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Plastic marine litter is a very complex global environmental issue, with plastic litter at the sea surface representing only a small fraction of plastic entering the sea. In this respect, the BLUE project investigated the potential of diverse LIDAR techniques (backscatter, fluorescence, Raman) to address the detection of plastic litter not only floating on the sea surface, but also suspended in the first few metres under the surface, with also a focus on detecting microplastics and discriminating plastic from other types of litter. The approach adopted was four-fold:
CNR-IFAC
Quantum algorithms process information stored in qubits, the basic memory unit of quantum processors, and quantum operations (called gates) are the building blocks of quantum algorithms. In order to be run on quantum computing hardware, quantum algorithms must be compiled into a set of elementary machine instructions (i.e., quantum gates).
ISTC-CNR
Shannon-Nyquist theorem rules the signal sampling stating that the signal must be sampled at a rate of at least twice the maximum frequency present in the signal to be fully reconstructed. Compressive Sensing (CS) theory affirms that a sparse signal can be efficiently reconstructed by the acquisition of a number of samples far below the minimal one dictated by Nyquist theorem, thus providing a new approach to data acquisition. CS technique is based on the concept of sparsity. The information rate of a continuous 'sparse' signal may be much smaller than suggested by its bandwidth.
CNR-IFAC
The Medium Earth Orbit (MEO) region, home of the operational Global Navigation Satellite Systems (GNSS) GPS and Glonass, is becoming more and more exploited with the advent of the European Galileo and the Chinese Beidou constellations, both in their build-up phase. The sensitive applications of the navigation satellites and the absence of any natural sink mechanism, such as the atmospheric drag, call for a careful debris prevention policy able to preserve the MEO environment, avoiding in the future the problems now already faced by the LEO and the Geostationary Orbit (GEO) environments.
IFAC-CNR
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