A high throughput hardware architecture for parallel recursive systematic convolutional encoders

During the last years, recursive systematic convolutional (RSC) encoders have found application in modern telecommunication systems to reduce the bit error rate (BER). In view of the necessity of increasing the throughput of such applications, several approaches using hardware implementations of RSC encoders were explored. In this paper, we propose a hardware intellectual property (IP) for high throughput RSC encoders. The IP core exploits a methodology based on the ABCD matrices model which permits to increase the number of inputs bits processed in parallel. Through an analysis of the proposed network topology and by exploiting data relative to the implementation on Zynq 7000 xc7z010clg400-1 field programmable gate array (FPGA), an estimation of the dependency of the input data rate and of the source occupation on the parallelism degree is performed. Such analysis, together with the BER curves, provides a description of the principal merit parameters of a RSC encoder

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

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

DETECT-AGING blind prediction contest: a benchmark for structural health monitoring of masonry buildings

The installation of monitoring systems on buildings allows analyzing variations in structural parameters over time, creating room for detection of damage. Structural Health Monitoring (SHM) systems have the potential to support pro-active risk management, where structural interventions are planned if specific thresholds related to target performance losses are achieved. DETECT-AGING is a research project of relevant national interest that was funded by the Italian Ministry of University and Research (MUR) through the PRIN 2017 programme. The project started in September 2019 and involves the universities of Bologna, Genova, Napoli Federico II, and Perugia. The main goal of the project is to develop a new analytical-instrumental approach aimed at the quantitative assessment of the effects of aging and material degradation on structural safety of cultural heritage, with special focus on masonry structures. Based on a combined use of structural models and health monitoring systems, indications and operational tools will be provided for the identification and quantification of structural damage, supporting the management of built cultural heritage. To this purpose, a two-storey masonry building, having a single room with a vault at the first floor and a timber roof, was built with the aim of being monitored and progressively and will be damaged during the project. It is equipped with a hybrid SHM system managed by the University of Perugia, which is based on both vibration and strain measurements. The present paper illustrates the main features of the case-study building and presents the results of the experimental program aimed at characterizing the mechanical properties of masonry the materials used. The final part of the paper presents a blind prediction contest based on prediction of modal features of the building in different damaged configurations

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

Caracterización física y química de ríos de montaña (Tafí del Valle-Tucumán-Argentina)

En este trabajo se estudió durante el ciclo anual 2000-2001, a los ríos Blanquito, Churqui, de La Ovejería, de Las Carreras, Tafí, El Mollar y Los Sosa, ubicados a 2000 msnm en el valle de Tafí (Tucumán-Argentina). El objetivo de esta contribución fue caracterizar e interpretar las variaciones espacio-temporales de los parámetros físicos y químicos en relación con la dinámica hidrológica a la que se encuentran sujetos estos ecosistemas acuáticos y además, comparar la calidad de sus aguas. Las variables físicas y químicas analizadas fueron: oxígeno disuelto (OD), demanda bioquímica de oxígeno (DBO5), iones mayoritarios, compuestos nitrogenados, ortofosfatos y metales pesados. Los resultados muestran que la temperatura varió entre 4.2 y 28 ◦C, el pH fluctuó de neutro a alcalino (6.7-8.7) y la conductividad eléctrica entre 64 y 296 μS/cm. El OD y la DBO5 se mostraron estables, alcanzando máximos valores de 10.1 y 2 mg/l, respectivamente. El agua pudo caracterizarse como bicarbonatada-cálcica dominante. Las concentraciones de N-NO−3 oscilaron entre 0.1 y 0.6 mg/l, el N-NO−2 sólo llegó en el río Churqui a 0.01 mg/l y el N-NH+4 alcanzó valores de 0.8 mg/l. En general los registros de los ortofosfatos fueron inferiores a 0.2 mg/l. Los metales pesados Cu2+ y Fe3+ llegaron a un máximo de 3 mg/l y 1.8 mg/l, respectivamente. Las mayores concentraciones del hierro se presentaron en el río de La Ovejería y de cobre en el río El Mollar, probablemente por contaminación antropogénica. La interpretación de los análisis de componentes principales realizados sobre la matriz de parámetros físicos y químicos, permitió diferenciar a los sistemas lóticos temporal y espacialmente. El componente 1 ordenó a los ríos de acuerdo a los iones mayoritarios predominantes y a la conductividad, lo que podría interpretarse como un eje de mineralización. Los componentes 2 y 3, ordenaron las muestras de invierno y primavera y las de verano y otoño, de acuerdo a la variación cíclica estacional coincidiendo con las condiciones climáticas del área de estudio.In this work, throughout the 2000-2001 annual period, the Blanquito, Churqui, de La Ovejería, de Las Carreras, Tafí, El Mollar and Los Sosa rivers, located at 2000 m above sea level in the Taf'ı Valley (Tucumán-Argentina) were studied. The aim of this paper was not only to characterize and understand the spatial and temporal variations of physical and chemical parameters related to the hydrological dynamics these aquatic ecosystems are subject to, but also to compare the quality of their waters. Physical and chemical variables analysed were: dissolved oxygen (DO), biochemical oxygen demand (BOD5), preponderant ions, nitrogenous compounds, orthophosphates, and heavy metals. Results show that the temperature ranged between 4.2 and 28 ◦C, pH fluctuated from neutral to alkaline (6.7-8.7) and electrical conductivity varied between 64 and 296 μS/cm. DO and BOD5 were stable and reached maximum values of 10.1 and 2 mg/l, respectively. The water could be characterized as mainly bicarbonated-calcic. N-NO−3 concentrations ranged between 0.1 and 0.6 mg/l, N-NO−2 reaching only 0.01 mg/l in the Churqui river, and N-NH+4 reached values of 0.8 mg/l. In general, orthophosphate records were lower than 0.2 mg/l. Maximum values for heavy metals, Cu2 + and Fe3 + were 3 mg/l y 1.8 mg/l, respectively. Iron highest concentrations were found in de La Ovejería river, whereas those for copper were found in El Mollar river, probably due to anthropogenic pollution. The interpretation of the main component analyses carried out on the physical and chemical parameters matrix, allowed to differentiate lotic systems both temporally and spatially. Component 1 ordered the rivers according to both the prevailing ions and conductivity, which could be interpreted as a mineralization axis. Components 2 and 3 ordered the winter and spring, and the summer and autumn samples according to the seasonal cyclic variation, coinciding with the climatic conditions of the area under study

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