On Designing Compliant Actuators Based On Dielectric Elastomers

Dielectric Elastomers (DE) are incompressible dielectrics which can experience deviatoric (isochoric) finite deformations in response to applied large electric fields. Thanks to the strong electro-mechanical coupling, DE intrinsically offer great potentialities for conceiving novel solid-state mechatronic devices, in particular linear actuators, which are more integrated, lightweight, economic, silent, resilient and disposable than equivalent devices based on traditional technologies. Such systems may have a huge impact in applications where the traditional technology does not allow coping with the limits of weight or encumbrance, and with problems involving interaction with humans or unknown environments. Fields such as medicine, domotic, entertainment, aerospace and transportation may profit. For actuation usage, DE are typically shaped in thin films coated with compliant electrodes on both sides and piled one on the other to form a multilayered DE. DE-based Linear Actuators (DELA) are entirely constituted by polymeric materials and their overall performance is highly influenced by several interacting factors; firstly by the electromechanical properties of the film, secondly by the mechanical properties and geometry of the polymeric frame designed to support the film, and finally by the driving circuits and activation strategies. In the last decade, much effort has been focused in the devolvement of analytical and numerical models that could explain and predict the hyperelastic behavior of different types of DE materials. Nevertheless, at present, the use of DELA is limited. The main reasons are 1) the lack of quantitative and qualitative models of the actuator as a whole system 2) the lack of a simple and reliable design methodology. In this thesis, a new point of view in the study of DELA is presented which takes into account the interaction between the DE film and the film supporting frame. Hyperelastic models of the DE film are reported which are capable of modeling the DE and the compliant electrodes. The supporting frames are analyzed and designed as compliant mechanisms using pseudo-rigid body models and subsequent finite element analysis. A new design methodology is reported which optimize the actuator performances allowing to specifically choose its inherent stiffness. As a particular case, the methodology focuses on the design of constant force actuators. This class of actuators are an example of how the force control could be highly simplified. Three new DE actuator concepts are proposed which highlight the goodness of the proposed method.

Comunicazione d'impresa in Alto Adige: Indagine sulle strategie di gestione del multilinguismo nelle PMI insediate in un territorio di contatto linguistico

La ricerca sulla comunicazione e gestione multilingue della conoscenza in azienda si è sinora concentrata sulle multinazionali o PMI in fase di globalizzazione. La presente ricerca riguarda invece le PMI in zone storicamente multilingui al fine di studiare se l’abitudine all’uso di lingue diverse sul mercato locale possa rappresentare un vantaggio competitivo. La tesi illustra una ricerca multimetodo condotta nel 2012-2013 in Alto Adige/Südtirol. Il dataset consiste in 443 risposte valide a un questionario online e 23 interviste con manager e imprenditori locali. Le domande miravano a capire come le aziende altoatesine affrontino la sfida del multilinguismo, con particolare attenzione ai seguenti ambiti: comunicazione multilingue, documentazione, traduzione e terminologia. I risultati delineano un quadro generale delle strategie di multilinguismo applicate in Alto Adige, sottolineandone punti di forza e punti deboli. Nonostante la presenza di personale multilingue infatti il potenziale vantaggio competitivo che ne deriva non è sfruttato appieno: le aziende si rivolgono ai mercati in cui si parla la loro stessa lingua (le imprese a conduzione italiana al mercato nazionale, quelle di lingua tedesca ad Austria e Germania). La comunicazione interna è multilingue solo nei casi in sia imprescindibile. Le “traduzioni fai-da-te” offrono l’illusione di gestire lingue diverse, ma il livello qualitativo rimane limitato. I testi sono sovente tradotti da personale interno privo di competenze specifiche. Anche nella cooperazione con i traduttori esterni si evidenza la mancata capacità di ottenere il massimo profitto dagli investimenti. La tesi propone delle raccomandazioni pratiche volte a ottimizzare i processi attuali e massimizzare la resa delle risorse disponibili per superare la sfida della gestione e comunicazione multilingue. Le raccomandazioni non richiedono investimenti economici di rilievo e sono facilmente trasferibili anche ad altre regioni multilingui/di confine, come ad altre PMI che impiegano personale plurilingue. Possono dunque risultare utili per un elevato numero di imprese.

Concepts and methods for efficient decentralized learning in federated settings

Deep Neural Networks (DNNs) have revolutionized a wide range of applications beyond traditional machine learning and artificial intelligence fields, e.g., computer vision, healthcare, natural language processing and others. At the same time, edge devices have become central in our society, generating an unprecedented amount of data which could be used to train data-hungry models such as DNNs. However, the potentially sensitive or confidential nature of gathered data poses privacy concerns when storing and processing them in centralized locations. To this purpose, decentralized learning decouples model training from the need of directly accessing raw data, by alternating on-device training and periodic communications. The ability of distilling knowledge from decentralized data, however, comes at the cost of facing more challenging learning settings, such as coping with heterogeneous hardware and network connectivity, statistical diversity of data, and ensuring verifiable privacy guarantees. This Thesis proposes an extensive overview of decentralized learning literature, including a novel taxonomy and a detailed description of the most relevant system-level contributions in the related literature for privacy, communication efficiency, data and system heterogeneity, and poisoning defense. Next, this Thesis presents the design of an original solution to tackle communication efficiency and system heterogeneity, and empirically evaluates it on federated settings. For communication efficiency, an original method, specifically designed for Convolutional Neural Networks, is also described and evaluated against the state-of-the-art. Furthermore, this Thesis provides an in-depth review of recently proposed methods to tackle the performance degradation introduced by data heterogeneity, followed by empirical evaluations on challenging data distributions, highlighting strengths and possible weaknesses of the considered solutions. Finally, this Thesis presents a novel perspective on the usage of Knowledge Distillation as a mean for optimizing decentralized learning systems in settings characterized by data heterogeneity or system heterogeneity. Our vision on relevant future research directions close the manuscript.