4 Contributo in Atti di Convegno (Proceeding)

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A Training to Relieve Work-Related Technostress: The Project “Tutela 2”

Technostress, or the inability to deal with information technology (IT) healthily, may have a detrimental impact on employees’ quality of life. The present study had the objective to develop training to facilitate the management of work-related technostress. A sample of 236 voluntary bank employees underwent an initial survey and a training protocol to mitigate and relieve technostress effects. Finally, they filled in the survey again. Within-group analyses were performed comparing pre- again...

Learning approximate semi-explicit hybrid MPC with an application to microgrids

We present a semi-explicit formulation of model predictive controllers for hybrid systems with feasibility guarantees. The key idea is to use a machine-learning approach to learn a compact predictor of the integer/binary components of optimal solutions of the multiparametric mixed-integer linear optimization problem associated with the controller, so that, on-line, only a linear programming problem must be solved. In this scheme, feasibility is ensured by a simple rule-based engine that corre...

Development of an innovative and sustainable sail-drone

Object of this work is the preliminary design and development of an innovative electric marine ASV (Autonomous Surface Vehicle). Propulsion of the drone is assured by a simplified sail system controlled by a system of electric actuators. All the electric systems are fed by the energy provided by a system of solar cells, so the autonomy of the proposed system is almost unlimited. The aim of this kind of sustainable marine vehicle is the exploration and the patrolling of wide marine areas with ...

Statistical physics of multimode ordered and disordered lasers

The adoption of a statistical mechanical framework in optics provides realistic models for multimode laser systems, whose experimental implications are presented and critically analyzed. A model for passive mode locking lasers is analyzed beyond the mean-field approximation, accounting for the presence of many well-resolved frequencies of the lasing modes. The inhomogeneous structure in the nonlinear "mode locked" interaction network is shown to yield short pulses and phase waves with nontriv...

Learning Nonlinear State-Space Models Using Deep Autoencoders

We introduce a new methodology for the identification of nonlinear state-space models using machine-learning techniques based on deep autoencoders for dimensionality reduction and neural networks. By learning a direct acyclic computational graph, our framework simultaneously identifies the nonlinear output and state-update maps, and optionally a neural state observer. After formulating the approach in detail and providing guidelines for tuning the related hyperparameters and reducing the mode...

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