Coronavirus variant COVID-19 pandemic: a report to seafarers

We report the current situation regarding the COVID-19 pandemic with particular regard to seafarers and with the indications drawn up by the Centro Internazionale Radio Medico (C.I.R.M.) in this regard

Coronavirus variant COVID-19 pandemic: a report to seafarers.

We report the current situation regarding the COVID-19 pandemic with particular regard to seafarers and with the indications drawn up by the Centro Internazionale Radio Medico (C.I.R.M.) in this regard

Chiedere asilo da lontano

La drammatica crisi afgana dell’agosto 2021 ha reso più evidente la necessità di un sistema del diritto all’asilo che consenta alle persone bisognose di protezione di essere effettivamente accolte senza affrontare il rischio di un viaggio che mette a repentaglio le loro stesse esistenze, ed il pericolo della disumana detenzione nel paesi di transito, in forza del preventivo riconoscimento del loro status prima dell’arrivo nel nostro Paese

Fusion of symbolic knowledge and uncertain information in robotics

The interpretation of data coming from the real world may require different and often complementary uncertainty models: some are better described by possibility theory, others are intrinsically probabilistic. A logic for belief functions is introduced to axiomatize both semantics as special cases. As it properly extends classical logic, it also allows the fusion of data with different semantics and symbolic knowledge. The approach has been applied to the problem of mobile robot localization. For each place in the environment, a set of logical propositions allows the system to calculate the belief of the robot’s presence as a function of the partial evidences provided by the individual sensors.

Abstract Sequent calculus and data fusion

We present a formal method for data fusion, based on possibilistic logic. The method has been applied to a real-world problem of noisy sensor-data fusion: the position estimation of an autonomous mobile robot navigating in an approximately and partially known office environment using a topological map. Each place in the map is characterized by a set of logical formulae axiomatizing both symbolic knowledge and uncertain information from the sensors. At each time instant during navigation, the necessity for each place is calculated using a function generated by a proof system based on sequent calculus. Several test runs using a real robot have shown the adequacy of the approach in interpreting and disambiguating the information coming from independent perceptual sources, in combination with symbolic knowledge