Skin repair optimization for the airbus A350XWB cargo door surround

The aim of the thesis is to design and verify a doubler for the Airbus A350XWB cargo door surround. The software used for the design is Catia and the software used for the doubler verification are Patran and Nastran.

Machine Learning applicato al Web Semantico: Statistical Relational Learning vs Tensor Factorization

Obiettivo della tesi è analizzare e testare i principali approcci di Machine Learning applicabili in contesti semantici, partendo da algoritmi di Statistical Relational Learning, quali Relational Probability Trees, Relational Bayesian Classifiers e Relational Dependency Networks, per poi passare ad approcci basati su fattorizzazione tensori, in particolare CANDECOMP/PARAFAC, Tucker e RESCAL.