A robust ransac-based planet radius estimation for onboard visual based navigation

Individual spacecraft manual navigation by human operators from ground station is expected to be an emerging problem as the number of spacecraft for space exploration increases. Hence, as an attempt to reduce the burden to control multiple spacecraft, future missions will employ smart spacecraft able to navigate and operate autonomously. Recently, image-based optical navigation systems have proved to be promising solutions for inexpensive autonomous navigation. In this paper, we propose a robust image processing pipeline for estimating the center and radius of planets and moons in an image taken by an on-board camera. Our custom image pre-processing pipeline is tailored for resource-constrained applications, as it features a computationally simple processing flow with a limited memory footprint. The core of the proposed pipeline is a best-fitting model based on the RANSAC algorithm that is able to handle images corrupted with Gaussian noise, image distortions, and frame drops. We report processing time, pixel-level error of estimated body center and radius and the effect of noise on estimated body parameters for a dataset of synthetic images

Evaluation of maternal perception of children's weight and Body Mass Index in Tuscany, Italy

Background: The prevention of overweight is a high-priority public health task. The perception that parents have of their children’s nutritional status is a well recognized risk factor for obesity in children, so the aim of our study was to evaluate mothers’ perceptions of their children’s nutritional status. Methods: We conducted, in 2016, a cross-sectional study enrolling1710 children (third grade of all primary schools ) in Tuscany, as well as their mothers. Mothers’ information were collected through a self-administered questionnaire, while children (weighed and measured) filled a questionnaire under the supervision of qualified personnel. Results: 1449 children completed the questionnaire. 74.12% of mothers were able to correctly identify children BMI. The non correct classification tends to significantly decrease in presence of a high educational level compared to low educational level. Mothers’ BMI seems to not be associated with misclassification. The non correct classification was significantly associated with mothers’ opinion about their children’s eating habit. Conclusion: Our data confirmed that, in Tuscany, a limited percentage of mothers tend to misclassify the nutritional state of their children, but in order to maintain these encouraging results, further efforts should be done in order to make all mothers able to correctly evaluate their children. Statements:Authors declare no conflict of interest. The study was conducted according to the criteria set by the declaration of Helsinki and each subject signed an informed consent before participating to the study. Approval of the protocol was obtained from the institutional review board of the National Institute of Health, including the use of opt-out consent; that is, parents could refuse participation but the lack of a returned form was taken to imply consent to their child’s participation

Dual-readout Calorimetry

The RD52 Project at CERN is a pure instrumentation experiment whose goal is to understand the fundamental limitations to hadronic energy resolution, and other aspects of energy measurement, in high energy calorimeters. We have found that dual-readout calorimetry provides heretofore unprecedented information event-by-event for energy resolution, linearity of response, ease and robustness of calibration, fidelity of data, and particle identification, including energy lost to binding energy in nuclear break-up. We believe that hadronic energy resolutions of {\sigma}/E $\approx$ 1 - 2% are within reach for dual-readout calorimeters, enabling for the first time comparable measurement preci- sions on electrons, photons, muons, and quarks (jets). We briefly describe our current progress and near-term future plans. Complete information on all aspects of our work is available at the RD52 website http://highenergy.phys.ttu.edu/dream/.Comment: 10 pages, 10 figures, Snowmass White pape

CloudScout: A deep neural network for on-board cloud detection on hyperspectral images

The increasing demand for high-resolution hyperspectral images from nano and microsatellites conflicts with the strict bandwidth constraints for downlink transmission. A possible approach to mitigate this problem consists in reducing the amount of data to transmit to ground through on-board processing of hyperspectral images. In this paper, we propose a custom Convolutional Neural Network (CNN) deployed for a nanosatellite payload to select images eligible for transmission to ground, called CloudScout. The latter is installed on the Hyperscout-2, in the frame of the Phisat-1 ESA mission, which exploits a hyperspectral camera to classify cloud-covered images and clear ones. The images transmitted to ground are those that present less than 70% of cloudiness in a frame. We train and test the network against an extracted dataset from the Sentinel-2 mission, which was appropriately pre-processed to emulate the Hyperscout-2 hyperspectral sensor. On the test set we achieve 92% of accuracy with 1% of False Positives (FP). The Phisat-1 mission will start in 2020 and will operate for about 6 months. It represents the first in-orbit demonstration of Deep Neural Network (DNN) for data processing on the edge. The innovation aspect of our work concerns not only cloud detection but in general low power, low latency, and embedded applications. Our work should enable a new era of edge applications and enhance remote sensing applications directly on-board satellite

