As artificial intelligence (AI) and machine learning (ML) systems increasingly influence high- stakes decisions in areas such as healthcare, finance, and hiring, concerns regarding bias and fairness have emerged as critical ...

This research explores the application of FL to the MNIST dataset, focusing on impact of system heterogeneity. The study involves two clients collaboratively training a machine learning model using the FedAvg algorithm, ...

The ongoing research delves into the intelligent transport protocol selection mechanism and bit-rate optimization on the face of protocol switching to enhance Quality of Experience (QoE) in dynamic network conditions. QoE ...

Significant progress has been made in developing optimal frameworks for spatial prediction in radio propagation environments, as they enhance various aspects of wireless networking. These predictions rely on a limited set ...

This work establishes a strong foundation in understanding the key physics concepts behind cryogenic transport in Gate-All-Around (GAA) nanowire MOSFETs. The findings contribute to a deeper understanding of device behavior ...

Decentralization is a major constitute of blockchain technology, ensuring robustness, resilience, and trust. However, achieving true decentralization requires validators to be geographically diverse. This research focuses ...

As semiconductor technology advances toward higher integration and functional density, the challenges associated with Design-for-Testability (DFT) have become increasingly significant, particularly in terms of power ...

This thesis work focuses on advancements in neural style transfer, a process that enables the blending of content and style features to generate stylized images. It explores feature extraction using two encoders: a VGG19-based ...

This thesis introduces a novel framework for language translation, transitioning from conventional text-based mapping to a phoneme-level modeling approach. By employing articulatory phoneme representations and sparse binary ...