Search results for "e learning"

La DaD nell’emergenza Covid19: restrizione spaziale e sfida per una nuova temporalizzazione

2020

L’introduzione della DaD nell’università, come risposta di emergenza alla pandemia del Covid19, ha comportato inevitabilmente il sacrificio della dimensione spaziale nel percorso formativo degli studenti e nella loro socialità. Questa restrizione, tuttavia, può creare il presupposto per riguadagnare in intensità ciò che si perde in estensione e ripensare, in termini filosofici, il rapporto tra temporalizzazione e spazializzazione nel processo di costruzione della personalità nella sua coscienza storica. The introduction of the DDA in the university, as an emergency response to the Covid19 pandemic, inevitably entailed the sacrifice of the spatial dimension in the training of students and in…

Foreign language learning in multilingual Germany

2021

This special issue on foreign language (FL) learning in multilingual contextsprovides insights into cross- and inter-linguistic phenomena comparingmonolingual and multilingual students who learn FLs in linguistically het-erogeneous classrooms. All contributions are based on data gathered in pro-jects carried out within the research cluster “Language education andmultilingualism”/“Sprachliche Bildung und Mehrsprachigkeit”, which hasbeen funded by the German Federal Ministry for Education and Research(Bundesministerium für Bildung und Forschung, BMBF) from 2013 to 2020. Bybringing together linguistic and educational perspectives on FL learning andteaching as well as different methodological a…

Dynamical learning of a photonics quantum-state engineering process

2021

Abstract. Experimental engineering of high-dimensional quantum states is a crucial task for several quantum information protocols. However, a high degree of precision in the characterization of the noisy experimental apparatus is required to apply existing quantum-state engineering protocols. This is often lacking in practical scenarios, affecting the quality of the engineered states. We implement, experimentally, an automated adaptive optimization protocol to engineer photonic orbital angular momentum (OAM) states. The protocol, given a target output state, performs an online estimation of the quality of the currently produced states, relying on output measurement statistics, and determine…

Monte Carlo Simulations of Au38(SCH3)24 Nanocluster Using Distance-Based Machine Learning Methods

2020

We present an implementation of distance-based machine learning (ML) methods to create a realistic atomistic interaction potential to be used in Monte Carlo simulations of thermal dynamics of thiol...

Machine learning regression algorithms for biophysical parameter retrieval: Opportunities for Sentinel-2 and -3

2012

Abstract ESA's upcoming satellites Sentinel-2 (S2) and Sentinel-3 (S3) aim to ensure continuity for Landsat 5/7, SPOT-5, SPOT-Vegetation and Envisat MERIS observations by providing superspectral images of high spatial and temporal resolution. S2 and S3 will deliver near real-time operational products with a high accuracy for land monitoring. This unprecedented data availability leads to an urgent need for developing robust and accurate retrieval methods. Machine learning regression algorithms may be powerful candidates for the estimation of biophysical parameters from satellite reflectance measurements because of their ability to perform adaptive, nonlinear data fitting. By using data from …

Recent Advances in Techniques for Hyperspectral Image Processing

2009

International audience; Imaging spectroscopy, also known as hyperspectral imaging, has been transformed in less than thirty years from being a sparse research tool into a commodity product available to a broad user community. Currently, there is a need for standardized data processing techniques able to take into account the special properties of hyperspec- tral data. In this paper, we provide a seminal view on recent advances in techniques for hyperspectral image processing. Our main focus is on the design of techniques able to deal with the high-dimensional nature of the data, and to integrate the spa- tial and spectral information. Performance of the discussed techniques is evaluated in …

2016

Gianluca Tramontana was supported by the GEOCARBON EU FP7 project (GA 283080). Dario Papale, Martin Jung and Markus Reichstein acknowledge funding from the EU FP7 project GEOCARBON (grant agreement no. 283080) and the EU H2020 BACI project (grant agreement no. 640176). Gustau Camps-Valls wants to acknowledge the support by an ERC Consolidator Grant with grant agreement 647423 (SEDAL). Kazuhito Ichii was supported by Environment Research and Technology Development Funds (2-1401) from the Ministry of the Environment of Japan and the JAXA Global Change Observation Mission (GCOM) project (no. 115). Christopher R. Schwalm was supported by National Aeronautics and Space Administration (NASA) gran…

Global Sensitivity Analysis of Leaf-Canopy-Atmosphere RTMs: Implications for Biophysical Variables Retrieval from Top-of-Atmosphere Radiance Data.

2019

Knowledge of key variables driving the top of the atmosphere (TOA) radiance over a vegetated surface is an important step to derive biophysical variables from TOA radiance data, e.g., as observed by an optical satellite. Coupled leaf-canopy-atmosphere Radiative Transfer Models (RTMs) allow linking vegetation variables directly to the at-sensor TOA radiance measured. Global Sensitivity Analysis (GSA) of RTMs enables the computation of the total contribution of each input variable to the output variance. We determined the impacts of the leaf-canopy-atmosphere variables into TOA radiance using the GSA to gain insights into retrievable variables. The leaf and canopy RTM PROSAIL was coupled with…

Comparing methods for computation of run-up heights of landslide-generated tsunami in the Northern Sicily continental margin

2018

The North Sicily continental margin is a very active region located in the Central Mediterranean. Strong seismicity, active tectonics and volcanism, fluid escape, high sediment supply, and widespread mass movements historically have exposed this region to marine geohazards, with a potential for tsunami generation. Morpho-bathymetric analysis revealed that one of the most common mechanisms associated with marine geohazards is due to submarine mass failure processes, genetically linked to the other processes active in this margin. With the aim to assess the risks associated with landslide-generated anomalous waves, we selected two sectors of this margin, Gulf of Palermo to the west and Patti …

Experimental socioecology: Integrative science for anthropocene landscape dynamics

2016

Abstract The emergence of coupled natural and human landscapes marked a transformative interval in the human past that set our species on the road to the urbanized, industrial world in which we live. This emergence enabled technologies and social institutions responsible for human-natural couplings in domains beyond rural, agricultural settings. The Mediterranean Landscape Dynamics Project (MedLand) is studying the interacting social and biophysical processes associated with these novel socioecological systems and their long-term consequences using a new form of 'experimental socioecology' made possible by recent advances in computation. We briefly describe the MedLand modeling laboratory, …