1,721,057 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
Contribution of textural analysis from high spatial resolution radar images for tropical forest mapping
No full textDepuis 2007, une nouvelle génération de capteurs RSO (RADAR à Synthèse d'Ouverture) a été mise en orbite. Ces capteurs (TerraSAR-X, Cosmo-SkyMed, RADARSAT-2, Sentinel) sont caractérisés par des résolutions spatiales métriques à la différence des capteurs précédents (ERS, JERS, ALOS, ASAR) de résolution spatiale d'une vingtaine de mètres. La résolution spatiale métrique met en évidence une information texturale intéressante qui était inaccessible avec les RSO satellitaires existants précédemment. Les travaux de cette thèse ont pour but d'évaluer le potentiel de l'analyse texturale des images RADAR à haute résolution spatiale, pour la classification des forêts tropicales. Trois différents sites d'étude avec différentes problématiques ont été choisis pour évaluer l'apport de l'analyse texturale au Cambodge, Cameroun et Brésil. La méthode d'analyse texturale des images est réalisé moyennant les paramètres de texture de Haralick, paramètres statistique de second ordre. Une classification supervisée, en utilisant la méthode SVM (Support Vector Machine) a été adopté pour évaluer l'apport des paramètres de texture utilisésSince 2007, a new generation of SAR sensors (Synthetic Aperture RADAR) was launched. These sensors (TerraSAR-X, Cosmo-SkyMed, RADARSAT-2, and Sentinel) are characterized by metric spatial resolutions unlike previous sensors (ERS, JERS, ALOS, ASAR) with a spatial resolution of about twenty meters. Metric spatial resolution highlights interesting textural information that was inaccessible with the previously existing SAR sensors. This thesis aims at evaluating the contribution of textural analysis from high spatial resolution images for tropical forests mapping. Three different study sites with different problematic have been chosen to evaluate the textural analysis in Cambodia, Cameroun and Brazil. Indeed, the contribution of the analysis of textural information for classification has been emphasized. The latter is understood through the analysis of Haralick textural parameters, second order statistic parameters. The retained algorithm of classification is the SVM (Support Vector Machine), as it allows taking into account numerous parameters, which can be heterogeneous with respect to their physical dimensio
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
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
Contribution of Sentinel-1 data for the continuous monitoring of the tropical forest : Case of French Guiana
No full textLes forêts tropicales abritent la biodiversité la plus riche de notre planète et jouent un rôle particulièrement important dans le stockage du carbone et le cycle de l’eau. Le suivi de la dégradation de ce milieu est un défi d’actualité car il représente un danger immédiat pour l’environnement et la biodiversité. Par ailleurs, depuis 2014, la mise en orbite des satellites Sentinel dans le cadre du programme européen Copernicus constitue une réelle révolution dans le panorama des capteurs d’observation de la Terre existants jusqu’alors. En effet, des données optiques (Sentinel-2) et radar (Sentinel-1) sont, depuis lors, accessibles librement à tous et permettent des acquisitions à une résolution décamétrique et une répétitivité allant de 5 à 12 jours selon la région analysée. L’objectif de cette thèse consiste donc à développer des méthodes pour le suivi de la forêt tropicale basées sur des données radar Sentinel-1 et des produits de cartographie exogènes. Plus spécifiquement, l’étude a pour but de fournir des outils pour observer le déboisement, en produisant des cartes en quasi-temps réel, puis en caractérisant les zones détectées avec la cause de leur déboisement. Ces informations sont nécessaires à l’estimation et au suivi du déboisement sur les zones tropicales, et à la lutte contre les défriches illicites.La région test est la Guyane. Couverte à plus de 95% par la forêt, elle est caractérisée par de nombreux types de perte forestière permettant de valider la méthode sur de nombreuses caractéristiques. De plus, ce territoire étant relativement bien surveillé, beaucoup de données cartographiques d’occupation du sol sont disponibles pour situer les déboisements ou pour servir de référence au niveau spatial. La première phase du travail est l’amélioration d’une méthode de détection du déboisement à partir des données Sentinel-1 et son évaluation sur la Guyane. La validation de la carte produite s’appuie sur 1 867 données (de différents types de déboisement) produites de manière indépendante, et représentant un total de 2 124.5 ha à travers toute la Guyane sur une période de 2 ans. Les résultats obtenus sur la Guyane au niveau spatial sont très satisfaisants : 96% de précision sur les surfaces déboisées et 81.5% de rappel. La mise en place d’une campagne terrain a rendu possible l’estimation du côté quasi-temps réel de la méthode sur 26 parcelles et avance un délai médian de détection de 3.5 jours. Une comparaison avec un produit optique souvent pris