1,720,970 research outputs found
Decomposition-based forecasting with application to shipboard electric loads
Variational Mode Decomposition (VMD) was presented in 2014 as a general tool for function decom-
position that subdivides functions into band-limited components. Although it was not specifically
designed for forecasting, researchers and practitioners have made significant efforts to employ VMD
as a preprocessing step for machine-learning-based predictors. In this viewpoint, the original signal
is decomposed into band-limited subsignals, a machine learning-based system predicts the future
behavior of each subsignal, and the components’ predictions are recombined to generate the forecast
of the original signal. Initially proposed for univariate cases, VMD was later extended to multivari-
ate contexts. While this step expanded the application of VMD to forecasting with multivariate
input, its usage as a preprocessing step for a predictor is less straightforward than the univariate
case, and extra care needs to be employed to properly deal with the added complexity. The present
work critically reviews the theory and implementation of VMD as a preprocessing step, analyzing
these aspects in relation to forecasting. Furthermore, established facts on the nature of machine
learning-based predictors are discussed to better refine potential new research avenues, especially in
the building of practical tools. Finally, this work introduces new algorithmic concepts with broad
applicability for enhancing forecasting systems
Schema introduttivo alla geologia delle Epiliguridi dell'Appennino modenese e delle aree limitrofe
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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