Ricerc@Sapienza

Due to the increasing amount of sensors and data streams that can be collected in order to monitor electric distribution networks, developing predictive diagnostic systems over Smart Grids demands powerful and scalable algorithms in order to search for regularities in Big Data. In this regards, Evolutive Agent Based Clustering (E-ABC) is a promising framing reference, as it is conceived to orchestrate a swarm of intelligent agents acting as individuals of an evolving population, each performing a random walk on a different subset of patterns.

We propose a deep architecture for the classification of mul-tivariate time series. By means of a recurrent and untrained reservoir we generate a vectorial representation that embeds temporal relationships in the data. To improve the memorization capability, we implement a bidirectional reservoir, whose last state captures also past dependencies in the input. We apply dimensionality reduction to the final reservoir states to obtain compressed fixed size representations of the time series.

Earth Observation (EO) data are used to map mostly affected urban areas after an earthquake generally exploiting change detection techniques applied at pixel scale. However, Civil Protection Services require damage assessment of each building according to a well-established scale to manage rescue operations and to estimate the economic losses.

Human skeletal muscles may undergo qualitative and quantitative, physiological and pathological changes during life. Some of these changes may be detected with imaging techniques, others with immunohystochemical and molecular analysis. Both these types of investigation are expensive, time consuming, and not readily available. Therefore, at present, a cheap, reliable, and widely applicable technique for non-invasive in vivo analysis of human muscles is lacking.

Optical spectroscopy is a powerful tool in research and industrial applications. Its properties of being rapid, non-invasive
and not destructive make it a promising technique for qualitative as well as quantitative analysis in medicine. Recent
advances in materials and fabrication techniques provided portable, performant, sensing spectrometers readily operated
by user-friendly cabled or wireless systems. We used such a system to test whether infrared spectroscopy techniques,

Asbestos recognition, inside different matrices (i.e. Asbestos Containing Materials: ACMs), is of great importance both "in situ" and in the further analysis at lab scale. Among the industrial sectors utilizing asbestos, the building and construction sector is the most important, especially with reference to all the constructions built before the '90s. The large utilization of asbestos is mainly linked to its technical properties (i.e. resistance to abrasion, heat and chemicals).

Abstract
OBJECTIVES:
This study is aimed at identifying discrete severity classes among adults with hypermobile Ehlers-Danlos syndrome (hEDS)/hypermobility spectrum disorders (HSD).
METHODS:

This paper presents the experience of survey and classification of about one hundred traditional masonry buildings in Central Italy, strucked by the earthquake in 2016. This territory, since several decades, presents high fragility featured due to the depopulation process that increase the vulnerability and risk degree. This condition affects even the maintenance practices of traditional buildings by the inhabitants and the extraordinary post-traumatic situation acts as an accelerating factor of the abandonment.