comme référence, a démontré l’avantage des données Sentinel-1 pour ces régions caractérisées par de fortes couvertures nuageuses. Cette meilleure performance s’observe tant sur le plan spatial (rappel du radar supérieur de plus de 35%), que sur le plan temporel (un tiers des zones déboisées nécessitant une surveillance est détecté avec 3 mois de retard par les images optiques). La deuxième partie du travail consiste à caractériser les zones déboisées détectées afin de déterminer leur cause. Pour cela, des méthodes d’apprentissage automatique ont été utilisées pour choisir des indicateurs cartographiques pertinents, permettant de produire un modèle prédictif simple, fiable, automatique et utilisable à l’échelle de la Guyane en temps-réel. Les indicateurs F-scores de chaque type de déboisement sont de 97% pour l’orpaillage et l’agriculture, 95% pour l’exploitation forestière, 87% pour l’urbanisation et 76% pour la classe « autre », pouvant se rapporter à des perturbations naturelles. Ce travail a montré la pertinence d’utiliser des indicateurs cartographiques pour déterminer la cause des déboisements en Guyane, permettant cette identification en temps-réel. Ces travaux qui démontrent le potentiel des données Sentinel-1 pour le suivi continu des forêts tropicales ont été menés en interaction avec les acteurs locaux. Ils montrent également la complémentarité de systèmes provenant de capteurs différents et pourront être poursuivis en ce sensTropical forests are home to the richest biodiversity on our planet and play a particularly important role in carbon storage and the water cycle. Monitoring the degradation of this environment is currently a challenge because it represents an immediate danger for the environment and biodiversity. Moreover, since 2014, the launch of the Sentinel satellites within the framework of the European Copernicus program constitutes a real revolution in the panorama of Earth observation sensors existing until then. Indeed, optical (Sentinel-2) and radar (Sentinel-1) data are, since then, freely accessible to all and allow acquisitions with a decametric resolution and a repeatability ranging from 5 to 12 days depending on the region analyzed. The objective of this thesis is to develop methods to monitor the tropical forest based on Sentinel-1 radar data and exogenous mapping products. More specifically, the study aims to provide tools to observe deforestation, by producing maps in near-real time, and then characterizing the detected areas with the driver of their deforestation. This information is needed to estimate and monitor deforestation in tropical areas, and to fight against illegal deforestation. The study site is French Guiana. With 95% forest coverage, it is characterized by many types of forest loss allowing the method to be validated on multiple characteristics. Moreover, as this area is already relatively well monitored, a lot of cartographic data is also available in order to locate forest loss or to be a reference at the spatial level.The first phase of the work is the improvement of a deforestation detection method from Sentinel-1 data and its evaluation over French Guiana. The validation of the map produced is based on 1 867 data (of different types of deforestation) produced from distinct organizations, and representing a total of 2 124.5 ha throughout French Guiana over a period of 2 years.The results obtained in French Guiana at the spatial level are very satisfactory: 96% accuracy in detecting deforested areas and 81.5% producer’s accuracy. The implementation of a field campaign has made it possible to estimate the quasi-real time side of the method on 26 plots and gives a median detection time of 3.5 days. A comparison with an optical product often taken as a reference, demonstrated the advantage of Sentinel-1 data in those regions characterized by high cloud cover. This best performance is observed both spatially (radar recall higher than 35%), and temporally (one third of the areas deforested requiring monitoring are detected within a 3-month delay by optical images).The second part of the work consists in characterizing the detected deforested areas in order to determine their cause. For this, machine learning methods were used to select relevant cartographic indicators, allowing to produce a simple, reliable, automatic and usable predictive model at French Guiana’s scale in real time.The F-scores for each type of deforestation are 97% for gold panning and agriculture, 95% for logging, 87% for urbanization, and 76% for the "other" class, which may refer to natural disturbances. This work has shown the relevance of using cartographic indicators to determine the drivers of deforestation in French Guiana, allowing this identification in real time. This work, which demonstrates the potential of Sentinel-1 data for continuous monitoring of tropical forests, was conducted in interaction with local stakeholders. They also show the complementariness of systems from different sensors and efforts can be continued in that regar
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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