Ghaida A. Al-Suhail

@uobasrah.edu.iq

Department of Computer Engineering/College of Engineering
University of Basrah

Ghaida A. Al-Suhail


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https://researchid.co/ghaidaalsuhail
Dr. Ghaida A. Al-Suhail received her B.Sc., M.Sc., and Ph.D. degrees in Electrical Engineering in 1984, 1989, and 2007, respectively all at University of Basrah in Iraq. She became an Assistant Professor in 1996. Currently, she is a Full Professor at the Department of Computer Engineering, College of Engineering, University of Basrah in Iraq. Her current research interests include Multimedia Communications, Wireless Networks, Cross-layer Design, Internet of Things, Routing Protocols in Ad hoc and Sensor Networks, Chaotic Radars, and Optical Communications. She was a Fulbright Scholar in 2011 at the Michigan State University (MSU), USA, and Endeavour Fellowship 2009 Scholar at the Australian National University (ANU), RSISE, Australia. She has published several papers in prestigious International Journals and Conferences.

RESEARCH INTERESTS

Multimedia Communications; Wireless Networks; Cross-layer Design; Internet of Things, Routing Protocols in Ad hoc Networks ( MANET, VANET and FANET); Wireless Sensor Networks; Chaotic Radar Systems; and Optical Communications
55

