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MS: Recent submissions

Now showing items 161-180 of 881

EEG based Emotion Recognition

Chaudary, Eamin (School of Electrical Engineering and Computer Sciences (SEECS), NUST, 2023)

Accurate detection of emotion plays a vital role in field of Human-Robot Interaction (HRI). Human Robot Interaction (HRI) robots aim for social intelligence, allowing them to recognize and respond to human emotional ...
Artificial neural network based MPPT and conditional controllers with saturated action for multi-renewable hybrid alternating or direct current microgrids in islanded and grid-connected Modes

Ghias, Rimsha (School of Electrical Engineering and Computer Sciences (SEECS), NUST, 2023)

In the face of energy uncertainty, the microgrid stands as a beacon of resilience, offering a lifeline to communities, businesses, and critical infrastructure. With its ability to seam lessly switch between conventional ...
EEG Based Sentimental Analysis

Khan, Sheeraz Ahmad (School of Electrical Engineering and Computer Sciences (SEECS) NUST, 2023)

One of the main challenges for biomedical researchers is to recognize emotions from elec troencephalogram (EEG) signals, which are non-invasive measurements of the brain’s electrical activity. EEG signals are complex and ...
Placement and sum-rate maximization of IRS enhanced next generation networks using machine learning

Khan, Muhammad Abdullah (School of Electrical Engineering and Computer Sciences (SEECS), NUST, 2023)

From the introduction of wireless communication to the development and deployment of forth generation of wireless telecommunication systems, the speed of reliability of communication between human users was prioritized. ...
NeuralGrip: Enhanced Motor Imagery Training and Testing for Assistive Robots Using Deep Learning and Advanced Data Augmentation Techniques

Mushtaq, Savera (School of Electrical Engineering and Computer Sciences (SEECS), NUST, 2023)

About 1.3 billion people in the globe have some sort of motor disability. This amounts to sixteen percent of the entire human population. Disabling in nature, these conditions provide fresh difficulties to those who live ...
Artificial intelligence based robust nonlinear controllers optimized by improved gray wolf optimization algorithm for plug-in hybrid electric vehicles in grid to vehicle applications

Saleem, Shabab (School of Electrical Engineering and Computer Sciences (SEECS) NUST, 2023)

The paper introduces a control strategy for a plug-in hybrid electric vehicle (PHEV) system, integrating a photovoltaic-based RES with battery and supercapacitor-based ESS. The objective is to efficiently utilize the PV ...
Optimal wireless power transfer to hybrid energy storage system for electric vehicles: A comparative analysis of machine learning-based model-free controllers

Shah, Syed Hassan Ahmed (School of Electrical Engineering and Computer Sciences (SEECS), NUST, 2023)

Wireless charging technology for electric vehicles (EVs) is gaining popularity as a result of advancements in battery technology and government incentives. It offers convenience, efficiency, and safety and is much quicker ...
Nonlinear Control of Flywheel based Hybrid Energy Storage System of Plug-in Electrical Vehicle

Mazhar, Noor Us Sabah (School of Electrical Engineering and Computer Sciences (SEECS), NUST, 2023)

The imperative drive for evolution within the electric vehicle (EV) sector, aimed at pro moting clean energy generation, has yielded remarkable advancements in recent times. Among these advancements, plug-in hybrid electric ...
Control of Multiport Converter to Integrate Solar PV and Energy Storage for Renewable Energy Applications

Shah, Syed Qasim (School of Electrical Engineering and Computer Science (SEECS), NUST, 2019)

DC-DC power converters have wide area of applications such as renewable energy, electric vehicle and smart grid system. Recently, great development is being made in power electronics dealing with renewable energy ...
Sonification of EEG for Anomaly Detection

Khitab, Umer (School of Electrical Engineering and Computer Science (SEECS), NUST, 2019)

The EEG is a technique which is utilized to monitor the electrical action of the brain. The communication between brain cells is through these electrical signals. An EEG is used to detect the possible issues which are ...
Spectrum Sensing: An integrated approach for 6G VANETs

Riaz, Umair (School of Electrical Engineering and Computer Science (SEECS), NUST, 2023)

To fulfill the needs of exponentially growing automobiles’ users and to provide services with efficient paths among different bands on demand for these proliferated users, an integrated approach for software-defined ...
Nonlinear control of DC microgrid integrated with renewable energy sources

Zehra, Syeda Shafia (School of Electrical Engineering and Computer Science (SEECS), NUST, 2020)

To minimize the impact of global warming, DC microgrids are widely used to fulfil the load requirement where connection with the main grid is laborious. The integration and control of a DC microgrid with PV and wind ...
Comparative analysis of mitigation techniques of quantum decoherence for quantum communication using Quantum channel

Khan, Muhammad Annas (School of Electrical Engineering and Computer Science (SEECS), NUST, 2023)

In the aftermath of unparalleled disruptive technologies, the quantum realm has emerged as a fundamental field of research, offering unrivaled computational power and super-secure communication. In addition to the conventional ...
Self-Supervision Based Learning to Move Obstacles for Path Planning

Zafar, Suneela (School of Electrical Engineering and Computer Science (SEECS), NUST, 2020)

Navigation among movable obstacles (NAMO) has been a research problem for many robotics researchers. The work presented so far includes moving obstacles out of the way and to plan shorter paths. However this interaction with ...
Nonlinear Control for Induction motor and comparison with vector control techniques

Munir, Shanza (School of Electrical Engineering and Computer Science (SEECS), NUST, 2020)

Induction motor is a complex nonlinear structure where strong coupling exists between rotor flux and produced electromagnetic torque.So, different decoupling techniques are applied to decouple the system which make ...
Adversarial Attacks on Deep Neural Networks (DNNs)

Salah ud Din (School of Electrical Engineering and Computer Science (SEECS), NUST, 2019)

Deep neural networks (DNNs) are extensively being used in multiple fields ranging from object classification and medical image analysis to self-driving cars. Vulnerability of such networks to the adversarial perturbations ...
Integration of E-Technologies in ESL Classrooms Evaluating the Impact of ICT-Intensive Pedagogy on English Speaking Skills of learners of primary schools

Saeed, Saira (School of Electrical Engineering and Computer Science (SEECS), NUST, 2019)

The integration of educational technologies to teach English Speaking skills in public sector primary schools in Pakistan lacked due attention. Furthermore, learning objectives set in the Pakistani national curriculum ...
ANN-Barrier Function-Based Adaptive Robust Nonlinear Control of DC Microgrid

Komba, Sahr (School of Electrical Engineering and Computer Science (SEECS), NUST, 2021)

Recently, DC microgrids (DC-MGs) have gained an immense popularity due to their unique characteristics such as structural simplicity and implementation, high efficiency, high power quality, and their capability of ...
Context Aware Initial Search in 5G mmWave Systems

Zia-ul-Mustafa, Rida (School of Electrical Engineering and Computer Science (SEECS), NUST, 2019)

The wide bandwidth available at the millimeter wave (mm Wave) frequencies is expected to offer high data rates in the fifth generation (5G) of cellular networks. The technology implements directional transmission to ...
Fault Detection and Parameter Estimation

Jahangir, Noman (School of Electrical Engineering and Computer Science (SEECS), NUST, 2019)

Now showing items 161-180 of 881

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