Electrical Engineering: Recent submissions

  • 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 ...
  • Nonlinear Dynamics Based Formation Control of Multiagent Systems 
    Mazhar, Naveed (College of Electrical & Mechanical Engineering (CEME), NUST, 2024)
    In multiagent systems, agents work together based on their local interactions to achieve a common goal by following established rules. Compared to single agents, multiagent systems have grown in popularity because of ...
  • 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 ...
  • Modeling and Maximum Power Extraction from Perovskite Solar Cell 
    Yousaf, Zeeshan (College of Electrical & Mechanical Engineering (CEME), NUST, 2024-08)
    This study depicted maximum power extraction from perovskite solar cells under the noticeable current density – voltage (J-V) hysteresis. The main objectives of this study were to analyze the impact of scan rate on the ...
  • Electrical Vehicle Battery Charger Based On Cuk-Sepic Converter Design 
    Nadeem, Hajira (College of Electrical & Mechanical Engineering (CEME), NUST, 2024-08)
    This paper introduces a groundbreaking advancement in electric vehicle technology: a sophisticated single-stage battery charger featuring an isolated bridgeless (BLS) CukSEPIC converter (CSC). Operating seamlessly in ...
  • YOLO-Based Multi-Object Tracking with Reduced Order Observer for Target Trajectory Estimation 
    NOUMAN, MUHAMMAD (College of Electrical & Mechanical Engineering (CEME), NUST, 2024-06)
    This thesis presents an innovative and efficient approach to track multiple objects in a video sequence by integrating state-of-art You Only Look Once (YOLO) object detection framework with efficient Reduced Order ...
  • Enhancing Alzheimer’s Disease Detection Using MRI Scans Through Transfer Learning Approach 
    AFTAB, MUHAMMAD ALI (College of Electrical & Mechanical Engineering (CEME), NUST, 2024-07)
    Alzheimer's Disease (AD) is a pervasive neurodegenerative ailment, affecting a vast population globally and posing challenges for early and precise diagnosis within medical image analysis. Although machine learning and ...
  • Open Switch Fault Diagnosis of Cascaded H-Bridge Multi-Level Inverter Using Deep Learning 
    Arif, Muhammad Nouman (College of Electrical & Mechanical Engineering (CEME), NUST, 2024-07)
    Cascaded H-bridge 5-level inverters (CHB-5LIs) have gained significant traction in high-power applications owing to their capacity to generate fine quality output voltage with minimal harmonic distortion. However, their ...
  • Exploring Negative Group Delay in Passive Microwave Circuits 
    Supervisor Dr. Mojeeb bin Ihsan, NC Ali Raza Mustafa NC Bilal Khalid NC Subas Muhammad PC Samia Noor (College of Electrical and Mechanical Engineering (CEME), NUST, 2022)
    Group delay is an important factor of consideration while designing a circuit with minimum signal distortion. There have been various attempts to minimize this group delay using different techniques, one of such techniques ...
  • FEDERATED LEARNING: FROM PERSPECTIVE OF NODE PERFORMANCE 
    Aini, Qurat Ul Ain (College of Electrical & Mechanical Engineering (CEME), NUST, 2024)
    Federated Learning (FL) has arose as a groundbreaking approach in distributed machine learning, enabling collaborative global model training while upholding data privacy and security. This research highlights the importance ...

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