Integrated communication and learning towards autonomous mobile radio networks

The integration of distributed and ubiquitous intelligence has emerged over the last years as the mainspring of transformative advancements in mobile radio networks. As we approach the era of “mobile for intelligence”, next-generation wireless networks are poised to undergo significant and profound changes. Notably, the overarching challenge that lies ahead is the development and implementation of integrated communication and learning mechanisms that will enable the realization of autonomous mobile radio networks. The ultimate pursuit of eliminating human-in-the-loop constitutes an ambitious challenge, necessitating a meticulous delineation of the fundamental characteristics that artificial intelligence (AI) should possess to effectively achieve this objective. This challenge represents a paradigm shift in the design, deployment, and operation of wireless networks, where conventional, static configurations give way to dynamic, adaptive, and AI-native systems capable of self-optimization, self-sustainment, and learning. This thesis aims to provide a comprehensive exploration of the fundamental principles and practical approaches required to create autonomous mobile radio networks that seamlessly integrate communication and learning components. The first chapter of this thesis introduces the notion of Predictive Quality of Service (PQoS) and adaptive optimization and expands upon the challenge to achieve adaptable, reliable, and robust network performance in dynamic and ever-changing environments. The subsequent chapter delves into the revolutionary role of generative AI in shaping next-generation autonomous networks. This chapter emphasizes achieving trustworthy uncertainty-aware generation processes with the use of approximate Bayesian methods and aims to show how generative AI can improve generalization while reducing data communication costs. Finally, the thesis embarks on the topic of distributed learning over wireless networks. Distributed learning and its declinations, including multi-agent reinforcement learning systems and federated learning, have the potential to meet the scalability demands of modern data-driven applications, enabling efficient and collaborative model training across dynamic scenarios while ensuring data privacy and reducing communication overhead.

Cosmology from probe combination: synergies between the number counts of galaxy clusters and cosmic voids

This Thesis work concerns the complementary study of the abundance of galaxy clusters and cosmic voids identified in cosmological simulations, at different redshifts. In particular, we focus our analyses on the combination of the cosmological constraints derived from these probes, which can be considered statistically independent, given the different aspects of Universe density field they map. Indeed, we aim at showing the orthogonality of the derived cosmological constraints and the resulting impressive power of the combination of these probes. To perform this combination we apply three newly implemented algorithms that allow us to combine independent probes. These algorithms represent a flexible and user-friendly tool to perform different techniques for probe combination and are implemented within the environment provided by the large set of free software C++/Python CosmoBolognaLib. All the new implemented codes provide simple and flexible tools that will be soon applied to the data coming from currently available and next-generation wide-field surveys to perform powerful combined cosmological analyses.

Neutrino interactions in the SAND LAr volume at the DUNE Near Detector site

The neutrino mass ordering and the leptonic CP violation phase are key parameters of the three-neutrino flavour mixing still to be determined. Measuring these parameters is the main goal of DUNE, a next generation Long Baseline neutrino experiment under construction in the United States. DUNE will feature a Near and a Far Detector site. An important component of the Near detector complex is the SAND apparatus, which will include GRAIN, a novel liquid Argon detector that aims at imaging neutrino interactions using scintillation light. For this purpose, an innovative optical readout system based on Coded Aperture Masks is under study. This thesis work is aimed at a first quantitative assessment of a 3D neutrino event reconstruction algorithm for GRAIN. The processing procedure is optimized and the reconstruction performance is evaluated. Promising results are obtained.

Integration Of Parking Assist Module with Body Computer Module.

This dissertation is focussed on integration of a Parking assist module ECU inside a Body computer Module. This project is aligned with the development of current electrical architecture into the next generation Lumped electrical architecture.

