Distributed optimization and games over networks: a system theoretical perspective

Several decision and control tasks involve networks of cyber-physical systems that need to be coordinated and controlled according to a fully-distributed paradigm involving only local communications without any central unit. This thesis focuses on distributed optimization and games over networks from a system theoretical perspective. In the addressed frameworks, we consider agents communicating only with neighbors and running distributed algorithms with optimization-oriented goals. The distinctive feature of this thesis is to interpret these algorithms as dynamical systems and, thus, to resort to powerful system theoretical tools for both their analysis and design. We first address the so-called consensus optimization setup. In this context, we provide an original system theoretical analysis of the well-known Gradient Tracking algorithm in the general case of nonconvex objective functions. Then, inspired by this method, we provide and study a series of extensions to improve the performance and to deal with more challenging settings like, e.g., the derivative-free framework or the online one. Subsequently, we tackle the recently emerged framework named distributed aggregative optimization. For this setup, we develop and analyze novel schemes to handle (i) online instances of the problem, (ii) ``personalized'' optimization frameworks, and (iii) feedback optimization settings. Finally, we adopt a system theoretical approach to address aggregative games over networks both in the presence or absence of linear coupling constraints among the decision variables of the players. In this context, we design and inspect novel fully-distributed algorithms, based on tracking mechanisms, that outperform state-of-the-art methods in finding the Nash equilibrium of the game.

L'archeologia pubblica in Italia tra comunicazione online e offline: una proposta metodologica per la pianificazione e la misurazione

In Italia, l’archeologia pubblica ha subìto negli ultimi anni un accelerazione, grazie ad una maggiore consapevolezza da parte degli archeologi sulla necessità di un dialogo con il pubblico. Sempre più progetti di ricerca archeologica investono risorse nell’organizzazione di iniziative volte a coinvolgere la comunità, sia onsite che online. Ma per valutare effettivamente l’impatto di queste iniziative c’è bisogno di delineare una metodologia condivisa, assente attualmente in Italia: manca una progettualità, una pianificazione, una riflessione critica sull’argomento. Il mio lavoro, inserito all’interno del progetto di “Archeologia dei paesaggi di Ravenna” dell’Università di Bologna, ha l’obiettivo di individuare le strategie comunicative migliori per coinvolgere il pubblico verso tematiche storico-archeologiche, ricorrendo in particolare all’utilizzo dei social media, e di individuare una metodologia efficace per la realizzazione e valutazione delle iniziative di archeologia pubblica nell’ambito della ricerca universitaria. Essendoci la necessità di una pianificazione, ho deciso di considerare il mio progetto come se fosse un’azienda con un prodotto o servizio da portare sul mercato. In tal caso, l’azienda deve ricorrere alla stesura di un piano marketing, un documento che formalizza le analisi e le conseguenti decisioni di marketing per un determinato prodotto/mercato, in un determinato arco temporale/spaziale al fine di conseguire gli obiettivi prefissati.

Carbapenemase producing enterobacteriacae rectal colonization in dialysis patients: a large monocentric retrospective analysis

Carbapenemase-producing Enterobacteriaceae (CPE) represent a growing global public health concern due to their increasing prevalence and resistance to carbapenems, a group of last-resort antibiotics. Dialysis patients, who often have compromised immune systems, are particularly vulnerable to infections that represent the second cause of death in dialysis’ cohorts. Presenting a rectal colonization by CPE has a significative impact on patients in dialysis? Are there factors that can help us understand which patients are at a higher risk of developing CPE colonization? How can we treat a CPE colonized patient who develop fever? Our study aim to reviews the challenges posed by CPE in dialysis settings and explores current diagnostic, therapeutic, and infection control strategies on a large cohort of dialyzed patients.

Machine Learning algorithm on seat comfort level measurement, mapping pressure values with body regions

The comfort level of the seat has a major effect on the usage of a vehicle; thus, car manufacturers have been working on elevating car seat comfort as much as possible. However, still, the testing and evaluation of comfort are done using exhaustive trial and error testing and evaluation of data. In this thesis, we resort to machine learning and Artificial Neural Networks (ANN) to develop a fully automated approach. Even though this approach has its advantages in minimizing time and using a large set of data, it takes away the degree of freedom of the engineer on making decisions. The focus of this study is on filling the gap in a two-step comfort level evaluation which used pressure mapping with body regions to evaluate the average pressure supported by specific body parts and the Self-Assessment Exam (SAE) questions on evaluation of the person’s interest. This study has created a machine learning algorithm that works on giving a degree of freedom to the engineer in making a decision when mapping pressure values with body regions using ANN. The mapping is done with 92% accuracy and with the help of a Graphical User Interface (GUI) that facilitates the process during the testing time of comfort level evaluation of the car seat, which decreases the duration of the test analysis from days to hours.