Hadron detection with a dual-readout fiber calorimeter

In this paper, we describe measurements of the response functions of a fiber-based dual- readout calorimeter for pions, protons and multiparticle "jets" with energies in the range from 10 to 180 GeV. The calorimeter uses lead as absorber material and has a total mass of 1350 kg. It is complemented by leakage counters made of scintillating plastic, with a total mass of 500 kg. The effects of these leakage counters on the calorimeter performance are studied as well. In a separate section, we investigate and compare different methods to measure the energy resolution of a calorimeter. Using only the signals provided by the calorimeter, we demonstrate that our dual-readout calorimeter, calibrated with electrons, is able to reconstruct the energy of proton and pion beam particles to within a few percent at all energies. The fractional widths of the signal distributions for these particles (sigma/E) scale with the beam energy as 30%/sqrt(E), without any additional contributing terms

System Test of the ATLAS Muon Spectrometer in the H8 Beam at the CERN SPS

An extensive system test of the ATLAS muon spectrometer has been performed in the H8 beam line at the CERN SPS during the last four years. This spectrometer will use pressurized Monitored Drift Tube (MDT) chambers and Cathode Strip Chambers (CSC) for precision tracking, Resistive Plate Chambers (RPCs) for triggering in the barrel and Thin Gap Chambers (TGCs) for triggering in the end-cap region. The test set-up emulates one projective tower of the barrel (six MDT chambers and six RPCs) and one end-cap octant (six MDT chambers, A CSC and three TGCs). The barrel and end-cap stands have also been equipped with optical alignment systems, aiming at a relative positioning of the precision chambers in each tower to 30-40 micrometers. In addition to the performance of the detectors and the alignment scheme, many other systems aspects of the ATLAS muon spectrometer have been tested and validated with this setup, such as the mechanical detector integration and installation, the detector control system, the data acquisition, high level trigger software and off-line event reconstruction. Measurements with muon energies ranging from 20 to 300 GeV have allowed measuring the trigger and tracking performance of this set-up, in a configuration very similar to the final spectrometer. A special bunched muon beam with 25 ns bunch spacing, emulating the LHC bunch structure, has been used to study the timing resolution and bunch identification performance of the trigger chambers. The ATLAS first-level trigger chain has been operated with muon trigger signals for the first time

Single hadron response measurement and calorimeter jet energy scale uncertainty with the ATLAS detector at the LHC

The uncertainty on the calorimeter energy response to jets of particles is derived for the ATLAS experiment at the Large Hadron Collider (LHC). First, the calorimeter response to single isolated charged hadrons is measured and compared to the Monte Carlo simulation using proton-proton collisions at centre-of-mass energies of sqrt(s) = 900 GeV and 7 TeV collected during 2009 and 2010. Then, using the decay of K_s and Lambda particles, the calorimeter response to specific types of particles (positively and negatively charged pions, protons, and anti-protons) is measured and compared to the Monte Carlo predictions. Finally, the jet energy scale uncertainty is determined by propagating the response uncertainty for single charged and neutral particles to jets. The response uncertainty is 2-5% for central isolated hadrons and 1-3% for the final calorimeter jet energy scale.Comment: 24 pages plus author list (36 pages total), 23 figures, 1 table, submitted to European Physical Journal

Measurement of the cross-section and charge asymmetry of WW bosons produced in proton-proton collisions at s=8\sqrt{s}=8 TeV with the ATLAS detector

This paper presents measurements of the $W^+ \rightarrow \mu^+\nu$ and $W^- \rightarrow \mu^-\nu$ cross-sections and the associated charge asymmetry as a function of the absolute pseudorapidity of the decay muon. The data were collected in proton--proton collisions at a centre-of-mass energy of 8 TeV with the ATLAS experiment at the LHC and correspond to a total integrated luminosity of 20.2~\mbox{fb^{-1}}. The precision of the cross-section measurements varies between 0.8% to 1.5% as a function of the pseudorapidity, excluding the 1.9% uncertainty on the integrated luminosity. The charge asymmetry is measured with an uncertainty between 0.002 and 0.003. The results are compared with predictions based on next-to-next-to-leading-order calculations with various parton distribution functions and have the sensitivity to discriminate between them.Comment: 38 pages in total, author list starting page 22, 5 figures, 4 tables, submitted to EPJC. All figures including auxiliary figures are available at https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PAPERS/STDM-2017-13

Standalone vertex finding in the ATLAS muon spectrometer

A dedicated reconstruction algorithm to find decay vertices in the ATLAS muon spectrometer is presented. The algorithm searches the region just upstream of or inside the muon spectrometer volume for multi-particle vertices that originate from the decay of particles with long decay paths. The performance of the algorithm is evaluated using both a sample of simulated Higgs boson events, in which the Higgs boson decays to long-lived neutral particles that in turn decay to bbar b final states, and pp collision data at √s = 7 TeV collected with the ATLAS detector at the LHC during 2011