Building Partial Discharge Signal Wireless Probes

This chapter focuses on the evaluation of the performances of different antenna sensors suitable for Partial Discharge (PD) measurements. Monopole, triangular and spherical antennas were simulated by means of the surface method of moments. The transmitting system is modeled by a power electronic device with a fault current between two metal plates. The shape of the simulated, transmitted and received signals, has been compared to verify the sensor that provides the best fidelity among the three. The auto-correlation function and the Pearson correlation index are adopted here for the comparison. A discussion on the dynamic characteristic of the different antenna probes and their use in different application is proposed

PyGNA:A unified framework for geneset network analysis

Input data and results for the manuscript "PyGNA: a unified framework for geneset network analysis". Manifest files describe the content of each file.This work has been supported by the Wellcome Trust Seed Award in Science (207769/A/17/Z) to G.S

High Frequency Model of PV Systems for the Evaluation of Ground Currents

A high frequency model of a photovoltaic (PV) plant is developed and analysed to investigate the common mode (CM) currents circulating through the ground connections of the plant. The modelling method is based on the measurement of the impedance frequency response of photovoltaic module and on a high frequency representation of the power conversion unit. An overall lumped parameters circuit model is obtained and then implemented in PSpice. The CM leakage currents are evaluated by simulation

Generative Temporal Models with Spatial Memory for Partially Observed Environments

In model-based reinforcement learning, generative and temporal models of environments can be leveraged to boost agent performance, either by tuning the agent's representations during training or via use as part of an explicit planning mechanism. However, their application in practice has been limited to simplistic environments, due to the difficulty of training such models in larger, potentially partially-observed and 3D environments. In this work we introduce a novel action-conditioned generative model of such challenging environments. The model features a non-parametric spatial memory system in which we store learned, disentangled representations of the environment. Low-dimensional spatial updates are computed using a state-space model that makes use of knowledge on the prior dynamics of the moving agent, and high-dimensional visual observations are modelled with a Variational Auto-Encoder. The result is a scalable architecture capable of performing coherent predictions over hundreds of time steps across a range of partially observed 2D and 3D environments.Comment: ICML 201

Performances of rainfall energy harvester

In this paper the performances of rainfall energy harvesting by means of piezoelectric transducers is presented. Diverse studies agree on the level of suitable generated voltage on the electrodes of a piezoelectric transducer subjected to rainfall, but a complete characterization on the supplied power is still missing. This work, in order to limit optimistic forecasts, takes into account the behavior of the transducers subjected to real and also artificial rainfall, condition that has shown promising behavior in laboratory. In order to increase the energy harvesting and also define its limits different loads have been taken into account. Only commercial transducers have been considered: a lead zirconate titanate and polyvinylidene difluoride transducer