MUHAMMAD ABDULRAZZAQ THANOON

@uoninevah.edu.iq

College of Electronics Engineering\Department of Systems and Control Engineering
Nineveh University

MUHAMMAD ABDULRAZZAQ THANOON


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https://researchid.co/mohmmedalsayed
8

Scopus Publications

264

Scholar Citations

5

Scholar h-index

3

Scholar i10-index

Scopus Publications

  • A Symmetric Encoder–Decoder Network with Enhanced Group–Shuffle Modules for Robust Lung Nodule Detection in CT Scans
    Mohammad A. Thanoon, Siti Raihanah Abdani, Ahmad Asrul Ibrahim, Asraf Mohamed Moubark, Nor Azwan Mohamed Kamari, Muhammad Ammirrul Atiqi Mohd Zainuri, Mohd Hairi Mohd Zaman, Mohd Asyraf Zulkifley
    Biomimetics, 2026
    Lung cancer is considered to be a significant cause of death in the world, and the timely identification of nodules in the lungs in CT scans is very important to enhance the prognosis of patients. Although the state of the art of nodule delineation using deep learning-based segmentation models was achieved, major problems, including high feature diversity, low spatial discrimination, and overfitting of the models, require stronger feature-processing approaches. This research explores an enhanced symmetric encoder–decoder segmentation network known as the Improved Group–Shuffle Module (IGSM) to overcome these shortcomings. The most important feature of the proposed method is the IGSM, which hierarchically divides feature maps into a few groups, then transforms them independently, and then randomly switches channels between groups to increase inter-group interaction of features and diversity. This IGSM method is inspired by human brain functions, which are processed in specialized cortex areas, which are mimicked in this work through small-group feature processing. Channel shuffling is designed based on inter-modular communication in the human brain through coherent information sharing among the small groups of cortices. Through this mechanism, the model is much better at capturing discriminative spatial and contextual patterns, especially on complex and subtle nodule structures. The IGSM configurations have been optimized, specifically, the placement of the modules, grouping size, and shuffle permutation strategies. The proposed model’s performance is then compared with the benchmarked models, like U-Net and DeepLab, with various performance indicators such as mean Intersection over Union (mIoU), Dice Score, Accuracy, Sensitivity, and Specificity. The simulation results proved the superiority of the IGSM-enhanced model with the mIoU of 0.7735, the Dice Score of 0.9665, and the Accuracy of 0.9873. The addition of the group and shuffle module not only enhances the discrimination between the nodules and their background, but it also improves the ability to generalize over a variety of nodules’ morphology, thus producing a reliable tool for automated detection of lung cancer.
  • Boost Converter Control Using Proportional-Integral-Derivative Controller Optimized by Whale Optimization Algorithm
    Mohammad A Thanoon, Mohammed Almaged, Abdulla Ibrahim Abdulla
    International Journal of Robotics and Control Systems, 2025
    This work offers an improved control approach for a boost converter called WOA_PID by combining a Whale Optimization Algorithm (WOA) with a Proportional-Integral-Derivative (PID) controller. The main goal is to optimize the PID controller gains for better voltage control and improved system stability and performance. Although boost converters are employed for step-up DC-DC conversion, they have nonlinear dynamics and sudden load changes that create major problems in conventional controller tuning. This work guarantees improved transient response and lower steady-state error by using the WOA employed as an optimization tool to effectively optimize the PID gains by minimizing the Integral Square Error (ISE) performance index. Simulations are used to assess the suggested WOA_PID controller, which showed better performance than traditional PID tuning techniques. The key aspects are zero overshoot, quicker rise and settling time of 0.216 and 0.654 respectively as well as improved output voltage control under changing load situations. Findings verify the efficiency of the WOA-based tuning approach in optimizing the PID controller for boost converters, providing a robust solution for practical applications in power electronics.
  • A Review of Deep Learning Techniques for Lung Cancer Screening and Diagnosis Based on CT Images
    Mohammad A. Thanoon, Mohd Asyraf Zulkifley, Muhammad Ammirrul Atiqi Mohd Zainuri, Siti Raihanah Abdani
    Diagnostics, 2023
    One of the most common and deadly diseases in the world is lung cancer. Only early identification of lung cancer can increase a patient’s probability of survival. A frequently used modality for the screening and diagnosis of lung cancer is computed tomography (CT) imaging, which provides a detailed scan of the lung. In line with the advancement of computer-assisted systems, deep learning techniques have been extensively explored to help in interpreting the CT images for lung cancer identification. Hence, the goal of this review is to provide a detailed review of the deep learning techniques that were developed for screening and diagnosing lung cancer. This review covers an overview of deep learning (DL) techniques, the suggested DL techniques for lung cancer applications, and the novelties of the reviewed methods. This review focuses on two main methodologies of deep learning in screening and diagnosing lung cancer, which are classification and segmentation methodologies. The advantages and shortcomings of current deep learning models will also be discussed. The resultant analysis demonstrates that there is a significant potential for deep learning methods to provide precise and effective computer-assisted lung cancer screening and diagnosis using CT scans. At the end of this review, a list of potential future works regarding improving the application of deep learning is provided to spearhead the advancement of computer-assisted lung cancer diagnosis systems.
  • LQR CONTROLLER DESIGN FOR STABILIZATION OF NON-LINEAR DIP SYSTEM BASED ON ABC ALGORITHM
    Mohammad A. Thanoon, Sohaib R. Awad, Ismael Kh. Abdullah
    Eastern European Journal of Enterprise Technologies, 2023
