1,721,046 research outputs found
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
Étude d'algorithmes d'apprentissage artificiel pour la prédiction de la syncope chez l'homme
No full textSyncope is considered as a common pathology, although sometimes its cause cannot be clearly diagnosed. In this case and when syncope is frequently experienced, the patient can have a head-upright tilt test. This examination is based on the reproduction of symptoms of the syncope ; however, its major drawback is the duration of the examination, which can take up to one hour. Therefore, reducing the examination time would decrease its cost and improve the comfort of the patient. This is the challenge of this thesis, which tries to predict the appearance of the symptoms of the syncope before the end of the tilt test. During the research, two areas of study became important : data mining and development of models used to predict the tilt-test result. Both areas use algorithms coming from machine learning, enabling the acquisition and extraction of relevant knowledge on data sets. Published works give many methods, which have enabled the extraction of some pertinent characteristics. With these, robust and ecient models have been constructed, which have enabled the prediction of the tilt-test results in the rst ten minutes of the examination. Also, the performance has been improved by the development of new techniques of data mining, enabling more ecient analysis of data. These methods have been used for the selection of the variables and for the interpretation of the non-linear projection techniques. Even though these methods have been developed for this research, they have shown interesting performances during tests on other data sets.La syncope, dont l'origine peut ne pas être clairement définie, est considérée comme une pathologie fréquente. Dans ce cas et lorsque les épisodes sont répétés, le patient peut être amené à réaliser le test de la table d'inclinaison. Cet examen appelé tilt-test, est une méthode reconnue pour recréer les conditions dans lesquelles le patient ressent les symptômes de la syncope. Cependant, le principal problème de ce test est sa durée, qui peut atteindre une heure. Dès lors, pour des raisons de coût et de bien-être des patients, il paraît important de pouvoir réduire sa durée. C'est dans cet objectif que s'inscrivent les travaux réalisés dans le cadre de cette thèse, qui tentent de prédire l'apparition des symptômes liés à la syncope, et ce, le plus tôt possible. Durant nos recherches, deux axes sont ressortis naturellement : la fouille de données et le dé- veloppement de modèles capables de prédire le résultat du tilt-test. Ces deux axes partagent des méthodes issues de l'apprentissage articiel, qui permettent d'acquérir et d'extraire des connaissances à partir d'un ensemble d'observations signicatif. La littérature propose tout un ensemble de méthodes, qui nous ont permis de mettre en évidence certaines caractéristiques pertinentes, de manière à construire des modèles parcimonieux et robustes. Ces derniers ont permis d'obtenir des résultats intéressants pour la prédiction du résultat du tilt-test au terme notamment, des dix premières minutes de l'examen. Ces performances ont pu être considérablement améliorées par le développement de nouvelles techniques de fouille de données, permettant d'extraire très e- cacement de la connaissance. Les méthodes mises en place s'articulent autour de la sélection de variables et de l'interprétation de projections non linéaires. Ces méthodes, bien que développées autour de notre thématique, se sont montrées reproductibles lors de tests sur d'autres ensembles de données
Étude d'algorithmes d'apprentissage artificiel pour la prédiction de la syncope chez l'homme
No full textSyncope is considered as a common pathology, although sometimes its cause cannot be clearly diagnosed. In this case and when syncope is frequently experienced, the patient can have a head-upright tilt test. This examination is based on the reproduction of symptoms of the syncope ; however, its major drawback is the duration of the examination, which can take up to one hour. Therefore, reducing the examination time would decrease its cost and improve the comfort of the patient. This is the challenge of this thesis, which tries to predict the appearance of the symptoms of the syncope before the end of the tilt test. During the research, two areas of study became important : data mining and development of models used to predict the tilt-test result. Both areas use algorithms coming from machine learning, enabling the acquisition and extraction of relevant knowledge on data sets. Published works give many methods, which have enabled the extraction of some pertinent characteristics. With these, robust and ecient models have been constructed, which have enabled the prediction of the tilt-test results in the rst ten minutes of the examination. Also, the performance has been improved by the development of new techniques of data mining, enabling more ecient analysis of data. These methods have been used for the selection of the variables and for the interpretation of the non-linear projection techniques. Even though these methods have been developed for this research, they have shown interesting performances during tests on other data sets.La syncope, dont l'origine peut ne pas être clairement définie, est considérée comme une pathologie fréquente. Dans ce cas et lorsque les épisodes sont répétés, le patient peut être amené à réaliser le test de la table d'inclinaison. Cet examen appelé tilt-test, est une méthode reconnue pour recréer les conditions dans lesquelles le patient ressent les symptômes