Ultra low power analog-to-information conversion by short-time compressed sensing

Il compressed sensing è un’innovativa tecnica per l’acquisizione dei dati, che mira all'estrazione del solo contenuto informativo intrinseco di un segnale. Ciò si traduce nella possibilità di acquisire informazione direttamente in forma compressa, riducendo la quantità di risorse richieste per tale operazione. In questa tesi è sviluppata un'architettura hardware per l'acquisizione di segnali analogici basata sul compressed sensing, specializzata al campionamento con consumo di potenza ridotto di segnali biomedicali a basse frequenze. Lo studio è svolto a livello di sistema mediante l'integrazione della modulazione richiesta dal compressed sensing in un convertitore analogico-digitale ad approssimazioni successive, modificandone la logica di controllo. Le prestazioni risultanti sono misurate tramite simulazioni numeriche e circuitali. Queste confermano la possibilità di ridurre la complessità hardware del sistema di acquisizione rispetto allo stato dell'arte, senza alterarne le prestazioni.

"Offshore tower or platform foundations: numerical analysis of a laterally loaded single pile or pile group in soft clay and analysis of actions on a jacket structure"

Laterally loaded piles are a typical situation for a large number of cases in which deep foundations are used. Dissertation herein reported, is a focus upon the numerical simulation of laterally loaded piles. In the first chapter the best model settings are largely discussed, so a clear idea about the effects of interface adoption, model dimension, refinement cluster and mesh coarseness is reached. At a second stage, there are three distinct parametric analyses, in which the model response sensibility is studied for variation of interface reduction factor, Eps50 and tensile cut-off. In addition, the adoption of an advanced soil model is analysed (NGI-ADP). This was done in order to use the complex behaviour (different undrained shear strengths are involved) that governs the resisting process of clay under short time static loads. Once set a definitive model, a series of analyses has been carried out with the objective of defining the resistance-deflection (P-y) curves for Plaxis3D (2013) data. Major results of a large number of comparisons made with curves from API (America Petroleum Institute) recommendation are that the empirical curves have almost the same ultimate resistance but a bigger initial stiffness. In the second part of the thesis a simplified structural preliminary design of a jacket structure has been carried out to evaluate the environmental forces that act on it and on its piles foundation. Finally, pile lateral response is studied using the empirical curves.

Design methods and geometric modelling of scaffolds for bone tissue engineering

Every year, thousand of surgical treatments are performed in order to fix up or completely substitute, where possible, organs or tissues affected by degenerative diseases. Patients with these kind of illnesses stay long times waiting for a donor that could replace, in a short time, the damaged organ or the tissue. The lack of biological alternates, related to conventional surgical treatments as autografts, allografts, e xenografts, led the researchers belonging to different areas to collaborate to find out innovative solutions. This research brought to a new discipline able to merge molecular biology, biomaterial, engineering, biomechanics and, recently, design and architecture knowledges. This discipline is named Tissue Engineering (TE) and it represents a step forward towards the substitutive or regenerative medicine. One of the major challenge of the TE is to design and develop, using a biomimetic approach, an artificial 3D anatomy scaffold, suitable for cells adhesion that are able to proliferate and differentiate themselves as consequence of the biological and biophysical stimulus offered by the specific tissue to be replaced. Nowadays, powerful instruments allow to perform analysis day by day more accurateand defined on patients that need more precise diagnosis and treatments.Starting from patient specific information provided by TC (Computed Tomography) microCT and MRI(Magnetic Resonance Imaging), an image-based approach can be performed in order to reconstruct the site to be replaced. With the aid of the recent Additive Manufacturing techniques that allow to print tridimensional objects with sub millimetric precision, it is now possible to practice an almost complete control of the parametrical characteristics of the scaffold: this is the way to achieve a correct cellular regeneration. In this work, we focalize the attention on a branch of TE known as Bone TE, whose the bone is main subject. Bone TE combines osteoconductive and morphological aspects of the scaffold, whose main properties are pore diameter, structure porosity and interconnectivity. The realization of the ideal values of these parameters represents the main goal of this work: here we'll a create simple and interactive biomimetic design process based on 3D CAD modeling and generative algorithmsthat provide a way to control the main properties and to create a structure morphologically similar to the cancellous bone. Two different typologies of scaffold will be compared: the first is based on Triply Periodic MinimalSurface (T.P.M.S.) whose basic crystalline geometries are nowadays used for Bone TE scaffolding; the second is based on using Voronoi's diagrams and they are more often used in the design of decorations and jewellery for their capacity to decompose and tasselate a volumetric space using an heterogeneous spatial distribution (often frequent in nature). In this work, we will show how to manipulate the main properties (pore diameter, structure porosity and interconnectivity) of the design TE oriented scaffolding using the implementation of generative algorithms: "bringing back the nature to the nature".

