MS: Recent submissions

  • Energy Harvesting with Speed Bumps 
    PROJECT SUPERVISOR LECTURER SUFYAN HAFEEZ KHAN, NC ABDUL HASEEB QAMAR NC ABDUL MOIZ MAZHAR NC HUMAYUN IMTIAZ KHAN (College of Electrical & Mechanical Engineering (CEME), NUST, 2020)
    peed bumps are commonly employed for the purpose of controlling traffic speed, and hence ensuring safety measures for pedestrians. The purpose of this project is to generate electrical power ranging up to several hundred ...
  • Data-driven framework for failure prediction and classification in industrial machines 
    Abid, Aaisha (College of Electrical & Mechanical Engineering (CEME), NUST, 2025-01)
    In this work, an advanced deep learning-based hierarchical diagnosis framework for industrial machinery is presented. The proposed Hierarchical Fault Diagnosis Network (HFDN) model uses a layered architecture to decompose ...
  • DEVELOPMENT OF SIMPLIFIED ELECTROCHEMICAL MODEL FOR LI ION BATTERY 
    BANO, BEENISH (College of Electrical & Mechanical Engineering (CEME), NUST, 2024-12)
    Advanced battery management systems (BMS) rely on accurate and computationally efficient models of Li-ion cells to ensure optimal operation, as the performance of BMS charging and estimation algorithms is directly influenced ...
  • Performance Evaluation of Wireless Communication System in Critical Propagation Scenarios Using Artificial Intelligence Algorithms 
    TAHIR, BILAL (College of Electrical & Mechanical Engineering (CEME), NUST, 2024-12)
    Modern wireless systems for mobile communication use electromagnetic waves to transmit information over the air, enabling seamless connectivity for a wide range of devices. However, one of the key challenges in wireless ...
  • PLI Removal from ECG Signal using Adaptive Algorithms 
    Javeria Habib (College of Electrical & Mechanical Engineering (CEME), NUST, 2016)
    Electrocardiogram (ECG) is the graphical illustration of heart activity to diagnose various cardiovascular diseases. Presence of Power Line Interference (PLI) in ECG makes it difficult for the examiner to identify proper ...
  • Speed Control of Induction Motor through PI-ANN Controller 
    SIDDIQUE, ZARA (College of Electrical & Mechanical Engineering (CEME), NUST, 2024-10)
    An induction motor is also called an asynchronous motor – it is an AC electric motor used extensively in applications. This particular type of motor is utilized in the majority of industrial and commercial electrical ...
  • Integrated Control of Parallel Connected Multiple SEPIC Converters For DC Microgrid Operation 
    ALI, MANZAR (College of Electrical & Mechanical Engineering (CEME), NUST, 2024-10)
    DC microgrids are gaining popularity now a days due to their advantages such as improved efficiency, reliability, and renewable energy integration and also due the environmental challenges like carbon and other greenhouse ...
  • Diagnosis of Major Depressive Disorder with a Hybrid Neural Network 
    Haider, Fakhar (College of Electrical & Mechanical Engineering (CEME), NUST, 2024-10)
    This thesis employs hybrid neural networks to process electroencephalography (EEG) data to provide an accurate diagnosis of major depressive disorder (MDD). Since EEG Data is of spatiotemporal nature, a hybrid neural ...
  • Design of a Ku Band Monopulse Comparator using ESIW for Tracking Radars 
    SALEEM, MUHAMMAD OSAMA (College of Electrical & Mechanical Engineering (CEME), NUST, 2024-10)
    This is a research work that puts forward the design and development of a Ku Band Monopulse Comparator utilizing ESIW technology into radar tracking applications. Being introduced into radar systems, it gives off several ...
  • EEG-based Detection of Directed Effective Connectivity and Microstate Analysis in Stress Disorder 
    AMAN, AKASHA (College of Electrical & Mechanical Engineering (CEME), NUST, 2024-10)
    Stress is a common phenomenon that affects individuals from all walks of life and it is associated with physical and physiological illness. Brain plays a key role in determining stress. This study represents the comprehensive ...
