Jovani Dalzochio

TL;DR: It is pointed out that predictive maintenance is a hot topic in the context of Industry 4.0 but with several challenges to be better investigated in the area of machine learning and the application of reasoning.

TL;DR: In this paper, the authors assess the association between staying at home and the reduction/increase in the number of deaths due to COVID-19 in several regions in the world.

TL;DR: The results were not able to explain if COVID-19 mortality is reduced by staying as home in ~98% of the comparisons after epidemiological weeks 9 to 34, and the novel approach to assess the association between staying at home values and the reduction/increase in the number of deaths in several regions around the world.

TL;DR: In this paper , the authors propose a framework called ELFpm, designed to predict equipment failures, regardless of location or condition of use, and propose a novel suitability index that selects the appropriate prediction algorithm considering the current status of the equipment.

TL;DR: In this paper , the challenges, principles, scenarios, techniques, and open questions of predictive maintenance (PdM) in the military domain are identified, along with the identification of 23 challenges and principles, 4 scenarios where predictive maintenance is crucial, besides discussing techniques used for PdM in the defense domain.