1,720,964 research outputs found
New insights and best practices for the successful use of Empirical Mode Decomposition, Iterative Filtering and derived algorithms
Algorithms based on Empirical Mode Decomposition (EMD) and Iterative Filtering (IF) are largely implemented for representing a signal as superposition of simpler well-behaved components called Intrinsic Mode Functions (IMFs). Although they are more suitable than traditional methods for the analysis of nonlinear and nonstationary signals, they could be easily misused if their known limitations, together with the assumptions they rely on, are not carefully considered. In this work, we examine the main pitfalls and provide caveats for the proper use of the EMD- and IF-based algorithms. Specifically, we address the problems related to boundary errors, to the presence of spikes or jumps in the signal and to the decomposition of highly-stochastic signals. The consequences of an improper usage of these techniques are discussed and clarified also by analysing real data and performing numerical simulations. Finally, we provide the reader with the best practices to maximize the quality and meaningfulness of the decomposition produced by these techniques. In particular, a technique for the extension of signal to reduce the boundary effects is proposed; a careful handling of spikes and jumps in the signal is suggested; the concept of multi-scale statistical analysis is presented to treat highly stochastic signals
How to be fooled searching for significant variations of the b-value
An unbiased estimation of the b-value and of its variability is essential to verify empirically its physical contribution to the earthquake generation process, and the capability to improve earthquake forecasting and seismic hazard. Notwithstanding the vast literature on the b-value estimation, we note that some potential sources of bias that may lead to non-physical b-value variations are too often ignored in seismological common practice. The aim of this paper is to discuss some of them in detail, when the b-value is estimated through the popular Aki's formula. Specifically, we describe how a finite data set can lead to biased evaluations of the b-value and its uncertainty, which are caused by the correlation between the b-value and the maximum magnitude of the data set; we quantify analytically the bias on the b-value caused by the magnitude binning; we show how departures from the exponential distribution of the magnitude, caused by a truncated Gutenberg-Richter law and by catalogue incompleteness, can affect the b-value estimation and the search for statistically significant variations; we derive explicitly the statistical distribution of the magnitude affected by random symmetrical error, showing that the magnitude error does not induce any further significant bias, at least for reasonable amplitude of the measurement error. Finally, we provide some recipes to minimize the impact of these potential sources of bias
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
Empirical evaluation of the magnitude-independence assumption
This article has been accepted for publication in Geophysical Journal International ©: The Authors 2019. Published by Oxford University Press on behalf of the Royal Astronomical Society. All rights reserved. Uploaded in accordance with the publisher's self-archiving policy.The most common earthquake forecasting models assume that the magnitude of the next earthquake is independent from the past. This feature severely limits the capability to forecast large earthquakes with high probabilities. Here we investigate empirically on the magnitude-independence assumption, exploring if: (i) background and triggered earthquakes have the same frequency–magnitude distribution, (ii) variations of seismicity in the space–time–magnitude domain encode some information on the future earthquakes size. For this purpose, and to verify the stability of the findings, we consider seismic catalogues covering different space–time–magnitude windows, such as the Alto Tiberina Near Fault Observatory (TABOO), the California and Japanese seismic catalogues. Our approach is inspired by the nearest-neighbour method proposed by Baiesi & Paczuski and elaborated by Zaliapin et al. to distinguish between triggered and background earthquakes. Here we implement the same metric-based correlation to identify the precursory seismicity of any triggered earthquake; this allows us to analyse, for each triggered earthquake, the space–time–magnitude distribution of the seismicity that likely contributed to its occurrence. Our results show that the magnitude-independence assumption holds reasonably well in all catalogues, with a remarkable exception that is consistent with a previous independent study; this departure from the magnitude-independence assumption shows that larger events tend to nucleate at a higher distance from the ongoing sequence. We also notice that the reliability of this assumption may depend on the spatial scale considered; it holds for seismic catalogues of large areas, but we identify possible departures in small areas, reflecting different ways to release locally seismic energy. Finally, we come across an important issue that may lead to misleading results in similar studies, that is, if a seismic catalogue appears overall complete above a fixed magnitude threshold, it may still yield spurious signals into the analysis. Specifically, we show that some significant departures from the magnitude-independence assumption do not survive when considering spatiotemporal variations of the magnitude of completeness.Published820–8394T. Sismologia, geofisica e geologia per l'ingegneria sismicaJCR Journa
koamabayili/VECTRON-author-checklist: VECTRON author checklist
We have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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