Microwave breast imaging reconstruction

In this thesis I analyzed the microwave tomography method to recognize breast can- cer. I study how identify the dielectric permittivity, the Helmoltz equation parameter used to model the real physic problem. Through a non linear least squares method I solve a problem of parameters identification; I show the theoric approach and the devel- opment to reach the results. I use the Levenberg-Marquardt algorithm, applied on COMSOL software to multiphysic models; so I do numerical proofs on semplified test problems compared to the specific real problem to solve.

Spectroscopic analysis of terrestrial analogues for the interpretation of surface composition of rocky bodies in the solar system. Effects of mineral mixing and particle size. Applications to moon, mars and implications for mercury.

Among the Solar System’s bodies, Moon, Mercury and Mars are at present, or have been in the recent years, object of space missions aimed, among other topics, also at improving our knowledge about surface composition. Between the techniques to detect planet’s mineralogical composition, both from remote and close range platforms, visible and near-infrared reflectance (VNIR) spectroscopy is a powerful tool, because crystal field absorption bands are related to particular transitional metals in well-defined crystal structures, e.g., Fe2+ in M1 and M2 sites of olivine or pyroxene (Burns, 1993). Thanks to the improvements in the spectrometers onboard the recent missions, a more detailed interpretation of the planetary surfaces can now be delineated. However, quantitative interpretation of planetary surface mineralogy could not always be a simple task. In fact, several factors such as the mineral chemistry, the presence of different minerals that absorb in a narrow spectral range, the regolith with a variable particle size range, the space weathering, the atmosphere composition etc., act in unpredictable ways on the reflectance spectra on a planetary surface (Serventi et al., 2014). One method for the interpretation of reflectance spectra of unknown materials involves the study of a number of spectra acquired in the laboratory under different conditions, such as different mineral abundances or different particle sizes, in order to derive empirical trends. This is the methodology that has been followed in this PhD thesis: the single factors previously listed have been analyzed, creating, in the laboratory, a set of terrestrial analogues with well-defined composition and size. The aim of this work is to provide new tools and criteria to improve the knowledge of the composition of planetary surfaces. In particular, mixtures composed with different content and chemistry of plagioclase and mafic minerals have been spectroscopically analyzed at different particle sizes and with different mineral relative percentages. The reflectance spectra of each mixture have been analyzed both qualitatively (using the software ORIGIN®) and quantitatively applying the Modified Gaussian Model (MGM, Sunshine et al., 1990) algorithm. In particular, the spectral parameter variations of each absorption band have been evaluated versus the volumetric FeO% content in the PL phase and versus the PL modal abundance. This delineated calibration curves of composition vs. spectral parameters and allow implementation of spectral libraries. Furthermore, the trends derived from terrestrial analogues here analyzed and from analogues in the literature have been applied for the interpretation of hyperspectral images of both plagioclase-rich (Moon) and plagioclase-poor (Mars) bodies.

Evaluating the urban heat island for cities of Emilia-Romagna region through numerical simulations

Lo scopo di questo studio è la comprensione della dinamica dello strato limite urbano per città dell’Emilia Romagna tramite simulazioni numeriche. In particolare, l’attenzione è posta sull’ effetto isola di calore, ovvero sulla differenza di temperatura dell’aria in prossimità del suolo fra zone rurali e urbane dovuta all’urbanizzazione. Le simulazioni sono state effettuate con il modello alla mesoscala "Weather Research and Forecasting" (WRF), accoppiato con le parametrizzazioni urbane "Building Effect Parametrization" (BEP) e "Building Energy Model" (BEM), che agiscono a vari livelli verticali urbani. Il periodo di studio riguarda sei giorni caldi e senza copertura nuvolosa durante un periodo di heat wave dell’anno 2015. La copertura urbana è stata definita con il "World Urban Databes and Access Portal Tools" (WUDAPT), un metodo che permette di classificare le aree urbane in dieci "urban climate zones" (UCZ), attraverso l’uso combinato di immagini satellitari e "training areas" manualmente definite con il software Google Earth. Sono state svolte diverse simulazioni a domini innestati, con risoluzione per il dominio più piccolo di 500 m, centrato sulla città di Bologna. Le differenze fra le simulazioni riguardano la presenza o l’assenza delle strutture urbane, il metodo di innesto e tipo di vegetazione rurale. Inoltre, è stato valutato l’effetto dovuto alla presenza di pannelli fotovoltaici sopra i tetti di ogni edificio e le variazioni che i pannelli esercitano sullo strato limite urbano. Per verificare la bontà del modello, i dati provenienti dalle simulazioni sono stati confrontati con misure provenienti da 41 stazioni all’interno dell’area di studio. Le variabili confrontate sono: temperatura, umidità relativa, velocità e direzione del vento. Le simulazioni sono in accordo con i dati osservativi e riescono a riprodurre l’effetto isola di calore: la differenza di temperatura fra città e zone rurali circostanti è nulla durante il giorno; al contrario, durante la notte l’isola di calore è presente, e in media raggiunge il massimo valore di 4°C alle 1:00. La presenza dei pannelli fotovoltaici abbassa la temperatura a 2 metri dell’aria al massimo di 0.8°C durante la notte, e l’altezza dello strato limite urbano dell’ordine 200mrispetto al caso senza pannelli. I risultati mostrano come l’uso di pannelli fotovoltaici all’interno del contesto urbano ha molteplici benefici: infatti, i pannelli fotovoltaici riescono a ridurre la temperatura durante un periodo di heat wave, e allo stesso tempo possono parzialmente sopperire all’alto consumo energetico, con una conseguente riduzione del consumo di combustibili fossili.

