1,720,974 research outputs found
Comparison of self-organizing maps classification approach with cluster and principal components analysis for large environmental data sets
No full textThree classification techniques (loading and score projections based on principal components analysis (PCA), cluster analysis (CA) and self-organizing maps (SOM)) were
applied to a large environmental data set of chemical indicators of river water quality. The study was carried out by using long-term water quality monitoring data. The advantages of SOM algorithm and its classification and visualization ability for large environmental data sets are stressed. The results obtained allowed detecting natural clusters of monitoring locations with similar water quality type and identifying important discriminant variables
responsible for the clustering. SOM clustering allows simultaneous observation of both spatial and temporal changes in water quality. The chemometric approach revealed different patterns of monitoring sites conditionally named ‘‘tributary’’, ‘‘urban’’, ‘‘rural’’ or ‘‘background’’. This objective separation could lead to an optimization of river monitoring nets and to a better tracing natural and anthropogenic changes along the river stream
Self-organizing map algorithm for assessing spatial and temporal patterns of pollutants in environmental compartments: A review
Full text linkThe evaluation of the spatial and temporal distribution of pollutants is a crucial issue to assess the anthropogenic burden on the environment. Numerous chemometric approaches are available for data exploration and they have been
applied for environmental health assessment purposes. Among the unsupervised methods, Self-Organizing Map
(SOM) is an artificial neural network able to handle non-linear problems that can be used for exploratory data analysis,
pattern recognition, and variable relationship assessment. Much more interpretation ability is gained when the SOMbased model is merged with clustering algorithms. This review comprises: (i) a description of the algorithm operation
principle with a focus on the key parameters used for the SOM initialization; (ii) a description of the SOM output features and how they can be used for data mining; (iii) a list of available software tools for performing calculations; (iv)
an overview of the SOM application for obtaining spatial and temporal pollution patterns in the environmental compartments with focus on model training and result visualization; (v) advice on reporting SOM model details in a pape
Disentangling Multiannual Air Quality Profiles Aided by Self-Organizing Map and Positive Matrix Factorization
Full text linkThe evaluation of air pollution is a critical concern due to its potential severe impacts on human health. Currently, vast quantities of data are collected at high frequencies, and researchers must navigate multiannual, multisite datasets trying to identify possible pollutant sources while addressing the presence of noise and sparse missing data. To address this challenge, multivariate data analysis is widely used with an increasing interest in neural networks and deep learning networks along with well-established chemometrics methods and receptor models. Here, we report a combined approach involving the Self-Organizing Map (SOM) algorithm, Hierarchical Clustering Analysis (HCA), and Positive Matrix Factorization (PMF) to disentangle multiannual, multisite data in a single elaboration without previously separating the sites and years. The approach proved to be valid, allowing us to detect the site peculiarities in terms of pollutant sources, the variation in pollutant profiles during years and the outliers, affording a reliable interpretation
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
Extracting knowledge from hybrid instrumental environmental odour monitoring systems: Self organizing maps, data fusion and supervised kohonen networks for prediction
No full textHigh frequency multi-sensor patterns for instrumental odor monitoring in urban areas close to industrial districts requires adequate analytical strategies, hardware and effective data analysis and control procedures. An approach linking data analysis tools is presented based on unsupervised identification of recurrent patterns from data produced by hybrid instrumental odour monitoring systems. A self-organizing map is built and clustered in order to identify air typologies at a e-nose site; they are interpreted thanks to data fusion of sensorial data from citizen complaints, olfactometric measures, air pollutants and meteorological data. A supervised Kohonen network generates quantitative relationships between multisensor patterns and sparse olfatometric measures on air samples timely collected after complaints or instrumental threshold exceedance, allowing high frequency estimates of odour concentrations
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
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe 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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