de la syncope. Cependant, le principal problème de ce test est sa durée, qui peut atteindre une heure. Dès lors, pour des raisons de coût et de bien-être des patients, il paraît important de pouvoir réduire sa durée. C'est dans cet objectif que s'inscrivent les travaux réalisés dans le cadre de cette thèse, qui tentent de prédire l'apparition des symptômes liés à la syncope, et ce, le plus tôt possible. Durant nos recherches, deux axes sont ressortis naturellement : la fouille de données et le dé- veloppement de modèles capables de prédire le résultat du tilt-test. Ces deux axes partagent des méthodes issues de l'apprentissage articiel, qui permettent d'acquérir et d'extraire des connaissances à partir d'un ensemble d'observations signicatif. La littérature propose tout un ensemble de méthodes, qui nous ont permis de mettre en évidence certaines caractéristiques pertinentes, de manière à construire des modèles parcimonieux et robustes. Ces derniers ont permis d'obtenir des résultats intéressants pour la prédiction du résultat du tilt-test au terme notamment, des dix premières minutes de l'examen. Ces performances ont pu être considérablement améliorées par le développement de nouvelles techniques de fouille de données, permettant d'extraire très e- cacement de la connaissance. Les méthodes mises en place s'articulent autour de la sélection de variables et de l'interprétation de projections non linéaires. Ces méthodes, bien que développées autour de notre thématique, se sont montrées reproductibles lors de tests sur d'autres ensembles de données
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
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
Development of multi-channel opto-mechanical seismometers, connected to plurikilometric fiber, for academic and industrial real-time applications
No full textLa recherche académique et la surveillance de zones présentant des aléas telluriques élevés nécessitent la mise en œuvre d’une instrumentation sismologique pouvant présenter certains facteurs limitants, tant en termes de couts que de facilité de déploiement. Ainsi, les fortes contraintes environnementales inhérentes à certaines zones géographiques, comme les édifices volcaniques (température, acidité, foudre), les forages profonds, ou les fonds marins, ne permettent pas toujours l’installation de matériel de mesure et la surveillance en temps réel de zones actives sur le long terme. Le projet LINES (ANR RiskNat – 2009-2012) a permis le développement d’un capteur de déplacement à fibre optique appliqué à la sismologie. Ce dernier, basé sur un interféromètre de Fabry-Pérot extrinsèque a permis d’envisager l’émergence de nouveaux sismomètres plus robustes et moins coûteux, tout en leur garantissant de bonnes performances métrologiques.Les travaux présentés dans cette thèse s’inscrivent dans la continuité de ce premier projet. Intégrés à l’ANR HIPERSIS (2017-2019), ils visent à (i) proposer un modèle du système de mesure optoélectronique, afin d’évaluer ses performances en termes de niveaux de bruits, de linéarité, de bande passante notamment, et l’impact des conditions environnementales sur son comportement, à (ii) concevoir, modéliser et réaliser un géophone adapté au système de mesure optique, et conforme aux attendus du projet HIPERSIS et à (iii) installer et qualifier l’ensemble du système sur un site d’intérêt : la Grande Soufrière de Guadeloupe. Un premier bilan quant à l’apport de ce sismomètre à l’étude de la microsismicité du volcan sera dressé. Les résultats de cette étude pourraient notamment encourager le déploiement en réseau de ce type de capteur sur d’autres sites d’intérêt – naturels ou industriels (géoindustries ou génie civil), ainsi que la diversification des structures mécaniques associées à l’interrogateur optique (hydrophone, inclinomètre).Academic research and monitoring of areas with high telluric hazards require number of seismic equipment that may present some limitations. Indeed, the cost of these systems can be high, and their deployment is sometimes very challenging. Thus, the harsh environment inherent to some geographical areas, such as volcanic edifices (temperature, acidity and lightning), deep boreholes, or seabed, do not always allow the installation of measurement devices and prevent the real-time monitoring of active areas on the long run. A fiber optic displacement sensor applied to seismology, based on an extrinsic Fabry-Perot interferometer, was proposed at the end of the LINES project (RiskNat ANR – 2009-2012). This work aimed to enhance the robustness and reduce the cost of new seismometers, while maintaining good metrological performances.The work presented in this thesis, part of the ANR HIPERSIS project (2017-2019), aims to (i) model the opto-electronic measurement system, in order to evaluate its performances (especially noise level, linearity, bandwidth), and the impact of the environmental conditions on its behavior, (ii) to design, model and engineer a geophone suitable for the optical measurement system, and compliant with the specifications of the HIPERSIS project, and (iii) to install and characterize the whole system on a site of interest : La Grande Soufrière Volcano, Guadeloupe. We will conduct a first assessment of the contribution of this seismometer to the study of the volcano microseismicity. The results of this study might open promising perspectives for monitoring networks in harsh environments: natural or industrial environment (geoindustries or civil engineering), as well as the diversification of mechanical structures associated with the optical interrogator (hydrophone, inclinometer, etc.)
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