Impact of the COVID-19 pandemic on the Internet latency: A large-scale study

The COVID-19 pandemic dramatically changed the way of living of billions of people in a very short time frame. In this paper, we evaluate the impact on the Internet latency caused by the increased amount of human activities that are carried out on-line. The study focuses on Italy, which experienced significant restrictions imposed by local authorities, but results about Spain, France, Germany, Sweden, and the whole of Europe are also included. The analysis of a large set of measurements shows that the impact on the network can be significant, especially in terms of increased variability of latency. In Italy we observed that the standard deviation of the average additional delay – the additional time with respect to the minimum delay of the paths in the region – during lockdown is ∼3−4 times as much as the value before the pandemic. Similarly, in Italy, packet loss is ∼2−3 times as much as before the pandemic. The impact is not negligible also for the other countries and for the whole of Europe, but with different levels and distinct patterns

On General Plane Fronted Waves. Geodesics

A general class of Lorentzian metrics, $M_0 x R^2$, $ds^2 = + 2 du dv + H(x,u) du^2$, with $(M_0,$ any Riemannian manifold, is introduced in order to generalize classical exact plane fronted waves. Here, we start a systematic study of their main geodesic properties: geodesic completeness, geodesic connectedness and multiplicity, causal character of connecting geodesics. These results are independent of the possibility of a full integration of geodesic equations. Variational and geometrical techniques are applied systematically. In particular, we prove that the asymptotic behavior of $H(x,u)$ with $x$ at infinity determines many properties of geodesics. Essentially, a subquadratic growth of $H$ ensures geodesic completeness and connectedness, while the critical situation appears when $H(x,u)$ behaves in some direction as $|x|^2$, as in the classical model of exact gravitational wave

Performance of the readout system for MONOLITH

Abstract In this paper, we describe the performance of the readout system for MONOLITH developed at the LNGS. This system is based on the use of flat cables as readout elements, instead of the conventional copper strips. The advantages of flat cable strips are the good performance, the easy installation and the possibility to realize complex readout systems. The X -coordinate readout system (X-system) is composed by 15 m long, Flat Cable Strips (FCS). The distribution of the time difference between the streamer signals transmitted at both the ends of the X-system FCS has a sigma resolution of the order of 100 ps . This resolution allows the measurement of the particle direction by means of the time-of-flight technique and can be exploited to measure the Y -coordinate with a resolution in the order of 1 cm . The Y -coordinate system is composed by short FCS connected together by a flat cable acting as a bus line. It allows the installation of the electronics outside the apparatus minimizing the number of channels

Adaptive Path Planning for Depth Constrained Bathymetric Mapping with an Autonomous Surface Vessel

This paper describes the design, implementation and testing of a suite of algorithms to enable depth constrained autonomous bathymetric (underwater topography) mapping by an Autonomous Surface Vessel (ASV). Given a target depth and a bounding polygon, the ASV will find and follow the intersection of the bounding polygon and the depth contour as modeled online with a Gaussian Process (GP). This intersection, once mapped, will then be used as a boundary within which a path will be planned for coverage to build a map of the Bathymetry. Methods for sequential updates to GP's are described allowing online fitting, prediction and hyper-parameter optimisation on a small embedded PC. New algorithms are introduced for the partitioning of convex polygons to allow efficient path planning for coverage. These algorithms are tested both in simulation and in the field with a small twin hull differential thrust vessel built for the task.Comment: 21 pages, 9 Figures, 1 Table. Submitted to The Journal of Field Robotic

Probabilistic movement modeling for intention inference in human-robot interaction.

Intention inference can be an essential step toward efficient humanrobot interaction. For this purpose, we propose the Intention-Driven Dynamics Model (IDDM) to probabilistically model the generative process of movements that are directed by the intention. The IDDM allows to infer the intention from observed movements using Bayes ’ theorem. The IDDM simultaneously finds a latent state representation of noisy and highdimensional observations, and models the intention-driven dynamics in the latent states. As most robotics applications are subject to real-time constraints, we develop an efficient online algorithm that allows for real-time intention inference. Two human-robot interaction scenarios, i.e., target prediction for robot table tennis and action recognition for interactive humanoid robots, are used to evaluate the performance of our inference algorithm. In both intention inference tasks, the proposed algorithm achieves substantial improvements over support vector machines and Gaussian processes.

DERIVAZIONE DI IDROGRAMMI DI PIENA ATTRAVERSO L\u2019ACCOPPIAMENTO DI MODELLI STOCASTICI BIVARIATI DELLE PRECIPITAZIONI E E MODELLI AFFLUSSI - DEFLUSSI DISTRIBUTI

In questo studio viene presentata una procedura di tipo Monte Carlo per la derivazione delle curve di frequenza delle portate al colmo e dei volumi corrispondenti basata sull\u2019accoppiamento di un modello di generazione delle forzanti pluviometriche tramite copule e un modello di trasformazione afflussideflussi di tipo distribuito. Tale procedura \ue8 stata applicata ad un caso di studio siciliano; i risultati ottenuti hanno mostrato la bont\ue0 del modello a riprodurre le statistiche complesse delle grandezze idrologiche a fronte di un basso numero di parametri modellistici e di un ridotto sforzo computazionale