    Inverted pendulum systems, such as double or single, rotational or translational inverted pendulums are non-linear and unstable, which have been the most dominant approaches for control systems. The double inverted pendulum is one kind of a non-linear, unstable system, multivariable, and strong coupling with a wide range of control methods. To model these types of systems, many techniques have been proposed so that motivating researchers to come up with new innovative solutions. The Linear Quadratic Regulator (LQR) controller has been a common controller used in this field. Meanwhile, the Artificial Bee Colony (ABC) technique has become an alternative solution for employing Bee Swarm Intelligence algorithms. The research solutions of the artificial bee colony algorithm in the literature can be beneficial, however, the utilization of discovered sources of food is ineffective. Thus, in this paper, we aim to provide a double inverted pendulum system for stabilization by selecting linear quadratic regulator parameters using a bio-inspired optimization methodology of artificial bee colony and weight matrices Q and R. The results show that when the artificial bee colony algorithm is applied to a linear quadratic regulator controller, it gains the capacity to autonomously tune itself in an online process. To further demonstrate the efficiency and viability of the suggested methodology, simulations have been performed and compared to conventional linear quadratic regulator controllers. The obtained results demonstrate that employing artificial intelligence (AI) together with the proposed controller outperforms the conventional linear quadratic regulator controllers by more than 50 % in transient response and improved time response and stability performance
  • Performance analysis and evaluation of distance vector and link state routing protocols over a large area networks
    Abdulhameed N. Hameed, Salah Abdulghani Alabady, Mohammad A. Thanoon
    Telkomnika Telecommunication Computing Electronics and Control, 2022
    Routing protocols are extremely important incredibly significant in data communication and computer networks. The high performance, reliability, stability, and security of the networks depend primarily on choosing the best type of dynamic routing protocol. In this paper, we evaluate and investigate the network performance for routing information protocol (RIP), enhanced interior gateway routing protocol (EIGRP), open shortest path first (OSPF), and intermediate system-to-intermediate system (IS-IS) routing protocols with three different scenarios of routes failure using the optimized network engineering tools (OPNET) simulator to determine which of the protocols is the most appropriate and effective in achieving high network performance. The results show that for large area networks, the EIGRP routing protocol gives the best network performance when all network routers are working with no failing, but when some network routers were failing to work and path failure is happening, the IS-IS link-state routing protocol works efficiently and gives the best performance. The obtained results for IS-IS protocol when failing seven routers is as: the hypertext transfer protocol (HTTP) page response time is (247.8 msec), voice delay variation is (4.19 µsec), video delay variation is (8.83 µsec) and ping request and response time is (115 msec).
  • Design of a Linear Quadratic Regulator Based on Genetic Model Reference Adaptive Control
    Abdullah Abdullah, Ali Mahmood, Mohammad Thanoon
    Journal of Automation Mobile Robotics and Intelligent Systems, 2022
    As the conventional control system is a controller that controls or regulates the dynamics of any other process. From time to time, this control system may not behave appropriately online; this is because of many factors like some variation in the dynamics of the process itself or unexpected changes in the environment, or even undefined parameters of the system model. To overcome the problem above, an adaptive controller is designed and implemented. This paper discusses the design of a controller for a ball and beam system with Genetic Model Reference Adaptive Control (GMRAC) for adaptive mechanism with the MIT rule. Parameter adjustment (selection) should be done using optimization methods in order to obtain an optimal performance, so genetic algorithm. (GA) will be used as an optimization method to obtain the optimum values for these parameters. As the controller, a Linear quadratic regulator (LQR) controller will be used as it is one of the most popular controllers, the performance of the proposed controller with the ball and beam system will be carried out with MATLAB Simulink in order to evaluate its effectiveness. The results show satisfactory performance where the position of the ball tracks the desired model reference.
  • Stabilization of Three Links Inverted Pendulum with Cart Based on Genetic LQR Approach
    Abdullah Ibrahim Abdullah, Yazen Hudhaifa Shakir Alnema, Mohammad A. Thanoon
    Journal Europeen Des Systemes Automatises, 2022
    This academic paper demonstrates the implementation of a Linear Quadratic Regulator (LQR) controller design for optimal controlling a three connected links in an inverted pendulum form that attached to a moving cart to realize the stability of making a pendulum in a straight vertical line via translation of the cart left and right. To maintain a triple link inverted pendulum (TLIP) vertical, genetic algorithm has been employed to adjust and tune the parameters of LQR, which are the weighting matrices Q and R instead of the approach of try and error. In this article, a hybrid control algorithm (GA-LQR) proposed to select the optimal values of weighting matrices to overcome LQR design difficulties, which gives the best transient response requirements such as percentage overshoot and steady state error. The triple link inverted pendulum is model mathematically modelled in MATLAB platform to simulate the actual system where the results from the simulation gives acceptable and adequate performance of LQR controller in making the system stable.
  • Feature Selection Based on Wrapper and Information Gain
    Mohammad A. Thanoon, Mohammad J.M Zedan, Abdulhameed N. Hameed
    Nicst 2019 1st Al Noor International Conference for Science and Technology, 2019
    The accuracy of the classification process always suffers from the high dimensionality problem due to the independent, irrelevant, redundant and not useful attributes of the dataset. In this research, feature selection techniques (wrapper selection method, and information gain method) are obtained to handle the mentioned problem by removing those features and reducing the dataset dimensions. The techniques include wrapper selection method and information gain method. This research predicates on the diabetes dataset in WEKA application, which contains checking seven models enforce wrapper selection method as an attribute evaluator, forwarding direction, backward, and bi-directional best-first search method and Naïve Bayes technique as a classifier method, checking eight models applying information gain method as attribute evaluator, as well as the ranker as a search method. Additional to demonstrate the decision tree and classification figures for the best-obtained models in each one technique. The results proved the ability of wrapper and information gain to choose a minimum number of features in order to classify the data with an accuracy of more than 76% in this work.

