1,720,958 research outputs found
Prédiction/classification de la qualité d'un système de production sous incertitudes par la méthode des machines à vecteurs supports (SVM)
No full textWith the emergence of the IoT paradigm, manufacturing industries are opting for new technologies for data collection and analysis to evaluate the quality of their manufacturing systems. Machine learning and classification methods provide various solutions to quality management such as defect detection and conformity prediction. However, manufacturing data are affected by uncertainties, which affect the performances of classification techniques. Accordingly, the thesis aims to study and manage the impact of measurement uncertainties on the predictive performances of support vector machine (SVM). Two groups of approaches are thus proposed: the former aiming to quantify the impact of measurement uncertainties on the prediction accuracy of SVM using several propagation techniques and data mining techniques, and the latter aiming to improve the robustness of SVM to uncertainties using robust optimization techniques. The various approaches provide a better understanding of the SVM robustness and how to improve it. The proposed approaches are evaluated through case studies with industrial partners.Avec l'émergence des techniques d’IoT, les industries manufacturières adoptent de nouvelles technologies d'analyse de données afin d’améliorer la qualité de leurs systèmes de production. Les méthodes de classification offrent diverses solutions aux problèmes de management de la qualité, comme la détection des défauts et la prédiction de la conformité. Cependant, les données de production sont entachées d’incertitudes qui affectent les performances de ces méthodes. Ces travaux visent à étudier l'impact des incertitudes de mesure sur les performances des machines à vecteurs supports (SVM). Deux groupes d'approches sont proposés, le premier visant à quantifier l'impact des incertitudes de mesure sur la précision de prédiction des SVM via des techniques de propagation d’incertitudes et d’analyse de données, et le second visant à améliorer la robustesse de la SVM via des approches d’optimisation robuste intrusives et non intrusives. Les différentes approches permettent de mieux appréhender la robustesse de la SVM et la manière de l'améliorer. Ces approches proposées ont été évaluées à l'aide d'études de cas avec des partenaires industriels
Prédiction/classification de la qualité d'un système de production sous incertitudes par la méthode des machines à vecteurs supports (SVM)
No full textWith the emergence of the IoT paradigm, manufacturing industries are opting for new technologies for data collection and analysis to evaluate the quality of their manufacturing systems. Machine learning and classification methods provide various solutions to quality management such as defect detection and conformity prediction. However, manufacturing data are affected by uncertainties, which affect the performances of classification techniques. Accordingly, the thesis aims to study and manage the impact of measurement uncertainties on the predictive performances of support vector machine (SVM). Two groups of approaches are thus proposed: the former aiming to quantify the impact of measurement uncertainties on the prediction accuracy of SVM using several propagation techniques and data mining techniques, and the latter aiming to improve the robustness of SVM to uncertainties using robust optimization techniques. The various approaches provide a better understanding of the SVM robustness and how to improve it. The proposed approaches are evaluated through case studies with industrial partners.Avec l'émergence des techniques d’IoT, les industries manufacturières adoptent de nouvelles technologies d'analyse de données afin d’améliorer la qualité de leurs systèmes de production. Les méthodes de classification offrent diverses solutions aux problèmes de management de la qualité, comme la détection des défauts et la prédiction de la conformité. Cependant, les données de production sont entachées d’incertitudes qui affectent les performances de ces méthodes. Ces travaux visent à étudier l'impact des incertitudes de mesure sur les performances des machines à vecteurs supports (SVM). Deux groupes d'approches sont proposés, le premier visant à quantifier l'impact des incertitudes de mesure sur la précision de prédiction des SVM via des techniques de propagation d’incertitudes et d’analyse de données, et le second visant à améliorer la robustesse de la SVM via des approches d’optimisation robuste intrusives et non intrusives. Les différentes approches permettent de mieux appréhender la robustesse de la SVM et la manière de l'améliorer. Ces approches proposées ont été évaluées à l'aide d'études de cas avec des partenaires industriels
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe 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
Get PDF“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
Get PDFWe 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
Get PDFWe 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
No full textWe 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
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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