Fermion masses, leptogenesis and gravitational waves in SO(10)

Grand Unification Theories (GUTs) predict the unification of three of the fundamental forces and are a possible extension of the Standard Model, some of them predict neutrino mass and baryon asymmetry. We consider a minimal non-supersymmetric $SO(10)$ GUT model that can reproduce the observed fermionic masses and mixing parameters of the Standard Model. We calculate the scales of spontaneous symmetry breaking from the GUT to the Standard Model gauge group using two-loop renormalisation group equations. This procedure determines the proton decay rate and the scale of $U(1)_{B-L}$ breaking, which generates cosmic strings, and the right-handed neutrino mass scales. Consequently, the regions of parameter space where thermal leptogenesis is viable are identified and correlated with the fermion masses and mixing, the neutrinoless double beta decay rate, the proton decay rate, and the gravitational wave signal resulting from the network of cosmic strings. We demonstrate that this framework, which can explain the Standard Model fermion masses and mixing and the observed baryon asymmetry, will be highly constrained by the next generation of gravitational wave detectors and neutrino oscillation experiments which will also constrain the proton lifetime

Generation and Characterization of Knockout Mice and Analysis of Patient Material Demonstrates a Role for Tissue Inhibitor of Metalloproteinases 4 (Timp4) in the Cardiovascular System and Tumor Metastasis

This thesis focuses on tissue inhibitor of metalloproteinases 4 (TIMP4) which is the newest member of a small gene and protein family of four closely related endogenous inhibitors of extracellular matrix (ECM) degrading enzymes. Existing data on TIMP4 suggested that it exhibits a more restricted expression pattern than the other TIMPs with high expression levels in heart, brain, ovary and skeletal muscle. These observations and the fact that the ECM is of special importance to provide the cardiovascular system with structural strength combined with elasticity and distensibility, prompted the present molecular biologic investigation on TIMP4. In the first part of the study the murine Timp4 gene was cloned and characterized in detail. The structure of murine Timp4 genomic locus resembles that in other species and of the other Timps. The highest Timp4 expression was detected in heart, ovary and brain. As the expression pattern of Timp4 gives only limited information about its role in physiology and pathology, Timp4 knockout mice were generated next. The analysis of Timp4 knockout mice revealed that Timp4 deficiency has no obvious effect on the development, growth or fertility of mice. Therefore, Timp4 deficient mice were challenged using available cardiovascular models, i.e. experimental cardiac pressure overload and myocardial infarction. In the former model, Timp4 deficiency was found to be compensated by Timp2 overexpression, whereas in the myocardial infarct model, Timp4 deficiency resulted in increased mortality due to increased susceptibility for cardiac rupture. In the wound healing model, Timp4 deficiency was shown to result in transient retardation of re-epithelialization of cutaneous wounds. Melanoma tumor growth was similar in Timp4 deficient and control mice. Despite of this, lung metastasis of melanoma cells was significantly increased in Timp4 null mice. In an attempt to translate the current findings to patient material, TIMP4 expression was studied in human specimens representing different inflammatory cardiovascular pathologies, i.e. giant cell arteritis, atherosclerotic coronary arteries and heart allografts exhibiting signs of chronic rejection. The results showed that cardiovascular expression of TIMP4 is elevated particularly in areas exhibiting inflammation. The results of the present studies suggest that TIMP4 has a special role in the regulation of tissue repair processes in the heart, and also in healing wounds and metastases. Furthermore, evidence is provided suggesting the usefulness of TIMP4 as a novel systemic marker for vascular inflammation.

Matrix based Key Generation to Enhance Key Avalanche in Advanced Encryption Standard

In symmetric block ciphers, substitution and diffusion operations are performed in multiple rounds using sub-keys generated from a key generation procedure called key schedule. The key schedule plays a very important role in deciding the security of block ciphers. In this paper we propose a complex key generation procedure, based on matrix manipulations, which could be introduced in symmetric ciphers. The proposed key generation procedure offers two advantages. First, the procedure is simple to implement and has complexity in determining the sub-keys through crypt analysis. Secondly, the procedure produces a strong avalanche effect making many bits in the output block of a cipher to undergo changes with one bit change in the secret key. As a case study, matrix based key generation procedure has been introduced in Advanced Encryption Standard (AES) by replacing the existing key schedule of AES. The key avalanche and differential key propagation produced in AES have been observed. The paper describes the matrix based key generation procedure and the enhanced key avalanche and differential key propagation produced in AES. It has been shown that, the key avalanche effect and differential key propagation characteristics of AES have improved by replacing the AES key schedule with the Matrix based key generation procedure