Scopus Publications

528

Scholar Citations

12

Scholar h-index

17

Scholar i10-index

Scopus Publications

  • Alzheimer’s Disease Diagnose using Deep Learning for Brain MRI Images: A Comparative Analysis
    Hiba A. Alahmed, Ghaida A. Al-Suhail
    Iraqi Journal for Electrical and Electronic Engineering, 2026
    Alzheimer’s disease (AD), the most common form of dementia, affects over 55 million people worldwide. The most form of dementia progresses into three distinct stages: mild, moderate, and very mild compared to Cognitively Normal (CN). Early detection is crucial to prevent brain damage before the late stages. Convolutional Neural Networks (CNNs), a subfield of deep learning, have recently found remarkable applications in medical image processing and computer-aided diagnosis (CAD). To this end, this paper presents a new efficient multi-classification AlzCNN-Net model to enhance the accuracy and efficacy of MRI image classification for various Alzheimer’s disease conditions. Initially, the training process involves utilizing open-source Alzheimer’s disease datasets from the Kaggle database to classify the brain MRI into its corresponding category. To verify the model’s efficacy, a comparative analysis with three pre-trained models, namely VGG16, Incep-tionV3, and MobileNetV2, has been investigated via transfer learning applied to the same dataset. As a result, the findings reveal that the AlzCNN-Net model exhibits an optimal performance, attaining the best accuracy in training with 99.67%, validation with 98.24%, and testing with 98.9% accuracy at epoch 100 with batch size 32 compared to the existing pre-trained approaches.
  • ResNet-OSD: an optimized hybrid deep learning framework for oil spill detection in coastal drone imagery
    Iman A. Al-Sudani, Ghaida A. Al-Suhail
    Visual Computer, 2026
  • W-GPSR Routing Based on Mobility Prediction for Vehicular Ad-Hoc Network (VANET)
    Raneen AL-Essa, Ghaida Al-Suhail
    Iraqi Journal for Electrical and Electronic Engineering, 2025
    In recent years, Vehicular Ad-Hoc Networks (VANETs) innovation has been regarded as a significant research area. This is owing to the increasing popularity of vehicle to vehicle (V2V) and vehicle to infrastructure (V2I) communications in the area of Intelligent Transportation System (ITS) to improve traffic management, safety, CO2 emission mitigation, and other applications. A variety of routing protocols for VANETs are being recently developed. More specifically, geographic-based routing algorithms such as Greedy Perimeter Stateless Routing (GPSR) have provoked the most interest in VANETs due to their compatibility with a regularly changing network structure and the highly unsteady nature of automobile nodes. This paper proposes an efficient weight based mobility method in VANET to improve the mechanism of the GPSR protocol through optimizing the greedy forwarding strategy; which is so called O-Greedy Mode. Therefore, the key goal is to achieve the optimal data forwarding paths. The next hop is determined by estimating the neighbors’ mobility based on each neighbor’s Greedy Link Weight Factor (GLWF). The Weighted GPSR (W-GPSR) based on Mobility Prediction is then evaluated using OMNeT++ simulator with Inet, Veins and SUMO traffic simulator. The results demonstrate the efficiency of W-GPSR in contrast with the traditional existing protocols for essential metrics of Packet Delivery Ratio (PDR), throughput, End-to-End Delay (E2ED), Normalized Routing Load (NRL) and Packet Loss Ratio (PLR).
  • LCxNet: An Explainable CNN Framework for Lung Cancer Detection in CT Images Using Multi-Optimizer and Visual Interpretability
    Noor S. Jozi, Ghaida A. Al-Suhail
    Applied System Innovation, 2025
    Lung cancer, the leading cause of cancer-related mortality worldwide, necessitates better methods for earlier and more accurate detection. To this end, this study introduces LCxNet, a novel, custom-designed convolutional neural network (CNN) framework for computer-aided diagnosis (CAD) of lung cancer. The IQ-OTH/NCCD lung CT dataset, which includes three different classes—benign, malignant, and normal—is used to train and assess the model. The framework is implemented using five optimizers, SGD, RMSProp, Adam, AdamW, and NAdam, to compare the learning behavior and performance stability. To bridge the gap between model complexity and clinical utility, we integrated Explainable AI (XAI) methods, specifically Grad-CAM for decision visualization and t-SNE for feature space analysis. With accuracy, specificity, and AUC values of 99.39%, 99.45%, and 100%, respectively, the results demonstrate that the LCxNet model outperformed the state-of-the-art models in terms of diagnostic performance. In conclusion, this study emphasizes how crucial XAI is to creating trustworthy and efficient clinical tools for the early detection of lung cancer.
  • Design and FPGA Implementation of a Hyper-Chaotic System for Real-time Secure Image Transmission
    Abdul-Basset A. Al-Hussein, Fadhil Rahma Tahir, Ghaida A. Al-Suhail
    Iraqi Journal for Electrical and Electronic Engineering, 2025
    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.
  • Explainable AI-based Deep Learning for Brain Tumor MRI Analysis: A Review
    Sarah J. Mohammed, Ghaida A. Al-Suhail