Tensor-Train decomposition for image classification problems

In these last years a great effort has been put in the development of new techniques for automatic object classification, also due to the consequences in many applications such as medical imaging or driverless cars. To this end, several mathematical models have been developed from logistic regression to neural networks. A crucial aspect of these so called classification algorithms is the use of algebraic tools to represent and approximate the input data. In this thesis, we examine two different models for image classification based on a particular tensor decomposition named Tensor-Train (TT) decomposition. The use of tensor approaches preserves the multidimensional structure of the data and the neighboring relations among pixels. Furthermore the Tensor-Train, differently from other tensor decompositions, does not suffer from the curse of dimensionality making it an extremely powerful strategy when dealing with high-dimensional data. It also allows data compression when combined with truncation strategies that reduce memory requirements without spoiling classification performance. The first model we propose is based on a direct decomposition of the database by means of the TT decomposition to find basis vectors used to classify a new object. The second model is a tensor dictionary learning model, based on the TT decomposition where the terms of the decomposition are estimated using a proximal alternating linearized minimization algorithm with a spectral stepsize.

A Multilevel Gradient Method for Optimization Problems

I problemi di ottimizzazione di dimensione finita di larga scala spesso derivano dalla discretizzazione di problemi di dimensione infinita. È perciò possibile descrivere il problema di ottimizzazione su più livelli discreti. Lavorando su un livello più basso di quello del problema considerato, si possono calcolare soluzioni approssimate che saranno poi punti di partenza per il problema di ottimizzazione al livello più fine. I metodi multilivello, già ampiamente presenti in letteratura a partire dagli anni Novanta, sfruttano tale caratteristica dei problemi di ottimizzazione per migliorare le prestazioni dei metodi di ottimizzazione standard. L’obiettivo di questa tesi è quello di implementare una variante multilivello del metodo del gradiente (MGM) e di testarlo su due diversi campi: la risoluzione delle Equazioni alle Derivate Parziali la ricostruzione di immagini. In questo elaborato viene illustrata la teoria dello schema multilivello e presentato l’algoritmo di MGM utilizzato nei nostri esperimenti. Sono poi discusse le modalità di utilizzo di MGM per i due problemi sopra presentati. Per il problema PDE, i risultati ottenuti mostrano un ottimo comportamento di MGM rispetto alla implementazione classica ad un livello. I risultati ottenuti per il problema di ricostruzione di immagini, al contrario delle PDEs, evidenziano come MGM sia efficace solo in determinate condizioni.

A nearly optimum linear-phase digital FIR filters design

A new simple method to design linear-phase finite impulse response (FIR) digital filters, based on the steepest-descent optimization method, is presented in this paper. Starting from the specifications of the desired frequency response and a maximum approximation error a nearly optimum digital filter is obtained. Tests have shown that this method is alternative to other traditional ones such as Frequency Sampling and Parks-McClellan, mainly when other than brick wall frequency response is required as a desired frequency response. (C) 2011 Elsevier Inc. All rights reserved.

