Test platform for electronic control units of high-performance safety-critical multi actuator systems

In this paper we are mostly concerned with the problem of testing electronic control units of synchronized electric power actuators. This task is particularly complex for safety critical applications, where it is crucial that the control system properly reacts in response to the faults, that are hard to reproduce and verify. A cost-effective flexible and reconfigurable test platform is proposed, discussing its architecture and implementation. The proposed system facilitates the phase of definition and development of the electronic control unit, allowing the interfacing towards both hydraulic and electromechanical actuators, and having a high flexibility as regards the I/O signals. Some results, obtained during the laboratory test activity, are also presented

A Web Service Interface for a Distributed Measurement System Based on Decentralized Sharing Network 1

Abstract: The Web Service technology has increased in importance in these years. Accessing to remote resources without knowledge about physical implementation and with a reduced hardware requirement is the main goal of new portable device. The use of Web Service technology allows clients to create a standard interface to access to the measurement service published by the server. In low cost multipoint distributed measurement systems, the measurement services are provided by Smart Web Sensors. A new concept of distributed measurement system arises from the possibility to fuse all services with the same functionality in a single user-transparent service: the response of distributed services network to a user request gives a complete vision of the service by collecting results from any Smart Web Sensor in the network. So, in this paper the development of a multipoint distributed measurement system, based on the peer-to-peer Gnutella network with Web Service interface, is presented. Copyright © 2013 IFSA

Measurements for non-intrusive load monitoring through machine learning approaches

The topic of non-intrusive load monitoring (NILM) has seen a significant increase in research interest over the past decade, which has led to a significant increase in the performance of these systems. Nowadays, NILM systems are used in numerous applications, in particular by energy companies that provide users with an advanced management service of different consumption. These systems are mainly based on artificial intelligence algorithms that allow the disaggregation of energy by processing the absorbed power signal over more or less long time intervals (generally from fractions of an hour up to 24 h). Less attention was paid to the search for solutions that allow non-intrusive monitoring of the load in (almost) real time, that is, systems that make it possible to determine the variations in loads in extremely short times (seconds or fractions of a second). This paper proposes possible approaches for non-intrusive load monitoring systems operating in real time, analysing them from the point of view of measurement. The measurement and post-processing techniques used are illustrated and the results discussed. In addition, the work discusses the use of the results obtained to train machine learning algorithms that allow you to convert the measurement results into useful information for the user

GLAST Large Area Telescope simulation tools

This paper presents the simulation of the GLAST high energy gamma-ray telescope. The simulation package, written in C++, is based on the Geant4 toolkit, and it is integrated into a general framework used to process events. A detailed simulation of the electronic signals inside silicon detectors has been provided and it is used for the particle tracking, which is handled by a dedicated software. A unique repository for the geometrical description of the detector has been realized using the XML language and a C++ library to access this information has been designed and implemented. A new event display based on the HepRep protocol is being implemented. The GLAST satellite parameters derived from the simulation are used in a fast simulator to obtain a "snapshot" of the gamma-ray sky. This paper outlines the contribution developed by the Italian GLAST software group

EVALITA Evaluation of NLP and Speech Tools for Italian - December 17th, 2020

Welcome to EVALITA 2020! EVALITA is the evaluation campaign of Natural Language Processing and Speech Tools for Italian. EVALITA is an initiative of the Italian Association for Computational Linguistics (AILC, http://www.ai-lc.it) and it is endorsed by the Italian Association for Artificial Intelligence (AIxIA, http://www.aixia.it) and the Italian Association for Speech Sciences (AISV, http://www.aisv.it)