Archivio della ricerca della Scuola Superiore Sant'Anna
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Explicable hyper-reduced order models on nonlinearly approximated solution manifolds of compressible and incompressible Navier-Stokes equations
No full textA slow decaying Kolmogorov n-width of the solution manifold of a parametric partial differential equation precludes the realization of efficient linear projection-based reduced-order models. This is due to the high dimensionality of the reduced space needed to approximate with sufficient accuracy the solution manifold. To solve this problem, neural networks, in the form of different architectures, have been employed to perform accurate nonlinear regressions of the solution manifolds. However, the majority of the implementations are non-intrusive black-box surrogate models and only a part of them perform dimension reduction from the number of degrees of freedom of the discretized parametric models to a latent dimension. We present a new intrusive and explicable methodology for reduced-order modeling that employs neural networks for the solution manifold approximation but that does not discard the physical and numerical models underneath in the predictive/online stage. We will focus on autoencoders used to compress further the dimensionality of linear approximants of solution manifolds, achieving in the end a nonlinear dimension reduction. After having obtained an accurate nonlinear approximant, we seek for the solutions on the latent manifold with the residual-based nonlinear least-squares Petrov-Galerkin method, opportunely hyper-reduced in order to be independent of the number of degrees of freedom. New adaptive hyper-reduction strategies are developed along with the employment of local nonlinear approximants. We test our methodology on two nonlinear time dependent parametric benchmarks involving a supersonic flow past a NACA airfoil with changing Mach number and an incompressible turbulent flow around the Ahmed body with changing slant angle
C. M. Stracke, D. Griffiths, D. Pappa, S. Bećirović, E. Polz, L. Perla, A. Di Grassi, S. Massaro, M. P. Skenduli, D. Burgos, V. Punzo, D. Amram, X. Ziouvelou, D. Katsamori, S. Gabriel, N. Nahar, J. Schleiss, P. Hollins. Analysis of Artificial Intelligence Policies for Higher Education in Europe, International Journal of Interactive Multimedia and Artificial Intelligence, vol. 9, no. 2, pp. 124-137, 2025, http://dx.doi.org/10.9781/ijimai.2025.02.011
Get PDFThis paper analyses 15 AI policies for higher education from eight European countries, drawn from individual
universities, from consortia of universities and from government agencies. Based on an overview of current
research findings, it focuses the comparison of different aspects among the selected AI policies. The analysis
distinguishes between four potential target groups, namely students, teachers, education managers and policy
makers. The paper aims at contributing to the further development and improvement of AI policies for higher
education through the identification of commonalities and gaps within the existing AI policies. Moreover, it
calls for further and in particular evidence-based research to identify the potential and practical impact of AI
in higher education and highlights the need to combine AI use in (higher) education with education about AI,
often called as AI literac
[L'impresa che vogliamo] Finalità e performance d’impresa: il contributo del costruttivismo pragmatico
Get PDFThe Standardization of Non-pecuniary Damages in a Comparative Perspective: The Cases of Ireland, Italy, and the Netherlands
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The End of the Victorian Era: Reflections on an Edwardian Viewpoint
No full textThis short piece makes some points on the end of Victorian age as perceived and fictionalised by a contemporary author, John Galsworthy. In one of the novels of his Forsyte Saga, first published in 1921, Galsworthy brought back Queen Victoria’s death and funeral procession. After analysing this passage, the piece addresses the issues of historical continuity and legitimacy of the British monarchy
Experimental Evaluation of Commercial OTN Transceivers under Emulated Weak Turbulence
No full textIn next-generation networks, the integration of satellite network segments within the existing terrestrial ones represents a key element to deliver high-speed connectivity with increased coverage, scalability, and reliability. The development of optical satellite links could be eased by taking advantage of the mature technology deployed in fiber-based networks. Differently from fiber optics propagation, laser beams traveling across the atmosphere experience turbulence-induced fading. Considering that commercial hardware has been designed to work in the static fiber channel, degradation of the communication performance is expected when the same devices are employed in scintillation-affected links. We present the first experimental performance assessment of commercial Optical Transport Network (OTN) equipment under the effect of scintillation. Our study focuses on a pre-amplified receiver employing coherent 100G and IM/DD 10G transceivers. We setup a testbed that emulates weak turbulence, reproducing the scintillation statistics at the receiver typical of feeder links. Our results highlight differences between 100G coherent and 10G IM/DD transceivers in terms of reliability, providing insights for hardware optimization and network design in future optical feeder links systems
La crescita della robotica in Cina. Un’analisi del settore attraverso le sue politiche, le aziende chiave e la ricerca
No full textThe Legal Implications of Results-based Agri-Environmental and Climate Commitments in the EU Common Agricultural Policy
No full textNeuroethology of natural actions in freely moving monkeys
Get PDFThe current understanding of primate natural action organization derives from laboratory experiments in restrained contexts (RCs) under the assumption that this knowledge generalizes to freely moving contexts (FMCs). In this work, we developed a neurobehavioral platform to enable wireless recording of the same premotor neurons in both RCs and FMCs. Neurons often encoded the same hand and mouth actions differently in RCs and FMCs. Furthermore, in FMCs, we identified cells that selectively encoded actions untestable during RCs and others that displayed mixed selectivity for multiple actions, which is compatible with an organization based on cortical motor synergies at different levels of complexity. Cross-context decoding demonstrated that neural activity in FMCs is richer and more generalizable than in RCs, which suggests that neuroethological approaches are better suited to unveil the neural bases of behavior