectiveness of the proposed method, the Field Reconstruction Method (FRM) is employed, providing a fast and accurate modeling technique that can be implemented using MATLAB. Additionally, a comparative analysis is conducted with finite element analysis (FEA) to confirm the accuracy and reliability of the approach. Results demonstrate that the matrix-based method is an efficient and effective solution for optimizing WR synchro designs, significantly improving performance and computational efficiency. Analytical model, finite element method (FEM), synchro, wound rotor (WR). http://ijeee.iust.ac.ir/article-1-3792-en.html http://ijeee.iust.ac.ir/article-1-3792-en.pdf
Iran University of Science and Technology (IUST) Iranian Journal of Electrical and Electronic Engineering 1735-2827 1735-2827 21 4 2025 11 1 Resilience-Oriented Restoration After Storm-Induced Failures Using Genetic Algorithm and Probabilistic Circuit Breaker Modeling 151 168 EN Mahdi Arabsadegh Department of Electrical Engineering, Faculty of Engineering, Shahed University of Tehran, Tehran, Iran. mahdi.arabsadegh@shahed.ac.ir Y aref doroudi Department of Electrical Engineering, Faculty of Engineering, Shahed University of Tehran, Tehran, Iran. doroudi@shahed.ac.ir N 10.22068/IJEEE.21.4.3860 This paper presents an advanced methodology for post-storm power system restoration. A real-time Condition Index (CI)-based classification scheme is introduced to categorize circuit breakers into high-reliability (Type A) and moderate-reliability (Type B) groups. Leveraging this classification, a genetic algorithm (GA) optimizes microgrid configurations to maximize power restoration probabilities by explicitly modeling the stochastic failure risks associated with circuit breakers under severe weather conditions. The approach was validated on the IEEE 118-bus system with five critical breakers deactivated due to storm conditions. The GA achieved a 92.5% load restoration after 200 iterations, surpassing a baseline Monte Carlo simulation that attained 85.2%. Computational efficiency was significantly improved, reducing execution time to approximately 15 minutes compared to 60 minutes for traditional methods, with enhanced accuracy indicated by a 1.8% error margin versus 7.5%. Key contributions include utilizing live CI data for dynamic breaker classification, which resulted in a 20% reduction in computational time, and demonstrating scalability and effectiveness on large-scale test systems such as the 118-bus network. The methodology's performance decreases to 78.3% load restoration when more than 14 breakers are compromised. Future research will focus on integrating detailed storm modeling—including wind speed profiles—and incorporating renewable energy resources to enhance grid resilience. resilience, Genetic Algorithm, Condition Index, probabilistic modeling, microgrids, storm-induced failures, load restoration. http://ijeee.iust.ac.ir/article-1-3860-en.html http://ijeee.iust.ac.ir/article-1-3860-en.pdf