  • EEG-Based Early Detection of Parkinson’s Disease Using Deep Learning 
    Hussain, Syed Moiz (College of Electrical & Mechanical Engineering (CEME), NUST, 2024-10)
    This thesis introduces a unique approach using neural networks to enhance Parkinson’s disease (PD) classification and predict its severity through novel analyses of the Default Mode Network (DMN) via electroencephalogram ...
  • Deep learning-based traffic accident detection and severity classification in video surveillance. 
    KAZMI, SYED ATEEB ALI (College of Electrical & Mechanical Engineering (CEME), NUST, 2024-09)
    Since there has been an increase in the number of cars on the road, there is need to fast identify accident-prone areas and respond to them promptly. This Thesis aims at finding the suitability of employing state-of-the-art ...
  • Speed Control of Solar Powered DC Motor through PI-ANN Controller 
    MALIK, HAMZA ISMAIL (College of Electrical & Mechanical Engineering (CEME), NUST, 2024)
    In recent years a lot of work has been done regarding energy generation from photovoltaics (PV). A Separately Excited DC Motor (SEDM) is the most used machine, especially in the power industry. Footings, transports, ...
  • Boost Inverter Based Variable Frequency Drive for Induction Motor 
    Riaz, Talha (College of Electrical & Mechanical Engineering (CEME), NUST, 2024)
    The fast expansion of renewable energy sources, including solar systems, fuel cells, and wind turbines, necessitates the development of efficient power conversion technology to manage their fluctuating voltage profiles.To ...
  • AI based Early Prediction of Alzheimer’s Disease using Neuropsychological Tests 
    KHAN, MUHAMMAD ALI WARIS (College of Electrical & Mechanical Engineering (CEME), NUST, 2024-09)
    Within the field of biomedical engineering, a novel imputation model employing machine learning techniques is proposed as a unique approach for the early diagnosis of Alzheimer's disease (AD). Early identification is ...
  • A Neural Network on Biomedical Knowledge Graph for the Prediction of Drug-Drug Interactions 
    KUNDI, IQRA NASEER (College of Electrical & Mechanical Engineering (CEME), NUST, 2024-08)
    Effective drug combination prediction is crucial for the achievement of drug discovery, but it is a challenging task due to drug drug interactions and potential adverse drug reactions. This study presents an innovative ...
  • DAB based Three Phase Boost Inverter for Higher Power Applications 
    Ahmed, Nafees (College of Electrical & Mechanical Engineering (CEME), NUST, 2024-08)
    This thesis describes of DAB-based boost inverter. Induction heating, defence equipment, electric motor speed control, grid-connected and standalone inverters, uninterruptible power supplies, and dual active bridge (DAB) ...
  • Control Aware Path Planning For Self-Driving Car 
    Suhail, Muhammad Zaid (College of Electrical & Mechanical Engineering (CEME), NUST, 2024-08)
    Self-driving cars represent a significant advancement in autonomous systems, aiming to revolutionize transportation by enhancing passenger safety and reducing human-driving errors. While existing research has focused on ...
  • Autonomous Bidirectional Converter for Electric Vehicles in DC Microgrid 
    JAMAL, MOIZ (College of Electrical & Mechanical Engineering (CEME), NUST, 2024-08)
    This paper proposes a bidirectional resonant DC-DC converter with high efficiency and highpower density while keeping the cost minimized over a wide range of battery voltages. In the forward mode, the resonant boost ...
  • Fault Diagnosis and Localization of Solar Photovoltaic Fed Cascaded H-Bridge Multi-Level Inverter 
    Ashfaq, Iqra (College of Electrical & Mechanical Engineering (CEME), NUST, 2024-08)
    This research introduces a deep learning approach for detecting and localizing switch faults in Photovoltaic (PV) systems, specifically targeting PV fed cascaded H-bridge 5-level inverters. The study’s primary focus is ...

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