    2025 6th International Conference on Communications Information Electronic and Energy Systems Ciees 2025 Conference Proceedings, 2025
  • AlzONet: a deep learning optimized framework for multiclass Alzheimer’s disease diagnosis using MRI brain imaging
    Hiba A. Alahmed, Ghaida A. Al-Suhail
    Journal of Supercomputing, 2025
  • Energy-aware Clustering Using Intelligent Scheme for Heterogeneous Wireless Sensor Networks
    Enaam A. Al-Hussain, Ghaida A. Al-Suhail
    Karbala International Journal of Modern Science, 2025
  • Lung Cancer Detection: The Role of Transfer Learning in Medical Imaging
    Noor S. Jozi, Ghaida A. Al-Suhail
    2024 International Conference on Future Telecommunications and Artificial Intelligence IC Ftai 2024 Proceedings, 2024
    Lung cancer is a major global health issue, and improved patient results and treatment efficacy rely on early diagnosis. For many human diseases, including lung cancer, computer-aided detection (CAD) systems have greatly improved clinical analysis and decision-making. This study applies pre-trained deep learning techniques with a focus on transfer learning approaches and utilizes the available computed tomography (CT) scan image dataset (IQ-OTH/NCCD) to investigate the automation of lung cancer detection through CT scans. It concentrates on the training and evaluation of VGG16, ResNet50V2, and InceptionV3 architecture using this dataset. The aim is to automate lung cancer identification, ultimately enhancing diagnostic precision and outcome for the patient. It concentrates on the training and evaluation of VGG16, ResNet50V2, and InceptionV3 architecture using this dataset. The aim is to automate lung cancer identification, ultimately improving the accuracy of diagnosis and prognosis of the patient. The findings revealed ResNet50V2 is superior with impressive 98% accuracy, high sensitivity (95%) and excellent specification (99%). This investigation highlights how CAD systems can greatly improve the diagnostic process by providing radiologists with reliable tools to identify cancerous nodules, thereby reducing the risk of missed diagnosis.
  • Medical Image Classification Using Deep Learning for Brain Tumors Detection: An Overview
    Hiba A. Alahmad, Ghaida A. Al-Suhail
    Lecture Notes in Networks and Systems, 2024
  • Lung Cancer Detection in Radiological Imaging using Deep Learning: A Review
    Noor S. Jozi, Ghaida A. Al-Suhail
    Ciees 2024 IEEE International Conference on Communications Information Electronic and Energy Systems, 2024
  • Image-Based Oil Spill Detection using Deep Learning Techniques: A Review
    Iman Ali Al-Sudani, Ghaida A. Al-Suhail
    Ciees 2024 IEEE International Conference on Communications Information Electronic and Energy Systems, 2024
  • Exploring Transfer Learning Techniques for Brain Tumor Diagnosis in MRI Data
    Hiba A. Alahmed, Ghaida A. Al-Suhail
    1st International Conference on Emerging Technologies for Dependable Internet of Things Iceti 2024, 2024
  • A Comparative Study of VGG16 and VGG19 for Oil Spill Detection in Coastal Imagery
    Iman A. Al-Sudani, Ghaida A. Al-Suhail
    1st International Conference on Emerging Technologies for Dependable Internet of Things Iceti 2024, 2024
  • AFB-GPSR: Adaptive Beaconing Strategy Based on Fuzzy Logic Scheme for Geographical Routing in a Mobile Ad Hoc Network (MANET)
    Raneen I. Al-Essa, Ghaida A. Al-Suhail
    Computation, 2023
  • A Service of RSU Communication in Internet of Vehicles (IoV) in Urban Environment
    Raneen I. Al-Essa, Ghaida A. Al-Suhail
    Lecture Notes in Networks and Systems, 2023
  • EEIT2-F: Energy-efficient aware IT2-fuzzy based clustering protocol in wireless sensor networks
    International Journal of Electrical and Computer Engineering, 2022
  • Synchronization of Monostatic Radar Using a Time-Delayed Chaos-Based FM Waveform
    Mariam H. Abd, Ghaida A. Al-Suhail, Fadhil R. Tahir, Ahmed M. Ali Ali, Hamza A. Abbood, et al.
    Remote Sensing, 2022
  • An Efficacy of Transmission Power on DYMO Routing Protocol in VANET
    Raneen I. Al-Essa, Ghaida A. Al-Suhail
    Proceedings 2022 International Conference on Engineering and MIS Icemis 2022, 2022
  • A Fuzzy Based Clustering Approach to Prolong the Network Lifetime in Wireless Sensor Networks
    Enaam A. Al-Hussain, Ghaida A. Al-Suhail
    Lecture Notes in Networks and Systems, 2022
  • A QoS Evaluation of AODV Topology-Based Routing Protocol in VANETs
    Israa A. Aljabry, Ghaida A. Al-Suhail
    Proceedings 2022 International Conference on Engineering and MIS Icemis 2022, 2022
  • Towards Energy Savings in Cluster-Based Routing for Wireless Sensor Networks
    Enaam A. Al-Hussain, Ghaida A. Al-Suhail
    Lecture Notes in Networks and Systems, 2022
  • Mobility and Transmission Power of AODV Routing Protocol in MANET
    Raneen I. Al-Essa, Ghaida A. Al-Suhail
    2022 2nd International Conference on Computing and Machine Intelligence Icmi 2022 Proceedings, 2022
  • Improving the Route Selection for Geographic Routing Using Fuzzy-Logic in VANET
    Israa A. Aljabry, Ghaida A. Al-Suhail
    Lecture Notes in Networks and Systems, 2022
  • A Simulation of AODV and GPSR Routing Protocols in VANET Based on Multimetrices
    Israa Aljabry, Ghaida Al-Suhail
    Iraqi Journal for Electrical and Electronic Engineering, 2021

