PORTO @ Archivio Istituzionale della Ricerca

SpyKing—Privacy-preserving framework for Spiking Neural Networks

Artificial intelligence (AI) models, frequently built using deep neural networks (DNNs), have become integral to many aspects of modern life. However, the vast amount of data they process is not always secure, posing potential risks to privacy and safety. Fully Homomorphic Encryption (FHE) enables computations on encrypted data while preserving its confidentiality, making it a promising approach for privacy-preserving AI. This study evaluates the performance of FHE when applied to DNNs and co...

Simulation Study on the Impact of Miniaturization in 3 nm Node 3D Junctionless Transistors

Junctionless Nanosheet gate-all-around Field Effect Transistor (JL-NSGAAFET) is a promising technology characterized by the absence of any junctions between source-channel-drain. This absence allows to further scale down transistors while limiting short-channel effects. In this article, JL-NSGAAFET is explored as a potential candidate for the next 3 nm technology node through 3D TCAD simulations. First, we propose and simulate, through fabrication process simulations, a fabrication strategy f...

Conductivity space isotherm behavior in quantum anomalous Hall devices

The quantum Hall effect (QHE) has enhanced accessibility to measure and disseminate electrical units, owed in part to the recently redefined International System of Units in 2019. Graphene remains one of the preferred options to realize the ohm despite the limitations of high magnetic fields to produce a robust QHE. Topological insulators, on the other hand, show promise in providing quantized resistance via the quantum anomalous Hall effect, a phenomenon that removes the need for magnetic fi...

Publication Trends in the Journal of Cardiothoracic and Vascular Anesthesia: A 10-Year Analysis