1,720,975 research outputs found
Predicting reservoir water volumes in the Mediterranean area by combining a data-driven approach with seasonal forecasts data
Combining a data-driven approach with seasonal forecasts data to predicting reservoir water volume in the Mediterranean area.
Artificial reservoirs are one of the main water supply resources in the Mediterranean areas; their management can be strongly affected by the problems of drought and water scarcity. The reservoir water level is the result of the hydrological processes occurring in the upstream catchment, which, in turn, depend on meteorological variables, such as rainfall and temperature. It follows that a reliable forecast model of the meteorological forcing, along with a reliable water balance model, could enhance the correct management of a reservoir. With regard to the rainfall/temperature forecast model, the use of forecast climate data in the mid-term may provide further support for the future water level estimation of reservoirs.
From the perspective of the water balance model, instead, among the approaches used to predict the water levels for the next future, those based on data-driven methods have been demonstrated to be particularly capable of correctly reproducing the correlation between a dependent variable (e.g., water level, volume) and some covariates (e.g., temperature, precipitation).
This study describes the preliminary results of a novel application that exploits the Seasonal Forecast (SF) data, produced at the European Centre for Medium-Range Weather Forecasting (ECMWF), within a data-driven model aimed to predict the reservoir water volume at a mid-term scale, up to 6 months ahead in four reservoirs of the Sicily (Italy) here considered as a case study.
For each case, a NARX (Nonlinear AutoRegressive network with eXogenous inputs) neural network is calibrated to reproduce the monthly stored water volume starting from the monthly precipitation and mean monthly air temperature variables.
Preliminary results showed that the NARXs have the capability to reproduce the water levels in the investigated period (January 2017 - April 2020), including the variations during more or less dry periods. All this despite the SF data have not been previously treated with downscaling and/or bias correction techniques
Combining a data-driven approach with seasonal forecast data to predict reservoir water volume in the Mediterranean area
Prolonged droughts and water scarcity have become more frequent in recent years, exacerbating the problem of artificial reservoir management in the Mediterranean area. This study proposes a methodology that combines a Nonlinear AutoRegressive network with eXogenous input (NARX) data-driven model with seasonal forecast (SF) data, with the aim to predict the water volume stored in reservoirs at a mid-term scale, as requested by the local authority. The methodology is applied to four Sicilian reservoirs that experienced water scarcity in the recent past. SFs produced at the European Centre for Medium-Range Weather Forecasting are used to force the NARX models. Also, the reservoirs are in a typical data-scarce environment, where very few or no measurements at all are available. The results show that the NARXs have the capability to reproduce the volumes stored in the considered reservoirs for the investigated period up to four months in advance. The performance of the modelling system strictly depends on: (i) the quality of climate forecasts and (ii) the strength of the autocorrelation for the water volumes.</p
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
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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