1,720,961 research outputs found
A multi-sensor indoor tracking system for autonomous marine model-scale vehicles
No full textAttitude estimation is a popular topic in marine engineering and robotics; the
position and orientation of a vehicle are required as feedback from several control algorithms to
improve autonomous navigation capabilities, such as dynamic positioning, track keeping, and
autodocking. Typically, position and heading angles are provided by the Global Positioning
System and compass. Usually, during the development and testing, the experiments are
performed in a controlled environment, such as an indoor test tank. However, Global Positioning
System systems can be unreliable due to non-negligible model scale errors or the absence of
line-of-sight with the satellites. This article presents an experimental tracking system setup
suitable for indoor testing facilities. In particular, the paper presents a tracking system based
on a GigE camera and ArUco markers detection and a LiDAR-based tracking system relying
on unsupervised machine learning techniques. The MQTT broker-based publish/subscribe
message-queuing protocol allows real-time data communication and sharing. The proposed
system was developed, installed, and tested in the COMPASS laboratory (University of Genoa).
The two tracking systems’ outcomes have been compared. Eventually, an accuracy analysis was
performed by comparing the results to the ground truth in purpose-built experiments. The
proposed approach can estimate the degrees of freedom of a self-propelled model-scale vessel in
an indoor testing facility without requiring active or powered markers and share the information
acquired with multiple entities in real-time at a high frame rate
Obstacle Detection in Real and Synthetic Harbour Scenarios
No full textIn the last decade, the autonomous vehicle has been investigated by both academia and industry. One of the open research topics is obstacle detection and avoidance in real-time; for such a challenge, the most used approaches are based on deep learning, especially in the automotive sector. Usually, trained neural networks are used to detect the obstacles by receiving the point clouds from LiDAR as input data. However, this approach is currently not feasible in the marine sector as there are no large datasets of LiDAR point clouds and relatively few RGB images available to train networks. For such a reason, this paper aims to present the first step for the design of an alternative approach that integrates unsupervised and supervised learning algorithms for the detection and tracking of both fixed and moving obstacles. A virtual scenario that can be customized according to the users’ purpose has been developed and used to collect data by emulating the LiDAR and camera behaviour. Moreover, the preliminary on-field LiDAR recording is presented and processed. The unsupervised clustering algorithms have been tested, and the pros and cons of the different clustering approaches are shown
Trade-off between power and bandwidth consumption in a reconfigurable xhaul network architecture
Get PDFThe increasing number of wireless devices, the high required traffic bandwidth, and power consumption will lead to a revolution of mobile access networks, which is not a simple evolution of traditional ones. Cloud radio access network technologies are seen as promising solution in order to deal with the heavy requirements defined for 5G mobile networks. The introduction of the common public radio interface (CPRI) technology allows for a centralization in BaseBand unit (BBU) of some access functions with advantages in terms of power consumption saving when switching off algorithms are implemented. Unfortunately, the advantages of the CPRI technology are to be paid with an increase in required bandwidth to carry the traffic between the BBU and the radio remote unit (RRU), in which only the radio functions are implemented. For this reason, a tradeoff solution between power and bandwidth consumption is proposed and evaluated. The proposed solution consists of: 1) handling the traffic generated by the users through both RRU and traditional radio base stations (RBS) and 2) carrying the traffic generated by the RRU and RBS (CPRI and Ethernet flows) with a reconfigurable network. The proposed solution is investigated under the lognormal spatial traffic distribution assumption. After proposing resource dimensioning analytical models validated by simulation, we show how the sum of the bandwidth and power consumption may be minimized with the deployment of a given percentage of RRU. For instance we show how in 5G traffic scenarios this percentage can vary from 30% to 50% according to total traffic amount handled by a switching node of the reconfigurable network
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe 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
Variations on the Author
Get PDF“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
Get PDFWe 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
Get PDFWe 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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