1,721,025 research outputs found
Modelling study for forecasting gaseous pollutants levels in a urban area
No full textAtmospheric pollution is an important topic in environmental sciences. Nowadays the quality and the quantity of the data from air quality monitoring networks are significantly increased, but, for an effective management and assessment of this information, innovative data analysis methodologies have been developed. Approaches coming from advanced statistical methods were introduced in modeling and forecasting procedure to define operational techniques for atmospheric pollutants characterization at different scales. In this paper we present an application of artificial neural networks (ANN) for forecasting atmospheric gaseous pollutants. Starting from hourly data collected in Basilicata (southern Italy), from 1998 to 2007, we select the best dataset in terms of minimum data missing percentage. The applied model is a feed-forward multi-layer perceptron with an only hidden layer. The conjugate gradient learning algorithm is used. The learning capability of the model and the average goodness of the prediction are evaluated by Mean Absolute Percentage Error. The goal is to evaluate the performance the ANN model for forecasting 24-hourly data on the base of only the 24-hourly data collected in the previous day and to quantify the improvement obtained with different input strategies (optimal mix of pollutants defined by data correlation structure analysis). The preliminary results suggest that the dynamical characteristics of the gaseous pollutants may play a fundamental role in the definition of the forecasting procedure. Moreover, results confirm that the correlation structure analysis may be usefully applied for identifying the optimal strategy of data input selection. Nevertheless the quality of data represents the main limit of forecasting techniques at local scale
Sanguinamento uterino anomalo: etiopatogenesi, forme cliniche, flow-chart diagnostico-terapeutica.
No full textAn application of multivariate statistical techniques to partial equilibrium models outputs: The analysis of the NEEDS-TIMES Pan European model results
No full textIperomocisteinemia e gravidanza: inquadramento eziopatogenetico e prospettive terapeutiche
No full textDEA, balanced scorecard and intellectual capital including the gender dimension: A comprehensive list of indicators
Full text linkOne of the most significant problems in the development of quantitative models to assess the performance of decision-making units (DMUs) is the availability of information coded into variables and indicators that are proxies for the relevant dimensions of the models: resources or inputs, products or services or outputs, and heterogeneous contextual factors including environmental factors. Data envelopment analysis (DEA) and balanced scorecard (BSC) are two of the best-known and applied tools to model and measure the performance of DMUs. Within the information set requested to model the performance, the most critical and sensitive variables and indicators related to the intangible capital of organizations, which includes with a primary role the intellectual capital (IC). Although they are very different, DEA (based on linear programming) and BSC (including a set of indicators along four dimensions) have recently been combined to try to address the problem indicated earlier, namely, having a set of variables and indicators available to better measure the performance of DMUs. We apply a three-level methodology combining (i) a series of systematic reviews, (ii) a bibliometric analysis of all the published works found, and (iii) an analysis of the so-called grey literature contained in the reports of knowledge-based organizations. The main results obtained are (1) a comprehensive survey and mapping of all scientific works combining DEA, BSC, and IC including the gender dimension; (2) an integral and inclusive list integrating all indicators found in both published works and reports, reclassified according to the main dimensions of the IC
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
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
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