1,721,056 research outputs found
Knowledge-Based Multitarget Ship Tracking for HF Surface Wave Radar Systems
These last decades spawned a great interest toward low-power high-frequency (HF) surface-wave (SW) radars for ocean remote sensing. By virtue of their over-the-horizon coverage capability and continuous-time mode of operation, these sensors are also effective long-range early warning tools in maritime situational awareness applications providing an additional source of information for target detection and tracking. Unfortunately, they also exhibit many shortcomings that need to be taken into account, and proper algorithms need to be exploited to overcome their limitations. In this paper, we develop a knowledge-based (KB) multitarget tracking methodology that takes advantage of a priori information on the ship traffic. This a priori information is given by the ship sea lanes and by their related motion models, which together constitute the basic building blocks of a variable structure interactive multiple model procedure. False alarms and missed detections are dealt with using a joint probabilistic data association rule and nonlinearities are handled by means of the unscented Kalman filter. The KB-tracking procedure is validated using real data acquired during an HF-radar experiment in the Ligurian Sea (Mediterranean Sea). Two HFSW radar systems were operated to develop and test target detection and tracking algorithms. The overall performance is defined in terms of time-on-target, false-alarm rate (FAR), track fragmentation (TF), and accuracy. A full statistical characterization is provided using one month of data. A significant improvement of the KB-tracking procedure, in terms of system performance, is demonstrated in comparison with a standard joint probabilistic data association tracker recently proposed in the literature to track HFSW radar data. The main improvement of our approach is the better capability of following targets without increasing the FAR. This increment is much more evident in the region of low FAR, where it can be over the 30% for both the HFSW radar systems. The KB-tracking exhibits on average a reduction of the TF of about the 20% and the 13% of the utilized HFSW-radar systems
Knowledge-based ship tracking applied to HF surface wave radar data
In recent years, low-power high-frequency surface-wave radars have received significant attention thanks to their over-the-horizon coverage capability and the continuous-time operation mode. These radars have become effective long-range early-warning tools for maritime situational awareness applications. In this paper a knowledge-based multi-target tracking algorithm is described. The advantages in using a prior information on ship traffic are assessed exploiting real data acquired by two high-frequency surface-wave radars. The outcomes confirm the ability of the proposed approach to better follow targets with a time-on-target increment up to 30% with respect to existing methods. A reduction of the track fragmentation up to 20% is also observed
Variable structure interacting multiple model algorithm for ship tracking using HF surface wave radar data
These last decades spawned a great interest towards low-power High-Frequency (HF) Surface-Wave (SW) radars for ocean remote sensing. By virtue of their over-the-horizon coverage capability and continuous-time mode of operation, these sensors are also effective long-range early-warning tools in maritime situational awareness applications. In this paper we show how it is possible to take advantage of a priori information on traffic by the means of a knowledge-based multi-target tracking algorithm, demonstrating that the tracking stage can be enhanced by combining on-line data from the HFSW radar with ship traffic information. A significant improvement of the proposed procedure, in terms of system performance, is demonstrated in comparison with the state-of-the-art approach recently presented in the literature. The main benefit of our approach is the ability to better follow targets without increasing the false alarm rate. The ability to follow targets can be over 30% better than existing methods. The proposed approach also exhibits a reduction of the track fragmentation. Average gains between the 13% and the 20% are observed
Going Beyond Counting First Authors in Author Co-citation Analysis
The 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
“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
We 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
We 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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