Evaluation of slope stability under water and seismic load through the Minimum Lithostatic Deviation method

The main objective of this thesis is to obtain a better understanding of the methods to assess the stability of a slope. We have illustrated the principal variants of the Limit Equilibrium (LE) method found in literature, focalizing our attention on the Minimum Lithostatic Deviation (MLD) method, developed by Prof. Tinti and his collaborators (e.g. Tinti and Manucci, 2006, 2008). We had two main goals: the first was to test the MLD method on some real cases. We have selected the case of the Vajont landslide with the objective to reconstruct the conditions that caused the destabilization of Mount Toc, and two sites in the Norwegian margin, where failures has not occurred recently, with the aim to evaluate the present stability state and to assess under which conditions they might be mobilized. The second goal was to study the stability charts by Taylor and by Michalowski, and to use the MLD method to investigate the correctness and adequacy of this engineering tool.

Matrix Designs and Methods for Secure and Efficient Compressed Sensing

The idea of balancing the resources spent in the acquisition and encoding of natural signals strictly to their intrinsic information content has interested nearly a decade of research under the name of compressed sensing. In this doctoral dissertation we develop some extensions and improvements upon this technique's foundations, by modifying the random sensing matrices on which the signals of interest are projected to achieve different objectives. Firstly, we propose two methods for the adaptation of sensing matrix ensembles to the second-order moments of natural signals. These techniques leverage the maximisation of different proxies for the quantity of information acquired by compressed sensing, and are efficiently applied in the encoding of electrocardiographic tracks with minimum-complexity digital hardware. Secondly, we focus on the possibility of using compressed sensing as a method to provide a partial, yet cryptanalysis-resistant form of encryption; in this context, we show how a random matrix generation strategy with a controlled amount of perturbations can be used to distinguish between multiple user classes with different quality of access to the encrypted information content. Finally, we explore the application of compressed sensing in the design of a multispectral imager, by implementing an optical scheme that entails a coded aperture array and Fabry-Pérot spectral filters. The signal recoveries obtained by processing real-world measurements show promising results, that leave room for an improvement of the sensing matrix calibration problem in the devised imager.