Evaluation of project management practices in the automotive original equipment manufacturers

This paper aims at understanding the current perceptions related to the Project Management (PM) practices in the automotive sector. To this end, a questionnaire is administrated to professionals and data are analyzed via the Kruskal-Wallis test. Results show that the ICT function is poorly oriented to PM, especially for professionals with longer experience. On the contrary, the logistics function might exploit the benefits of PM tools. PM is also considered a lever for increasing the firm's reputation. This work demonstrates that PM is a challenge for future developments of organizations and it shows its importance in the automotive industry that involves increasingly complex projects

Visual odometry with depth-wise separable convolution and quaternion neural networks

Monocular visual odometry is a fundamental problem in computer vision and it was extensively studied in literature. The vast majority of visual odometry algorithms are based on a standard pipeline consisting in feature detection, feature matching, motion estimation and local optimization. Only recently, deep learning approaches have shown cutting-edge performance, replacing the standard pipeline with an end-to-end solution. One of the main advantages of deep learning approaches over the standard methods is the reduced inference time, that is an important requirement for the application of visual odometry in real-time. Less emphasis, however, has been placed on memory requirements and training efficiency. The memory footprint, in particular, is important for real world applications such as robot navigation or autonomous driving, where the devices have limited memory resources. In this paper we tackle both aspects introducing novel architectures based on Depth-Wise Separable Convolutional Neural Network and deep Quaternion Recurrent Convolutional Neural Network. In particular, we obtain equal or better accuracy with respect to the other state-of-the-art methods on the KITTI VO dataset with a reduction of the number of parameters and a speed-up in the inference time

A GAN Approach for Anomaly Detection in Spacecraft Telemetries

In spacecraft health management a large number of time series is acquired and used for on-board units surveillance and for historical data analysis. The early detection of abnormal behaviors in telemetry data can prevent failures in the spacecraft equipment. In this paper we present an advanced monitoring system that was carried out in partnership with Thales Alenia Space Italia S.p.A, a leading industry in the field of spacecraft manufacturing. In particular, we developed an anomaly detection algorithm based on Generative Adversarial Networks, that thanks to their ability to model arbitrary distributions in high dimensional spaces, allow to capture complex anomalies avoiding the burden of hand crafted feature extraction. We applied this method to detect anomalies in telemetry data collected from a simulator of a Low Earth Orbit satellite. One of the strengths of the proposed approach is that it does not require any previous knowledge on the signal. This is particular useful in the context of anomaly detection where we do not have a model of the anomaly. Hence the only assumption we made is that an anomaly is a pattern that lives in a lower probability region of the data space

Contenido de minerales en algunas especies forrajeras presentes en el pastizal natural de un sistema silvopastoril en el bajo delta del Río Paraná

We analyzed the content of phosphorus (P), calcium (Ca), magnesium (Mg), total ash (Cen) and insoluble ash (Insol), iron (Fe), copper (Cu) and zinc (Zn) in forage species growing wild in silvopastoral system of the Lower Delta of the Parana River after planting forest. 10 plants were harvested from the following species: Glyceria multiflora (Cebadilla de agua), Deyeuxia viridiflavescens (Pasto plateado), Melilotus officinalis (Trébol de olor amarillo), Phalaris angusta (Alpistillo), Lolium multiflorum (Ray gras), Lathyrus pubescens (Arvejilla), Vicia gramínea (Vicia) y Leersia hexandra (Arrocillo). They were dried, incinerated and ashes dissolved in acid. Mineral determinations were performed by atomic absorption spectrophotometry (AAS) and colorimetry. Mineral contents in the species studied here were lower than values informed previously of forage species of temperate weather and, in some cases, mineral requirements for cattle.Se realizó el análisis del contenido de fósforo (P), calcio (Ca), magnesio (Mg), hierro (Fe), cobre (Cu), zinc (Zn) y cenizas totales (Cen) e insolubles (Insol), en especies forrajeras que crecen naturalmente en el sistema silvopastoril del Bajo Delta del Río Paraná,  luego de la plantación forestal. Se cosecharon 10 plantas de cada una de las siguientesespecies: Glyceria multiflora (Cebadilla de agua), Deyeuxia viridiflavescens (Pasto plateado), Melilotus officinalis (Trébol de olor amarillo), Phalaris angusta (Alpistillo), Lolium multiflorum (Ray gras), Lathyrus pubescens (Arvejilla), Vicia gramínea (Vicia) y Leersia hexandra (Arrocillo). Se secaron y calcinaron, resuspendiendo las cenizas en ácido. Las determinaciones de minerales se realizaron por espectrofotometría de absorción atómica (EAA) y colorimetría. Las concentraciones determinadas fueron inferiores a las informadas para forrajeras de clima templado y, en algunos casos, a los requerimientos establecidos para ganado bovino

Topical Review on "Beta-beams"

Neutrino physics is traversing an exciting period, after the important discovery that neutrinos are massive particles, that has implications from high-energy physics to cosmology. A new method for the production of intense and pure neutrino beams has been proposed recently: the ``beta-beam''. It exploits boosted radioactive ions decaying through beta-decay. This novel concept has been the starting point for a new possible future facility. Its main goal is to address the crucial issue of the existence of CP violation in the lepton sector. Here we review the status and the recent developments with beta-beams. We discuss the original, the medium and high-energy scenarios as well as mono-chromatic neutrino beams produced through ion electron-capture. The issue of the degeneracies is mentioned. An overview of low energy beta-beams is also presented. These beams can be used to perform experiments of interest for nuclear structure, for the study of fundamental interactions and for nuclear astrophysics.Comment: Topical Review for Journal of Physics G: Nuclear and Particle Physics, published version, minor corrections, references adde

Rehabilitación de ambientes perdidos en megaciudades: el caso de la Cuenca Matanza-Riachuelo

La tendencia a degradar o reemplazar la matriz natural (clímax) por sistema agropecuarios o viviendas humanas es tan extensa e intensa, que también está afectando a otros componentes del paisaje como los corredores ribereños y sus humedales asociados, ambientes edáficos, locales, de alta sensibilidad ecológica, así como a diversos parches y remanentes naturales en zonas de alta incidencia urbana. El objeto central de este capítulo será analizar los procesos de rehabilitación ecológica en la cuenca Matanza-Riachuel

RPC-based Muon Identification System for the neutrino detector of the SHiP experiment

The SHiP experiment has been proposed at CERN to shed light on phenomena still unexplained in the framework of the Standard Model, such as the nature of dark matter, the baryonic asymmetry of the Universe and the neutrino oscillations, searching for hints of New Physics. A section of the detector will be dedicated to the study of neutrino physics with special emphasis on tau neutrino properties, still very poorly measured. A system to identify the muons produced in neutrino interactions, based on RPC technology, has been proposed and it is presented in detail in this paper