1,721,004 research outputs found
Improvements in on-board systems design for advanced sustainable air mobility
No full textThis paper describes the activity proposed in the context of National Center for Sustainable Mobility (CN MOST) for designing an advanced core Guidance, Navigation, and Control system together with an effective on-board systems configuration for sustainable air mobility. A Model Based Systems Engineering strategy is adopted to support the design and development phases. The introduction of new sustainability objectives and the U-Space services to support the integration of unmanned air vehicles in the traditional Air Traffic Management drives the need of a full redesign of on-board systems that must be interfaced with different air platform categories. High performance processing units are considered for embedded systems, including but not limited to machine learning based, image processing and data fusion algorithms for advanced navigation. Three use-cases are presented as reference platform and mission types for validating the proposed systems configuration, specifically unmanned electric Vertical Take Off and Landing aircraft, fully electric general aviation aircraft, and hybrid-electric regional aircraft
Trajectory flight-time prediction based on machine learning for unmanned traffic management
No full textThis paper describes the study conducted to predict the trajectory flight-time of a drone adopting a machine learning approach. The proposed method has been carried out developing a feedforward neural network to estimate the flight-time needed by the drone to perform a selected corner of a designed path. To acquire a consistent database for the neural network training several reference corner paths have been flown by a test drone. The reference corners have fixed side length and different turning angle. Neural network input parameters are the corner angle, relative orientation and intensity of wind. From the telemetry analysis the flight-time to fly the corner path has been computed and employed to train the neural network. The Levenberg-Marquardt algorithm and the Bayesian Regularization backpropagation algorithm have been exploited as training functions, analyzing several neural network architectures with a different number of hidden layers and neurons. At the end, the neural networks that are characterized by the best training and test performance have been selected for each training function. Stating the trained network, a generic path has been planned to test the proposed method. The error between the estimated flight-time and the real flight-time from the drone telemetry has been evaluated
Above Ground Biomass Estimation in Agroforestry Environment by UAS and RGB Imagery
No full textRapid advances in unmanned aerial system (UAS) platforms have boosted the use of low-altitude aerial imagery in estimating crops Above Ground Biomass (AGB). By electro-optical camera onboard UAS it is easy to obtain crop information at the farm scale under adequate weather conditions with high temporal and spatial resolution. In order to assess the biomass of woody crops, this study intends to evaluate the potential of Red Green Blue (RGB)-imagery and of the relevant vegetation indices to compute diameter at breast height and plant height as the main input for AGB estimation. The method monitors the biomass, carbon stock, and coverage of tree plants by integrating various techniques and software. It is also of general validity, so it can apply to other woody crops and results may help managers of ecosystem assess and monitor ecosystems as well as remediation and revegetation initiatives
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Evaluating a Reinforcement Learning Approach for Collision Avoidance with Heterogeneous Aircraft
No full textThis paper focuses on the problem of decentralized collision avoidance for Unmanned Aircraft Systems. The considered setting involves drones that can sense the presence of other traffic within a specified sensing area, for example due to remote ID signal broadcasts or visual perception, and take evasive maneuvers according to drone dynamics to ensure a minimum separation. A Reinforcement Learning approach is investigated to adapt the ego drone trajectory in response to the limited observations of the intruders trajectory within a bounded environment. The key aim of the work is on designing evasive maneuvers for ego drone when sharing the airspace with heterogeneous aircraft that have varying sensing capabilities, maneuverability, and risk-awareness. Beside reachability-based techniques, which offer a powerful framework for identifying safe trajectories under worst case actions by other agents, the proposed approach aims at adapting the evasive maneuver to the incoming aircraft behavior. Tests were executed in the simulated environment comparing the results obtained with heterogeneous incoming aircraft with different maneuverability levels and with randomly selected fixed obstacles. The Reinforcement Learning based method performance was also tested adopting different state vector parameters. The results show that the proposed approach can support the implementation of safe collision avoidance services allowing the generation of adaptive maneuvers for Unmanned Aerial System Traffic Management
RCS of a F-35 Stealth Aircraft: Statistical Analyses of a POFACETS Model
Full text linkThis paper analyzes the simulated radar cross section (RCS) of the POFACETS F-35 aircraft model versus azimuth and elevation aspect angle. In particular, the RCS values are obtained for all azimuths and for a short-range (SR) elevation regime. Moreover, the tests are conducted considering three different frequencies of the transmitted wave, viz. 0.3 GHz (VHF), 1GHz(L), and 10 GHz(X). The RCS data for the F - 3 5 aircraft are derived through a realistic model implemented in the Mathworks Matlab simulation toolbox POFACETS, developed at the Naval Postgraduate School of the USN. Therefore, a statistical analysis of the simulated RCSs is performed to establish among which is the best theoretical model representing these data. In this respect, the parameters for the theoretical distribution are selected using the moment matching technique. Then, the best fit statistical distribution is selected as the one minimizing the Cramèr-von Mises (CVM) distance from the empirical one. Finally, the spatial autocorrelation function is also derived to evaluate the degree of spatial decorrelation under each elevation regime and operative frequency
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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