1,720,958 research outputs found
Support vector machine classification on a biased training set: Multi-jet background rejection at hadron colliders
No full textThis paper describes an innovative way to optimize a multivariate classifier, a Support Vector Machine algorithm, on a problem characterized by a biased training sample. This is possible thanks to the feedback of a signal-background template fit performed on a validation sample and included both in the optimization process and in the input variable selection. The procedure is applied to a real case of interest at hadron collider experiments: the reduction and the estimate of the multi-jet background in the W→eν plus jets data sample collected by the CDF experiment. The training samples, partially derived from data and partially from simulation, are described in detail together with the input variables exploited for the classification. At present, the reached performance is better than any other prescription applied to the same final state at hadron collider experiments. © 2013 Elsevier B.V
Rejection of multi-jet background in pp̄ → eν + jj̄ channel through a SVM classifier
No full textWe test and optimize a multivariate discriminant software package, based on the Support Vector Machine (SVM) algorithm, to reduce the multi-jet background events in the channel pp̄ → eν + jj̄. We use the CDFII data-set, collected at the TeVatron pp̄ ollider, where this channel provides the signature for many important physics processes: e.g. associated Higgs production, WZ, single top events. The Multi-jet background can be large and difficult to reject but, in this paper, we show that an appropriatly trained SVM can handle it in an effective way. The developed programs perform training set selection, efficiency maximization and consistency checks; we also discuss the robustness of the discriminant. A classification accuracy ≥ 95% can be reached using Monte Carlo simulated signal and a data-driven background model (limited by statistic) with a background rejection of ∼90%
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
Identification of gait phases with neural networks for smooth transparent control of a lower limb exoskeleton
Full text linkLower limbs exoskeletons provide assistance during standing, squatting, and walking. Gait dynamics, in particular, implies a change in the configuration of the device in terms of contact points, actuation, and system dynamics in general. In order to provide a comfortable experience and maximize performance, the exoskeleton should be controlled smoothly and in a transparent way, which means respectively, minimizing the interaction forces with the user and jerky behavior due to transitions between different configurations. A previous study showed that a smooth control of the exoskeleton can be achieved using a gait phase segmentation based on joint kinematics. Such a segmentation system can be implemented as linear regression and should be personalized for the user after a calibration procedure. In this work, a nonlinear segmentation function based on neural networks is implemented and compared with linear regression. An on-line implementation is then proposed and tested with a subject
Rejection of multi-jet background in a hadron collider environment through a SVM classifier
No full textWe optimized a multivariate discriminant software package, based on the Support Vector Machine (SVM) algorithm, to reduce the multi-jet background events in the channel pp̄ → ev + jj̄. This channel is important for many physics searches but the multi-jet background can be large and it is difficult to model. We developed a package which allows training set selection, maximization of efficiency and consistency checks. In this paper we will show how the multivariate approach we presented proved to be more efficient compared to the state of art approaches, both in terms of classification accuracy and background contamination. © 2011 IEEE
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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