RECENT SCHOLAR PUBLICATIONS

  • A Symmetric Encoder–Decoder Network with Enhanced Group–Shuffle Modules for Robust Lung Nodule Detection in CT Scans
    MA Thanoon, SR Abdani, AA Ibrahim, A Mohamed Moubark, NAM Kamari, ...
    Biomimetics 11 (2), 92 , 2026
    2026.0
  • Boost Converter Control Using Proportional-Integral-Derivative Controller Optimized by Whale Optimization Algorithm
    AIA Mohammad A Thanoona,Mohammed Almageda
    International Journal of Robotics and Control Systems 5 (3), 1850-1865 , 2025
    2025.0
    Citations: 3
  • A Review of Deep Learning Techniques for Lung Cancer Screening and Diagnosis Based on CT Images
    SRA Mohammad A. Thanoon,Mohd Asyraf Zulkifley,Muhammad Ammirrul Atiqi Mohd ...
    Diagnostics , 2023
    2023.0
    Citations: 202
  • LQR CONTROLLER DESIGN FOR STABILIZATION OF NON-LINEAR DIP SYSTEM BASED ON ABC ALGORITHM
    IK Thanoon, M.A. , Awad, S.R. , Abdullah
    Eastern-European Journal of Enterprise Technologies 2 ((2-122)2023), 36-44 , 2023
    2023.0
  • A Review of Deep Learning Techniques for Lung Cancer Screening and Diagnosis Based on CT Images. Diagnostics. 2023; 13 (16): 2617
    MA Thanoon, MA Zulkifley, MA Mohd Zainuri, SR Abdani
    2023.0
    Citations: 7
  • A review of deep learning techniques for lung cancer screening and diagnosis based on CT images. Diagnostics, 13 (16), 2617
    MA Thanoon, MA Zulkifley, MAA Mohd Zainuri, SR Abdani
    2023.0
    Citations: 15
  • Performance analysis and evaluation of distance vector and link state routing protocols over a large area networks
    AN Hameed, SA Alabady, MA Thanoon
    Telkomnika (Telecommunication computing electronics and control) 20 (6 … , 2022
    2022.0
    Citations: 3
  • Stabilization of three links inverted pendulum with cart based on genetic LQR approach
    AI Abdullah, YHS Alnema, MA Thanoon
    Journal Européen des Systèmes Automatisés 55 (1), 125-130 , 2022
    2022.0
    Citations: 4
  • Design of Linear Quadratic Regulator Based on Genetic Model Reference Adaptive Control
    A Abdullah, A Mahmood, M Thanoon
    Journal of Automation, Mobile Robotics and Intelligent Systems, 75-81 , 2022
    2022.0
    Citations: 4
  • Feature selection based on wrapper and information gain
    MA Thanoon, MJM Zedan, AN Hameed
    2019 1st AL-Noor International Conference for Science and Technology (NICST … , 2019
    2019.0
    Citations: 16
  • Forecasting USD/IQD Future Values According to Minimum RMSE Rate
    JK Shareef, MA Thanoon, WR Abdulhussien
    International Journal of Computer Science and Mobile Computing 4 (4), 271-285 , 2015
    2015.0
    Citations: 6
  • Prediction of International Stock Market Movement Using Technical Analysis Methods and TSK
    MA Thanoon
    Eastern Mediterranean University (EMU)-Doğu Akdeniz Üniversitesi (DAÜ) , 2014
    2014.0
    Citations: 1
  • A Review of Deep Learning Techniques for Lung Cancer Screening and Diagnosis Based on CT Images. Diagnostics 2023; 13
    MA Thanoon, MA Zulkifley, MAA Mohd Zainuri, SR Abdani
    Citations: 3

