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Institution

Polytechnic University of Milan

EducationMilan, Italy
About: Polytechnic University of Milan is a education organization based out in Milan, Italy. It is known for research contribution in the topics: Finite element method & Population. The organization has 18231 authors who have published 58416 publications receiving 1229711 citations. The organization is also known as: PoliMi & L-NESS.


Papers
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Journal ArticleDOI
TL;DR: The aim of the experiment was to demonstrate that interferometric synthetic aperture radar (InSAR) measurements can indeed allow a displacement time series estimation with submillimeter accuracy (both in horizontal and vertical directions), provided that the data are properly processed and the impact of in situ as well as atmospheric effects is minimized.
Abstract: This paper presents the results of a blind experiment that is performed using two pairs of dihedral reflectors. The aim of the experiment was to demonstrate that interferometric synthetic aperture radar (InSAR) measurements can indeed allow a displacement time series estimation with submillimeter accuracy (both in horizontal and vertical directions), provided that the data are properly processed and the impact of in situ as well as atmospheric effects is minimized. One pair of dihedral reflectors was moved a few millimeters between SAR acquisitions, in the vertical and east-west (EW) directions, and the ground truth was compared with the InSAR data. The experiment was designed to allow a multiplatform and multigeometry analysis, i.e., each reflector was carefully pointed in order to be visible in both Envisat and Radarsat acquisitions. Moreover, two pairs of reflectors were used to allow the combination of data gathered along ascending and descending orbits. The standard deviation of the error is 0.75 mm in the vertical direction and 0.58 mm in the horizontal (EW) direction. GPS data were also collected during this experiment in order to cross-check the SAR results

364 citations

Journal ArticleDOI
TL;DR: It is demonstrated that floating-plant dominance can be a self-stabilizing ecosystem state, which may explain its notorious persistence in many situations and suggest that nutrient enrichment reduces the resilience of freshwater systems against a shift to floating- plant dominance.
Abstract: Invasion by mats of free-floating plants is among the most important threats to the functioning and biodiversity of freshwater ecosystems ranging from temperate ponds and ditches to tropical lakes. Dark, anoxic conditions under thick floating-plant cover leave little opportunity for animal or plant life, and they can have large negative impacts on fisheries and navigation in tropical lakes. Here, we demonstrate that floating-plant dominance can be a self-stabilizing ecosystem state, which may explain its notorious persistence in many situations. Our results, based on experiments, field data, and models, represent evidence for alternative domains of attraction in ecosystems. An implication of our findings is that nutrient enrichment reduces the resilience of freshwater systems against a shift to floating-plant dominance. On the other hand, our results also suggest that a single drastic harvest of floating plants can induce a permanent shift to an alternative state dominated by rooted, submerged growth forms.

364 citations

Journal ArticleDOI
TL;DR: Clinical Applications Ilaria Tirotta,“‡ Valentina Dichiarante,†,‡ Claudia Pigliacelli,‚‡ Gabriella Cavallo,’‡ Giancarlo Terraneo,‬‡ Francesca Baldelli Bombelli,*,†, ‡,§ Pierangelo Metrangolo,*,‡,∥ and Giuseppe Resnati.
Abstract: Clinical Applications Ilaria Tirotta,†,‡ Valentina Dichiarante,†,‡ Claudia Pigliacelli,†,‡ Gabriella Cavallo,†,‡ Giancarlo Terraneo,†,‡ Francesca Baldelli Bombelli,*,†,‡,§ Pierangelo Metrangolo,*,†,‡,∥ and Giuseppe Resnati*,†,‡ †Laboratory of Nanostructured Fluorinated Materials (NFMLab), Department of Chemistry, Materials, and Chemical Engineering “Giulio Natta” and ‡Fondazione Centro Europeo Nanomedicina, Politecnico di Milano, Milan 20131, Italy School of Pharmacy, University of East Anglia, Norwich NR4 7TJ, United Kingdom VTT-Technical Research Centre of Finland, Espoo FI-02044, Finland

363 citations

Journal ArticleDOI
TL;DR: What is still missing in the implemented DT to be compliant to their description in literature is identified and the developed DT paves the way for future research to close the loop between the MES and the DT taking into consideration the number of services that a DT could offer in a single environment.

363 citations

Proceedings ArticleDOI
05 Sep 2007
TL;DR: An audio-based video surveillance system which automatically detects anomalous audio events in a public square, such as screams or gunshots, and localizes the position of the acoustic source, in such a way that a video-camera is steered consequently.
Abstract: This paper describes an audio-based video surveillance system which automatically detects anomalous audio events in a public square, such as screams or gunshots, and localizes the position of the acoustic source, in such a way that a video-camera is steered consequently. The system employs two parallel GMM classifiers for discriminating screams from noise and gunshots from noise, respectively. Each classifier is trained using different features, chosen from a set of both conventional and innovative audio features. The location of the acoustic source which has produced the sound event is estimated by computing the time difference of arrivals of the signal at a microphone array and using linear-correction least square localization algorithm. Experimental results show that our system can detect events with a precision of 93% at a false rejection rate of 5% when the SNR is 10dB, while the source direction can be estimated with a precision of one degree. A real-time implementation of the system is going to be installed in a public square of Milan.

363 citations


Authors

Showing all 18743 results

NameH-indexPapersCitations
Alex J. Barker132127384746
Pierluigi Zotto128119778259
Andrea C. Ferrari126636124533
Marco Dorigo10565791418
Marcello Giroletti10355841565
Luciano Gattinoni10361048055
Luca Benini101145347862
Alberto Sangiovanni-Vincentelli9993445201
Surendra P. Shah9971032832
X. Sunney Xie9822544104
Peter Nijkamp97240750826
Nicola Neri92112241986
Ursula Keller9293433229
A. Rizzi9165340038
Martin J. Blunt8948529225
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023302
2022811
20214,151
20204,301
20193,831
20183,767