Induction Motor Diagnosis in Variable Speed Drives

Several diagnostic techniques are presented for the detection of electrical fault in induction motor variable speed drives. These techinques are developed taking into account the impact of the control system on machine variables and non stationary operating conditions.

A bayesian model for mixed responses and skew laten variable to measure HRQoL in children

The aim of the thesi is to formulate a suitable Item Response Theory (IRT) based model to measure HRQoL (as latent variable) using a mixed responses questionnaire and relaxing the hypothesis of normal distributed latent variable. The new model is a combination of two models already presented in literature, that is, a latent trait model for mixed responses and an IRT model for Skew Normal latent variable. It is developed in a Bayesian framework, a Markov chain Monte Carlo procedure is used to generate samples of the posterior distribution of the parameters of interest. The proposed model is test on a questionnaire composed by 5 discrete items and one continuous to measure HRQoL in children, the EQ-5D-Y questionnaire. A large sample of children collected in the schools was used. In comparison with a model for only discrete responses and a model for mixed responses and normal latent variable, the new model has better performances, in term of deviance information criterion (DIC), chain convergences times and precision of the estimates.

Pulsating variable stars as tracers of galactic structure and interaction mechanisms

My PhD project has been focused on the study of the pulsating variable stars in two ultra-faint dwarf spheroidal satellites of the Milky Way, namely, Leo IV and Hercules; and in two fields of the Large Magellanic Cloud (namely, the Gaia South Ecliptic Pole calibration field, and the 30 Doradus region) that were repeatedly observed in the KS band by the VISTA Magellanic Cloud (VMC, PI M.R. Cioni) survey of the Magellanic System.