1,721,159 research outputs found
Efficient identification of pre-flare features in SDO/AIA images through use of spatial Fourier transforms
No full textIn this "Methods " paper, we investigate how to compress SDO/AIA data by transforming the AIA source maps into the Fourier domain at a limited set of spatial frequency points. Specifically, we show that compression factors of one order of magnitude or more can be achieved without significant loss of information. The exploration of data compression techniques is motivated by our plan to train Neural Networks on AIA data to identify features that lead to a solar flare. Because the data is spatially resolved and polychromatic (as opposed to spatially-integrated, such as GOES, or monochromatic, such as magnetograms), the network can be trained to recognize features representing changes in plasma properties (e.g., temperature, density), in addition to temporal changes revealed by Sun-integrated data or physical restructuring revealed by monochromatic spatially-resolved data. However, given the immense size of a suitable training set of SDO/AIA data (more than 10(11) pixels, requiring more than one TB of memory), some form of data compression scheme is highly desirable and, in this paper, we propose a Fourier based one. Numerical experiments show that, not only Fourier maps retain more information on the original AIA images compared to straightforward binning of spatial pixels, but also that certain types of changes in source structure (e.g., thinning or thickening of an elongated filamentary structure) may be equally, if not more, recognizable in the spatial frequency domain. We conclude by describing a program of work designed to exploit the use of spatial Fourier transform maps to identify features in four-dimensional data hypercubes containing spatial, spectral, and temporal information of the state of the solar plasma prior to possible flaring activity
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
Approximation of discontinuous inverse operators with neural networks
No full textIn this work we deal with parametric inverse problems, which consist in recovering a finite number of parameters describing the structure of an unknown object, from indirect measurements. State-of-the-art methods for approximating a regularizing inverse operator by using a dataset of input-output pairs of the forward model rely on deep learning techniques. In these approaches, a neural network (NN) is trained to predict the value of the sought parameters directly from the data. In this paper, we show that these methods provide suboptimal results when a regularizing inverse operator is discontinuous with respect to the Euclidean topology. Hence, we propose a two-step strategy for approximating it by means of a NN, which works under general topological conditions. First, we embed the parameters into a subspace of a low-dimensional Euclidean space; second, we use a NN to approximate a homeomorphism between the subspace and the image of the parameter space through the forward operator. The parameters are then retrieved by applying the inverse of the embedding to the network predictions. The results are shown for the problem of x-ray imaging of solar flares with data from the Spectrometer/Telescope for Imaging X-rays. In this case, the parameter space is homeomorphic to a Moebius strip. Our simulation studies show that the use of a NN for predicting the parameters directly from the data yields systematic errors due to the non-Euclidean topology of the parameter space. The proposed strategy overcomes the discontinuity issues and furnishes stable and accurate reconstructions
OPPORTUNITIES FOR AN EFFECTIVE USE OF SOCIAL MEDIA GEOGRAPHIC INFORMATION (SMGI) WITHIN GEODESIGN APPROACH
Full text linkThis contribution focuses on two types of georeferenced User-Generated Content (geo-UGC): Volunteered Geographic Information (VGI) and Social Media Geographic Information (SMGI): both can be profitably used in spatial planning practices, thanks to the high potential of the information they enclose. Several case studies, developed by the authors, are presented to illustrate how geo-UGC can be used in different stages of spatial planning processes, supporting a more multifaceted understanding of places, contributing to more participatory processes, and fostering the collaboration between decision-makers in spatial planning practices. The Geodesign approach has been used as a base framework to underpin the discussion. In addition, the case studies show how geo-UGC can be advantageous in knowledge building on the current regional and urban dynamics, in identifying possible alternatives and in finding agreement on preferred future developments
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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