Observations and modeling of the Marginal Ice Zone

Global climate change in recent decades has strongly influenced the Arctic generating pronounced warming accompanied by significant reduction of sea ice in seasonally ice-covered seas and a dramatic increase of open water regions exposed to wind [Stephenson et al., 2011]. By strongly scattering the wave energy, thick multiyear ice prevents swell from penetrating deeply into the Arctic pack ice. However, with the recent changes affecting Arctic sea ice, waves gain more energy from the extended fetch and can therefore penetrate further into the pack ice. Arctic sea ice also appears weaker during melt season, extending the transition zone between thick multi-year ice and the open ocean. This region is called the Marginal Ice Zone (MIZ). In the Arctic, the MIZ is mainly encountered in the marginal seas, such as the Nordic Seas, the Barents Sea, the Beaufort Sea and the Labrador Sea. Formed by numerous blocks of sea ice of various diameters (floes) the MIZ, under certain conditions, allows maritime transportation stimulating dreams of industrial and touristic exploitation of these regions and possibly allowing, in the next future, a maritime connection between the Atlantic and the Pacific. With the increasing human presence in the Arctic, waves pose security and safety issues. As marginal seas are targeted for oil and gas exploitation, understanding and predicting ocean waves and their effects on sea ice become crucial for structure design and for real time safety of operations. The juxtaposition of waves and sea ice represents a risk for personnel and equipment deployed on ice, and may complicate critical operations such as platform evacuations. The risk is difficult to evaluate because there are no long-term observations of waves in ice, swell events are difficult to predict from local conditions, ice breakup can occur on very short time-scales and wave-ice interactions are beyond the scope of current forecasting models [Liu and Mollo-Christensen, 1988,Marko, 2003]. In this thesis, a newly developed Waves in Ice Model (WIM) [Williams et al., 2013a,Williams et al., 2013b] and its related Ocean and Sea Ice model (OSIM) will be used to study the MIZ and the improvements of wave modeling in ice infested waters. The following work has been conducted in collaboration with the Nansen Environmental and Remote Sensing Center and within the SWARP project which aims to extend operational services supporting human activity in the Arctic by including forecast of waves in ice-covered seas, forecast of sea-ice in the presence of waves and remote sensing of both waves and sea ice conditions. The WIM will be included in the downstream forecasting services provided by Copernicus marine environment monitoring service.

Generazione di osservabili radiometriche per navigazione deep space tramite reti neurali convoluzionali

Grazie all’evoluzione degli strumenti di calcolo e delle strutture digitali, le intelligenze artificiali si sono evolute considerevolmente negli ultimi anni, permettendone sempre nuove e complesse applicazioni. L’interesse del presente progetto di tesi è quello di creare un modello di studio preliminare di intelligenza artificiale definita come Rete Neurale Convoluzionale, o Convolutional Neural Network (CNN), al fine di essere impiegata nel campo della radioscienza e dell’esplorazione planetaria. In particolare, uno degli interessi principali di applicazione del modello è negli studi di geodesia compiuti tramite determinazione orbitale di satelliti artificiali nel loro moto attorno ai corpi celesti. Le accelerazioni causate dai campi gravitazionali planetari perturbano le orbite dei satelliti artificiali, queste variazioni vengono captate dai ricevitori radio a terra sottoforma di shift Doppler della frequenza del segnale, a partire dalla quale è quindi possibile determinare informazioni dettagliate sul campo di gravità e sulla struttura interna del corpo celeste in esame. Per poter fare ciò, occorre riuscire a determinare l’esatta frequenza del segnale in arrivo, il quale, per via di perdite e disturbi durante il suo tragitto, presenterà sempre una componente di rumore. Il metodo più comune per scindere la componente di informazione da quella di rumore e ricavarne la frequenza effettiva è l’applicazione di trasformate di Fourier a tempo breve, o Short-time Fourier Transform (STFT). Con l’attività sperimentale proposta, ci si è quindi posto l’obiettivo di istruire un CNN alla stima della frequenza di segnali reali sinusoidali rumorosi per avere un modello computazionalmente rapido e affidabile a supporto delle operazioni di pre-processing per missioni di radio-scienza.