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Quantum Machine Learning for Earth Observation: Methods, Applications and Future Directions

Earth Observation (EO) plays a key role in climate monitoring, urban planning, and natural resource management, producing increasingly large and complex datasets. While traditional Artificial Intelligence techniques, particularly classical Machine Learning and Deep Learning, have significantly improved the analysis of EO data, they are beginning to encounter important limitations in terms of computational cost, scalability, and model efficiency. This doctoral thesis investigates Quantum Compu...

PROFILING, PERSONALISATION, VULNERABILITY: APPLICATION PARADIGMS. RESEARCH HYPOTHESIS THROUGH THE STUDY OF LARGE LANGUAGE MODELS

This research, starting from the dynamism that has always characterised private law, focuses on the evolution of profiling to the point of “personalisation”, especially from the perspective of vulnerable individuals, taking as its paradigm the study of Generative Artificial Intelligence, and in particular the socalled “Large Language Models”. Actually, the post-digital era is a direct consequence of the Fourth Industrial Revolution, a category that can be traced back to the study of complexit...

Advanced Photonics Assisted Theranostic Platforms For Locoregional Cancer Approaches

This thesis reports the development of an integrated theranostic platform that combines nanomedicine and advanced optical technologies to overcome the major limitations of conventional cancer treatments. Rooted in the principles of theranostics—the concurrent integration of diagnostic and therapeutic functionalities—the proposed approach aims to advance personalized medicine by enhancing therapeutic efficacy while minimizing systemic toxicity. In Chapter 1, the underlying theoretical framewor...

Raman Spectroscopy, Surface-Enhanced Raman Spectroscopy (SERS) and Tip-Enhanced Raman Spectroscopy (TERS) for advanced diagnostics

Cancer is a global health burden, highlighting the limitations of traditional diagnostic approaches, which are often invasive, subjective, and limited in their capacity for timely detection. Addressing these challenges through the development of innovative diagnostic tools that enable accurate, non-invasive and objective assessment is crucial for advancing early diagnosis, optimizing treatment strategies, and improving patient outcomes. This thesis explores the transformative potential of adv...

Process Design and Reactor Modelling for Integrated CO2 Capture and Hydrogenation via Chemical Looping

This thesis focuses on developing and numerically analyzing chemical looping technologies and integrated processes for sustainable energy conversion and storage. Chemical looping involves the cyclic reduction and oxidation of solid oxygen carriers to facilitate reactions such as combustion, gasification and methanation, with applications in low-carbon energy generation and renewable fuel production. The research presented in this thesis is organized into three main directions: (a) the develop...

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Tipologia
  • 8 Tesi12
Autore
  • CIULLO, Marianna1
  • CUTILLO, Enrico Alberto1
  • De Luca, Giuseppina1
  • ESPOSITO, Concetta1
  • FORGIONE, Annunziata1
  • MANCINO, Ilaria1
  • MARTONE, Chiara1
  • MAURO, Francesco1
  • MULE', Chiara1
  • PARROTTA, Michele1
Data di pubblicazione
  • 202612
Editore
  • Università degli Studi del Sannio...12
Settore disciplinare
  • Settore ING-IND/25 - Impianti Chi...1
  • Settore ING-INF/05 - Sistemi di E...1
  • Settore IUS/01 - Diritto Privato1
  • Settore SECS-S/06 - Metodi mat. d...1
Keyword
  • digital metasurfaces1
  • fault diagnostics1
  • machine learning1
  • multi- frequency synthesis1
  • reconfigurable intelligent surfaces1
  • space-time-coding.1
Lingua
  • eng10
  • ita3
Accesso al fulltext
  • open8
  • no fulltext4