Search results for "Machine"
showing 10 items of 2592 documents
Survey on the innovation in the Sicilian grapevine nurseries
2012
This paper deals with quality innovation in the grapevine nursery sector. The vegetative propagation of grapevines, scarcely considered by economic research, is the first step in the wine production chain as it influences both the type and the quality of wines as well as the quality and quantity of the performance of farm investments.This paper gives the results of a study carried out through a structural analysis of both national and regional grapevine nurseries and then through a direct survey of the largest Sicilian nurseries. The survey covers the main structural and productive issues as well as the commercial aspects of eight Sicilian grapevine nurseries and their innovative investment…
Atrial Fibrosis Hampers Non-invasive Localization of Atrial Ectopic Foci From Multi-Electrode Signals: A 3D Simulation Study
2018
[EN] Introduction: Focal atrial tachycardia is commonly treated by radio frequency ablation with an acceptable long-term success. Although the location of ectopic foci tends to appear in specific hot-spots, they can be located virtually in any atrial region. Multi-electrode surface ECG systems allow acquiring dense body surface potential maps (BSPM) for non-invasive therapy planning of cardiac arrhythmia. However, the activation of the atria could be affected by fibrosis and therefore biomarkers based on BSPM need to take these effects into account. We aim to analyze the effect of fibrosis on a BSPM derived index, and its potential application to predict the location of ectopic foci in the …
Control and design for efficiency improvement of permanent-magnet synchronous motor drives in household appliances
2011
This paper deals with some aspects of efficiency improvement of PMSMD (Permanent Magnet Synchronous Motor Drives). Particularly two aspects are focused: the control algorithm for the PMSMD, which allows to reduce the power losses of the electric drive without penalty on its dynamic performances and the optimization of an IPMSM (Interior Permanent Magnet Synchronous Motor) rotor configuration capable to increase the performances in terms of shaft torque production, limiting at the same time the rotor leakage flux. The loss minimization algorithm is here briefly analyzed, a test bed for experimental validation is presented and the data are analyzed. Experimental tests have been performed aimi…
Vibrations of a continuous web on elastic supports
2017
We consider an infinite, homogenous linearly elastic beam resting on a system of linearly elastic supports, as an idealized model for a paper web in the middle of a cylinder-based dryer section. We obtain closed-form analytical expressions for the eigenfrequencies and the eigenmodes. The frequencies increase as the support rigidity is increased. Each frequency is bounded from above by the solution with absolutely rigid supports, and from below by the solution in the limit of vanishing support rigidity. Thus in a real system, the natural frequencies will be lower than predicted by commonly used models with rigid supports. peerReviewed
Regularized extreme learning machine for regression problems
2011
Extreme learning machine (ELM) is a new learning algorithm for single-hidden layer feedforward networks (SLFNs) proposed by Huang et al. [1]. Its main advantage is the lower computational cost, which is especially relevant when dealing with many patterns defined in a high-dimensional space. This paper proposes an algorithm for pruning ELM networks by using regularized regression methods, thus obtaining a suitable number of the hidden nodes in the network architecture. Beginning from an initial large number of hidden nodes, irrelevant nodes are then pruned using ridge regression, elastic net and lasso methods; hence, the architectural design of ELM network can be automated. Empirical studies…
An entropy-based machine learning algorithm for combining macroeconomic forecasts
2019
This paper applies a Machine Learning approach with the aim of providing a single aggregated prediction from a set of individual predictions. Departing from the well-known maximum-entropy inference methodology, a new factor capturing the distance between the true and the estimated aggregated predictions presents a new problem. Algorithms such as ridge, lasso or elastic net help in finding a new methodology to tackle this issue. We carry out a simulation study to evaluate the performance of such a procedure and apply it in order to forecast and measure predictive ability using a dataset of predictions on Spanish gross domestic product.
A machine learning application to predict early lung involvement in scleroderma: A feasibility evaluation
2021
Introduction: Systemic sclerosis (SSc) is a systemic immune-mediated disease, featuring fibrosis of the skin and organs, and has the greatest mortality among rheumatic diseases. The nervous system involvement has recently been demonstrated, although actual lung involvement is considered the leading cause of death in SSc and, therefore, should be diagnosed early. Pulmonary function tests are not sensitive enough to be used for screening purposes, thus they should be flanked by other clinical examinations
Experimental Validation of a Novel Method for Harmonic Mitigation for a Three-Phase Five-Level Cascaded H-Bridges Inverter
2019
In modern high-power electrical drives, the efficiency of the system is a crucial constraint. Moreover, the efficiency of power converters plays a fundamental role in modern applications requiring also a limited weight, such as the electric vehicles and novel more electric aircraft. The reduction of losses pushes for systems with a dc bus and a high number of dc/ac converters, widespread in the vehicle, not burdened by a too expensive data processing system. The purpose of this article is to concur to reduce losses by proposing an innovative selective harmonic mitigation method based on the identification of the working areas where the reference harmonics present lower amplitudes. In partic…
Design and Test of a Thermomagnetic Motor Using a Gadolinium Rotor
2013
This paper presents a Thermomagnetic Motor, whose design of the motor is based on a thermal-magnetic coupled dynamic model, which models its magnetic as well thermal properties (magnetic permeability and thermal conductivity). The thermal processes are supposed to be influenced by the thermal conductivity, the convection and the advection. An analytical expression of the generated torque, which links this quantity to the magnetic, thermal and geometrical parameters of the generated torque is given. A design of a machine, based on this theory is proposed and the related performances are numerically simulated. An experimental verification of the performances is reported.
A dq axis theory of the magnetic, thermal, and mechanical properties of Curie motor
2011
A dq axis theory of a thermomagnetic Curie motor is presented. This theory allows one to estimate the performances of a Curie motor from its geometrical, magnetic, and thermal properties. The proposed approach shows that the thermomagnetic Curie motor is equivalent from a magnetic point of view to a dc electric machine. The physical meaning of the parameters used in the dq theory of Curie motor is explicated. The theory is validated by using experimental data.