1,720,984 research outputs found
IMPROVING PANDEMIC FORECASTS - ASSIMILATING OBSERVATIONS AND SIMULATIONS
Get PDFAt the height of the COVID-19 pandemic, an international team of mathematicians borrowed techniques from the geosciences to predict the complex and shifting dynamics of the virus’ spread. The technique known as data assimilation combines numerical model data with fresh observational
data to deliver more accurate forecasts. Validating the method in eight distinct countries, the team demonstrated the potential to reasonably and accurately predict the short-term impacts of
various reopening measures on virus transmission. This method can provide critical information to policymakers to make informed decisions and design effective policies to mitigate the pandemic’s impacts
Supervised machine learning to estimate instabilities in chaotic systems: estimation of local Lyapunov exponents
Get PDFIn chaotic dynamical systems such as the weather, prediction errors grow
faster in some situations than in others. Real-time knowledge about the error
growth could enable strategies to adjust the modelling and forecasting
infrastructure on-the-fly to increase accuracy or reduce computation time. One
could, e.g., change the ensemble size, or the distribution and type of target
observations. Local Lyapunov exponents are known indicators of the rate at
which very small prediction errors grow over a finite time interval. However,
their computation is very expensive: it requires maintaining and evolving a
tangent linear model, orthogonalisation algorithms and storing large matrices.
In this feasibility study, we investigate the accuracy of supervised machine
learning in estimating the current local Lyapunov exponents, from input of
current and recent time steps of the system trajectory, as an alternative to
the classical method. Thus machine learning is not used here to emulate a
physical model or some of its components, but non intrusively as a
complementary tool. We test four popular supervised learning algorithms:
regression trees, multilayer perceptrons, convolutional neural networks and
long short-term memory networks. Experiments are conducted on two
low-dimensional chaotic systems of ordinary differential equations, the
R\"ossler and the Lorenz 63 models. We find that on average the machine
learning algorithms predict the stable local Lyapunov exponent accurately, the
unstable exponent reasonably accurately, and the neutral exponent only somewhat
accurately. We show that greater prediction accuracy is associated with local
homogeneity of the local Lyapunov exponents on the system attractor.
Importantly, the situations in which (forecast) errors grow fastest are not
necessarily the same as those where it is more difficult to predict local
Lyapunov exponents with machine learning.Comment: 37 pages, 10 Figure
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe 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
Get PDF“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
Get PDFWe 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
Get PDFWe 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
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe 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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