1,720,983 research outputs found
METROLOGICAL CHARACTERIZATION OF A LASER-CAMERA 3D VISION SYSTEM THROUGH PERSPECTIVE-N-POINT POSE COMPUTATION AND MONTE CARLO SIMULATIONS
No full textThis study focuses on the metrological characterization of a 3D vision system consisting in the fusion of a CMOS camera sensor with a 2D laser scanner for contactless dimensional measurements. The purpose is to obtain an enhanced measurement information as a result of the combination of two different data sources. On one side, we can estimate the pose of the target measurand by solving the well-known Perspective-n-Point (PnP) problem from the calibrated camera. On the other side, the 2D laser scanner generates a discrete point cloud which describes the profile of the intercepted surface of the same target object. This solution allows to estimate the target's geometrical parameters through the application of fit-to-purpose algorithms that see the data acquired by the overall system as their input. The measurement uncertainty is evaluated by applying the Monte Carlo Method (MCM) to estimate the uncertainty deriving from the Probability Distribution Functions (PDF) of the input variables. Through a Design of Experiments (DOE) model the effects of different influence factors were evaluated
Multisource classification of complex rural areas by statistical and neural-network approaches
No full textThe automatic generation of land-cover inventories by using remote-sensing data is a very difficult task when complex rural areas are involved. The main difficulties are related to the characterization of such spectrally complex and heterogeneous environments and to the choice of an effective classification approach. In this paper, the usefulness of spectral (Landsat-5 Thematic Mapper images), texture (grey-level cooccurrence matrix statistics), and ancillary (terrain elevation, slope, and aspect) data to characterize two complex rural areas in central Italy is quantitatively demonstrated. A statistical and a neural-network classification approach are applied to such a multisource data set, and their classification performances are assessed and compared. The classification performances of the two approaches are quantitatively evaluated in terms of global and conditional Kappa accuracies. The Zeta statistics is used to evaluate the statistical significance of the different classification accuracies obtained by the two approaches by using multisource data
Multisource classification of complex rural areas by statistical and neural-network approaches RID A-2076-2012
No full textThe automatic generation of land-cover inventories by using remote-sensing data is a very difficult task when complex rural areas are involved. The main difficulties are related to the characterization of such spectrally complex and heterogeneous environments and to the choice of an effective classification approach. In this paper, the usefulness of spectral (Landsat-5 Thematic Mapper images), texture (grey-level cooccurrence matrix statistics), and ancillary (terrain elevation, slope, and aspect) data to characterize two complex rural areas in central Italy is quantitatively demonstrated. A statistical and a neural-network classification approach are applied to such a multisource data set, and their classification performances are assessed and compared. The classification performances of the two approaches are quantitatively evaluated in terms of global and conditional Kappa accuracies. The Zeta statistics is used to evaluate the statistical significance of the different classification accuracies obtained by the two approaches by using multisource data
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
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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