RECENT SCHOLAR PUBLICATIONS

  • Alzheimer’s Disease Diagnose using Deep Learning for Brain MRI Images: A Comparative Analysis
    HA Alahmed, GA Al-Suhail
    Iraqi Journal for Electrical and Electronic Engineering 22 (1), 486-501 , 2026
    2026
    Citations: 5
  • Brain Tumor Prediction from Magnetic Resonance Images
    HA Alahmed, GA Al-Suhail
    Iraqi Journal of Intelligent Computing and Informatics (IJICI) 5 (1), 13-23 , 2026
    2026
    Citations: 1
  • ResNet-OSD: an optimized hybrid deep learning framework for oil spill detection in coastal drone imagery
    IA Al-Sudani, GA Al-Suhail
    The Visual Computer 42 (3), 165 , 2026
    2026
  • Next-Generation of Smart Healthcare: A Review of Emerging AI Technologies and Their Clinical Applications
    H Ahmed, G Al-Suhail, AA Abood
    International Journal of Mechatronics, Robotics, and Artificial Intelligence … , 2025
    2025
    Citations: 3
  • Explainable AI-based Deep Learning for Brain Tumor MRI Analysis: A Review
    SJ Mohammed, GA Al-Suhail
    2025 6th International Conference on Communications, Information, Electronic … , 2025
    2025
  • LCxNet: An Explainable CNN Framework for Lung Cancer Detection in CT Images Using Multi-Optimizer and Visual Interpretability
    NS Jozi, GA Al-Suhail
    Applied System Innovation 8 (5), 153 , 2025
    2025
    Citations: 6
  • Design and FPGA implementation of a hyper-chaotic system for real-time secure image transmission
    ABA Al-Hussein, FR Tahir, GA Al-Suhail
    Iraqi J. Electr. Electron. Eng 21, 55-68 , 2025
    2025
    Citations: 6
  • AlzONet: a deep learning optimized framework for multiclass Alzheimer’s disease diagnosis using MRI brain imaging
    HA Alahmed, GA Al-Suhail
    The Journal of Supercomputing 81 (2), 423 , 2025
    2025
    Citations: 20
  • W-GPSR Routing Based on Mobility Prediction for Vehicular Ad-Hoc Network (VANET)
    ALE Raneen, G Al-Suhail
    Iraqi Journal for Electrical and Electronic Engineering 21 (2), 145-159 , 2025
    2025
    Citations: 1
  • Energy-Aware Clustering Using Intelligent Scheme for Heterogeneous Wireless Sensor Networks
    EA Al-Hussain, GA Al-Suhail
    Karbala International Journal of Modern Science 11 (2), 3 , 2025
    2025
  • Lung cancer detection: The role of transfer learning in medical imaging
    NS Jozi, GA Al-Suhail
    2024 International Conference on Future Telecommunications and Artificial … , 2024
    2024
    Citations: 5
  • A comparative study of VGG16 and VGG19 for oil spill detection in coastal imagery
    IA Al-Sudani, GA Al-Suhail
    2024 1st International Conference on Emerging Technologies for Dependable … , 2024
    2024
    Citations: 5
  • Exploring transfer learning techniques for brain tumor diagnosis in MRI data
    HA Alahmed, GA Al-Suhail
    2024 1st International Conference on Emerging Technologies for Dependable … , 2024
    2024
    Citations: 10
  • Image-based oil spill detection using deep learning techniques: A review
    IA Al-Sudani, GA Al-Suhail
    2024 5th International Conference on Communications, Information, Electronic … , 2024
    2024
    Citations: 10
  • Lung Cancer Detection in Radiological Imaging using Deep Learning: A Review
    NS Jozi, GA Al-Suhail
    2024 5th International Conference on Communications, Information, Electronic … , 2024
    2024
    Citations: 7
  • Medical image classification using deep learning for brain tumors detection: An overview
    HA Alahmad, GA Al-Suhail
    International Conference on Intelligent Computing & Optimization, 194-207 , 2023
    2023
    Citations: 7
  • AFB-GPSR: Adaptive Beaconing Strategy Based on Fuzzy Logic Scheme for Geographical Routing in a Mobile Ad Hoc Network (MANET)
    RI Al-Essa, GA Al-Suhail
    Computation 11 (174), 27 , 2023
    2023
    Citations: 25
  • A Service of RSU Communication in Internet of Vehicles (IoV) in Urban Environment
    RI Al-Essa, GA Al-Suhail
    Computational Intelligence, Data Analytics and Applications, ICCIDA 2022 … , 2023
    2023
    Citations: 3
  • AFB-GPSR: Adaptive Beaconing Strategy Based on Fuzzy Logic Scheme for Geographical Routing in a Mobile Ad Hoc Network (MANET). Computation 2023, 11, 174
    RI Al-Essa, GA Al-Suhail
    2023
    Citations: 1
  • A QoS Evaluation of AODV Topology-Based Routing Protocol in VANETs
    IA Aljabry, GA Al-Suhail
    2022 International Conference on Engineering & MIS (ICEMIS), 1-6 , 2022
    2022
    Citations: 9

