Search results for "Instrumentation"
showing 10 items of 4914 documents
A new approach for deducing the stage-discharge relationship of triangular in plan sharp-crested weirs
2013
Abstract In this paper, the outflow process of a triangular in plan sharp-crested weir is studied using the dimensional analysis and the incomplete self-similarity theory. The new stage-discharge is theoretically deduced and its testing is carried out using measurements available in literature.
Modeling particle acceleration and non-thermal emission in supernova remnants
2021
According to the most popular model for the origin of cosmic rays (CRs), supernova remnants (SNRs) are the site where CRs are accelerated. Observations across the electromagnetic spectrum support this picture through the detection of non-thermal emission that is compatible with being synchrotron or inverse Compton radiation from high energy electrons, or pion decay due to proton-proton interactions. These observations of growing quantity and quality promise to unveil many aspects of CRs acceleration and require more and more accurate tools for their interpretation. Here, we show how multi-dimensional MHD models of SNRs, including the effects on shock dynamics due to back-reaction of acceler…
The nearest X-ray emitting protostellar jet observed with HST
2009
The HH 154 jet coming from the YSO binary L1551 IRS5 is one of the closest (about 150 pc) astrophysical jet known. It is therefore a unique laboratory for studies of outflow mechanisms and of the shocks forming at the interaction front between the expanding material and the ambient medium. The substructures (knots) observed within the HH 154 jet were imaged in several spectral bands using the Hubble Space Telescope. This allows us to derive a simple characterization of the physical conditions in different structures as well as to measure the proper motion of the knots in the jet, their flux variability and shock emission over a time base of about ten years. These knots in the jet undergo si…
New solutions for energy supply: sea wave and offshore photovoltaic in Sardinia (Italy)
2018
This work illustrates a study on the integration among sea wave farm and off shore photovoltaic in Italian island (Sardinia). In order to exploit both energy sources, the paper presents an innovative prototype, designed and developed by Palermo University. According the data about sea wave and solar energy potential, we evaluated the installation of wave-solar energy farms, based on the prototype presented in this paper.
Rapid parameter determination of discrete damped sinusoidal oscillations
2020
We present different computational approaches for the rapid extraction of the signal parameters of discretely sampled damped sinusoidal signals. We compare time- and frequency-domain-based computational approaches in terms of their accuracy and precision and computational time required in estimating the frequencies of such signals, and observe a general trade-off between precision and speed. Our motivation is precise and rapid analysis of damped sinusoidal signals as these become relevant in view of the recent experimental developments in cavity-enhanced polarimetry and ellipsometry, where the relevant time scales and frequencies are typically within the ∼1 − 10 µs and ∼1 − 100 MHz ranges, …
Statistical Learning for End-to-End Simulations
2018
End-to-end mission performance simulators (E2ES) are suitable tools to accelerate satellite mission development from concet to deployment. One core element of these E2ES is the generation of synthetic scenes that are observed by the various instruments of an Earth Observation mission. The generation of these scenes rely on Radiative Transfer Models (RTM) for the simulation of light interaction with the Earth surface and atmosphere. However, the execution of advanced RTMs is impractical due to their large computation burden. Classical interpolation and statistical emulation methods of pre-computed Look-Up Tables (LUT) are therefore common practice to generate synthetic scenes in a reasonable…
Toward a Collective Agenda on AI for Earth Science Data Analysis
2021
In the last years we have witnessed the fields of geosciences and remote sensing and artificial intelligence to become closer. Thanks to both the massive availability of observational data, improved simulations, and algorithmic advances, these disciplines have found common objectives and challenges to advance the modeling and understanding of the Earth system. Despite such great opportunities, we also observed a worrying tendency to remain in disciplinary comfort zones applying recent advances from artificial intelligence on well resolved remote sensing problems. Here we take a position on research directions where we think the interface between these fields will have the most impact and be…
Signal integrity studies at optical multiplexer board for TileCal system
2007
6 pages.-- ISI Article Identifier: 000253651800006
Generation of multidimensional random pulses for radioactivity measurements
2000
Multidimensional binary pseudo-random pulses are extremely useful for the set-up calibration and testing of radioactivity measuring equipment. A new method of generation of such signals, based on the parting operation of labeled pulse trains, is presented. The concept of a general coincidence ratio is introduced. Digital window comparators and prohibited or permitted state programmers capable of performing the parting operation and controlling the values of the coincidence ratio are proposed.
Special Issue on Signal Processing and Machine Learning for Biomedical Data
2021
This Special Issue is focused on advanced techniques in signal processing, analysis, modelling, and classification, applied to a variety of medical diagnostic problems. Biomedical data play a fundamental role in many fields of research and clinical practice. Very often the complexity of these data and their large volume makes it necessary to develop advanced analysis techniques and systems. Furthermore, the introduction of new techniques and methodologies for diagnostic purposes, especially in the field of medical imaging, requires new signal processing and machine learning methods. The recent progress in machine learning techniques, and in particular deep learning, revolutionized various f…