MOST CITED SCHOLAR PUBLICATIONS

  • A Review of Deep Learning Techniques for Lung Cancer Screening and Diagnosis Based on CT Images
    SRA Mohammad A. Thanoon,Mohd Asyraf Zulkifley,Muhammad Ammirrul Atiqi Mohd ...
    Diagnostics , 2023
    2023.0
    Citations: 202
  • Feature selection based on wrapper and information gain
    MA Thanoon, MJM Zedan, AN Hameed
    2019 1st AL-Noor International Conference for Science and Technology (NICST … , 2019
    2019.0
    Citations: 16
  • A review of deep learning techniques for lung cancer screening and diagnosis based on CT images. Diagnostics, 13 (16), 2617
    MA Thanoon, MA Zulkifley, MAA Mohd Zainuri, SR Abdani
    2023.0
    Citations: 15
  • A Review of Deep Learning Techniques for Lung Cancer Screening and Diagnosis Based on CT Images. Diagnostics. 2023; 13 (16): 2617
    MA Thanoon, MA Zulkifley, MA Mohd Zainuri, SR Abdani
    2023.0
    Citations: 7
  • Forecasting USD/IQD Future Values According to Minimum RMSE Rate
    JK Shareef, MA Thanoon, WR Abdulhussien
    International Journal of Computer Science and Mobile Computing 4 (4), 271-285 , 2015
    2015.0
    Citations: 6
  • Stabilization of three links inverted pendulum with cart based on genetic LQR approach
    AI Abdullah, YHS Alnema, MA Thanoon
    Journal Européen des Systèmes Automatisés 55 (1), 125-130 , 2022
    2022.0
    Citations: 4
  • Design of Linear Quadratic Regulator Based on Genetic Model Reference Adaptive Control
    A Abdullah, A Mahmood, M Thanoon
    Journal of Automation, Mobile Robotics and Intelligent Systems, 75-81 , 2022
    2022.0
    Citations: 4
  • Boost Converter Control Using Proportional-Integral-Derivative Controller Optimized by Whale Optimization Algorithm
    AIA Mohammad A Thanoona,Mohammed Almageda
    International Journal of Robotics and Control Systems 5 (3), 1850-1865 , 2025
    2025.0
    Citations: 3
  • Performance analysis and evaluation of distance vector and link state routing protocols over a large area networks
    AN Hameed, SA Alabady, MA Thanoon
    Telkomnika (Telecommunication computing electronics and control) 20 (6 … , 2022
    2022.0
    Citations: 3
  • A Review of Deep Learning Techniques for Lung Cancer Screening and Diagnosis Based on CT Images. Diagnostics 2023; 13
    MA Thanoon, MA Zulkifley, MAA Mohd Zainuri, SR Abdani
    Citations: 3
  • Prediction of International Stock Market Movement Using Technical Analysis Methods and TSK
    MA Thanoon
    Eastern Mediterranean University (EMU)-Doğu Akdeniz Üniversitesi (DAÜ) , 2014
    2014.0
    Citations: 1
  • A Symmetric Encoder–Decoder Network with Enhanced Group–Shuffle Modules for Robust Lung Nodule Detection in CT Scans
    MA Thanoon, SR Abdani, AA Ibrahim, A Mohamed Moubark, NAM Kamari, ...
    Biomimetics 11 (2), 92 , 2026
    2026.0
  • LQR CONTROLLER DESIGN FOR STABILIZATION OF NON-LINEAR DIP SYSTEM BASED ON ABC ALGORITHM
    IK Thanoon, M.A. , Awad, S.R. , Abdullah
    Eastern-European Journal of Enterprise Technologies 2 ((2-122)2023), 36-44 , 2023
    2023.0