MOST CITED SCHOLAR PUBLICATIONS

  • An adaptive observer synchronization using chaotic time-delay system for secure communication
    MH Abd, FR Tahir, GA Al-Suhail, VT Pham
    Nonlinear dynamics 90 (4), 2583-2598 , 2017
    2017
    Citations: 64
  • A Survey on Network Simulators for Vehicular Ad-hoc Networks (VANETS)
    IA Aljabry, GA Al-Suhail
    International Journal of Computer Applications 174, 8887 , 2021
    2021
    Citations: 56
  • Modelling of Long-Wave Chaotic Radar System for Anti-Stealth Applications
    GA Al-Suhail, FR Tahir, MH Abd, VT Pham, L Fortuna
    Communications in Nonlinear Science and Numerical Simulation (CNSNS), 2018 … , 2017
    2017
    Citations: 28
  • A Weighted Voting of K-Nearest Neighbor Algorithm for Diabetes Mellitus
    AH Khaleel, GA Al-Suhail, BM Hussan
    International Journal of Computer Science and Mobile Computing (IJCSMC) 6 (1 … , 2017
    2017
    Citations: 26
  • AFB-GPSR: Adaptive Beaconing Strategy Based on Fuzzy Logic Scheme for Geographical Routing in a Mobile Ad Hoc Network (MANET)
    RI Al-Essa, GA Al-Suhail
    Computation 11 (174), 27 , 2023
    2023
    Citations: 25
  • A Simulation of AODV and GPSR Routing Protocols in VANET Based on Multimetrices
    IA Aljabry, GA Al-Suhail
    Iraqi Journal for Electrical and Electronic Engineering (IJEEE) 17 (2), 66-72 , 2021
    2021
    Citations: 21
  • AlzONet: a deep learning optimized framework for multiclass Alzheimer’s disease diagnosis using MRI brain imaging
    HA Alahmed, GA Al-Suhail
    The Journal of Supercomputing 81 (2), 423 , 2025
    2025
    Citations: 20
  • E-FLEACH: An Improved Fuzzy Based Clustering Protocol for Wireless Sensor Network
    EA Al-Husain, GA Al-Suhail
    Iraqi Journal for Electrical and Electronic Engineering (IJEEE) 17 (2), 190-197 , 2021
    2021
    Citations: 15
  • Synchronization of Monostatic Radar Using a Time-Delayed Chaos-Based FM Waveform
    MH Abd, GA Al-Suhail, FR Tahir, AMA Ali, HA Abbood, K Dashtipour, ...
    Remote Sensing 14 (9), 1984 , 2022
    2022
    Citations: 14
  • Energy efficiency analysis of adaptive error correction in wireless sensor networks
    GA Al-Suhail, KW Louis, TY Abdallah
    International Journal of Computer Science Issues (IJCSI) 9 (4), 79 , 2012
    2012
    Citations: 14
  • Mobility and Transmission Power of AODV Routing Protocol in MANET
    RI Al-Essa, GA Al-Suhail
    2nd International Conference on Computing and Machine Intelligence (ICMI … , 2022
    2022
    Citations: 12
  • Error-resilience of TCP-friendly video transmission over wireless channel
    GA Al-Suhail, N Wakamiya, RS Fyath
    2006 9th International Conference on Control, Automation, Robotics and … , 2006
    2006
    Citations: 12
  • Client-server based wireless networked control system
    MJ Marie, GA Al-Suhail, S Al-Majeed
    2016 IEEE East-West Design & Test Symposium (EWDTS), 1-7 , 2016
    2016
    Citations: 11
  • Exploring transfer learning techniques for brain tumor diagnosis in MRI data
    HA Alahmed, GA Al-Suhail
    2024 1st International Conference on Emerging Technologies for Dependable … , 2024
    2024
    Citations: 10
  • Image-based oil spill detection using deep learning techniques: A review
    IA Al-Sudani, GA Al-Suhail
    2024 5th International Conference on Communications, Information, Electronic … , 2024
    2024
    Citations: 10
  • Improving the route selection for geographic routing using fuzzy-logic in vanet
    IA Aljabry, GA Al-Suhail
    International Conference on Intelligent Computing & Optimization, 958-967 , 2021
    2021
    Citations: 10
  • A fuzzy GPSR route selection based on link quality and neighbor node in VANET
    IA Aljabry, GA Al-Suhail, WA Jabbar
    2021 International Conference on Intelligent Technology, System and Service … , 2021
    2021
    Citations: 10
  • A QoS Evaluation of AODV Topology-Based Routing Protocol in VANETs
    IA Aljabry, GA Al-Suhail
    2022 International Conference on Engineering & MIS (ICEMIS), 1-6 , 2022
    2022
    Citations: 9
  • Towards ubiquitous human gestures recognition using wireless networks
    MS Aljumaily, GA Al-Suhail
    International Journal of Pervasive Computing and Communications 13 (4), 408-418 , 2017
    2017
    Citations: 9
  • Lung Cancer Detection in Radiological Imaging using Deep Learning: A Review
    NS Jozi, GA Al-Suhail
    2024 5th International Conference on Communications, Information, Electronic … , 2024
    2024
    Citations: 7