Constraint reasoning with local search for continuous optimization

Optimization is a very important field for getting the best possible value for the optimization function. Continuous optimization is optimization over real intervals. There are many global and local search techniques. Global search techniques try to get the global optima of the optimization problem. However, local search techniques are used more since they try to find a local minimal solution within an area of the search space. In Continuous Constraint Satisfaction Problems (CCSP)s, constraints are viewed as relations between variables, and the computations are supported by interval analysis. The continuous constraint programming framework provides branch-and-prune algorithms for covering sets of solutions for the constraints with sets of interval boxes which are the Cartesian product of intervals. These algorithms begin with an initial crude cover of the feasible space (the Cartesian product of the initial variable domains) which is recursively refined by interleaving pruning and branching steps until a stopping criterion is satisfied. In this work, we try to find a convenient way to use the advantages in CCSP branchand- prune with local search of global optimization applied locally over each pruned branch of the CCSP. We apply local search techniques of continuous optimization over the pruned boxes outputted by the CCSP techniques. We mainly use steepest descent technique with different characteristics such as penalty calculation and step length. We implement two main different local search algorithms. We use “Procure”, which is a constraint reasoning and global optimization framework, to implement our techniques, then we produce and introduce our results over a set of benchmarks.

A Gradient based algorithm for blind inversion of Wiener System using multi-variate score functions

A Wiener system is a linear time-invariant filter, followed by an invertible nonlinear distortion. Assuming that the input signal is an independent and identically distributed (iid) sequence, we propose an algorithm for estimating the input signal only by observing the output of the Wiener system. The algorithm is based on minimizing the mutual information of the output samples, by means of a steepest descent gradient approach.

Learning Robot Environment through Simulation

Traditionally simulators have been used extensively in robotics to develop robotic systems without the need to build expensive hardware. However, simulators can be also be used as a “memory”for a robot. This allows the robot to try out actions in simulation before executing them for real. The key obstacle to this approach is an uncertainty of knowledge about the environment. The goal of the Master’s Thesis work was to develop a method, which allows updating the simulation model based on actual measurements to achieve a success of the planned task. OpenRAVE was chosen as an experimental simulation environment on planning,trial and update stages. Steepest Descent algorithm in conjunction with Golden Section search procedure form the principle part of optimization process. During experiments, the properties of the proposed method, such as sensitivity to different parameters, including gradient and error function, were examined. The limitations of the approach were established, based on analyzing the regions of convergence.

Assignment on Matlab

Considers systems of linear equations, steepest ascent optimisation and Monte Carlo simulation.

Solving surface structures from normal incidence X-ray standing wave data

A program is provided to determine structural parameters of atoms in or adsorbed on surfaces by refinement of atomistic models towards experimentally determined data generated by the normal incidence X-ray standing wave (NIXSW) technique. The method employs a combination of Differential Evolution Genetic Algorithms and Steepest Descent Line Minimisations to provide a fast, reliable and user friendly tool for experimentalists to interpret complex multidimensional NIXSW data sets.

A uniformly valid far field asymptotic expansion of the green function for two-dimensional propagation above a homogeneous impedance plane

A generalized asymptotic expansion in the far field for the problem of cylindrical wave reflection at a homogeneous impedance plane is derived. The expansion is shown to be uniformly valid over all angles of incidence and values of surface impedance, including the limiting cases of zero and infinite impedance. The technique used is a rigorous application of the modified steepest descent method of Ot

Una biografia per immagini

Life and work of screen-writer Enrico Medioli (b. 1925), following the criteria of Dizionario Biografico degli Italiani (by Istituto Enciclopedia Italiana), tht is the top of Italian tools (I wrote several items for it).

Partial spectral projected gradient method with active-set strategy for linearly constrained optimization

A method for linearly constrained optimization which modifies and generalizes recent box-constraint optimization algorithms is introduced. The new algorithm is based on a relaxed form of Spectral Projected Gradient iterations. Intercalated with these projected steps, internal iterations restricted to faces of the polytope are performed, which enhance the efficiency of the algorithm. Convergence proofs are given and numerical experiments are included and commented. Software supporting this paper is available through the Tango Project web page: http://www.ime.usp.br/similar to egbirgin/tango/.

CASPT2 Study of the Potential Energy Surface of the HSO(2) System

The importance of the HSO(2) system in atmospheric and combustion chemistry has motivated several works dedicated to the study of associated structures and chemical reactions. Nevertheless controversy still exists in connection with the reaction SH + O(2) -> H + SO(2) and also related to the role of the HSOO isomers in the potential energy surface (PES). Here we report high-level ab initio calculation for the electronic ground state of the HSO(2) system. Energetic, geometric, and frequency properties for the major stationary states of the PES are reported at the same level of calculations:,CASPT2/aug-cc-pV(T+d)Z. This study introduces three new stationary points (two saddle points and one minimum). These structures allow the connection of the skewed HSOOs and the HSO(2) minima defining new reaction paths for SH + O(2) -> H + SO(2) and SH + O(2) -> OH + SO. In addition, the location of the HSOO isomers in the reaction pathways have been clarified.