1,721,078 research outputs found
Application of mixture models to large datasets
No full textMixture distributions are commonly being applied for modelling and for discriminant and cluster analyses in a wide variety of situations. We first consider normal and t-mixture models. As they are highly parameterized, we review methods to enable them to be fitted to large datasets involving many observations and variables. Attention is then given to extensions of these mixture models to mixtures with skew normal and skew t-distributions for the segmentation of data into clusters of non-elliptical shape. The focus is then on the latter models in conjunction with the JCM (joint clustering and matching) procedure for an automated approach to the clustering of cells in a sample in flow cytometry where a large number of cells and their associated markers have been measured. For a class of multiple samples, we consider the use of JCM for matching the sample-specific clusters across the samples in the class and for improving the clustering of each individual sample. The supervised classification of a sample is also considered in the case where there are different classes of samples corresponding, for example, to different outcomes or treatment strategies for patients undergoing medical screening or treatment
HiPC 2016 Workshop 1: International Workshop on Foundations of Big Data Computing (BigDF)
No full textNoncommunicable disease modeling and simulation as means of understanding childhood obesity and intervention effectiveness
No full textLifestyle and dietary changes have led to rise in noncommunicable diseases such as diabetes, obesity, and cardiovascular disorders, accounting for increased mortality and morbidity in many parts of the world including developing countries. Obesity has doubled since 1980s and continues to be a growing problem of our times. Public health policies to address obesity are evolving in connection with dynamically changing human behaviors and complex interactions with the environment. However, designing and testing of new interventions are expensive and time-consuming. Computational simulations to model interventions offer useful tools to compare the effectiveness of potential interventions. In this article, we discuss a popular computational approach, agent-based modeling (ABM), to address the global challenge of childhood obesity through modeling of different interventions as described in the literature
Noncommunicable disease modeling and simulation as means of understanding childhood obesity and intervention effectiveness
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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
A distributed framework for supporting adaptive ensemble-based intrusion detection
No full textThis paper proposes anatomy and main functionalities of a distributed framework for supporting adaptive ensemble-based intrusion detection. We start from open issues and limitations of actual state-of-the-art proposals, and we derive a suitable architecture that, based on actual, emerging research trends, finally defines an innovative ensemble-based network intrusion detection system that combines following requirements: distribution, cooperativeness, scalability, multi-scale network traffic analysis, feature selection and extraction. These requirements are recognized by our study as first-class research challenges for next-generation intrusion detection systems
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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