1,721,220 research outputs found
Going Beyond Counting First Authors in Author Co-citation Analysis
The 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
“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
We 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
We 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
Scalable multi-dimensional resources scheduling constraints
La programmation par contraintes est une approche régulièrement utilisée pour résoudre des problèmes combinatoires d’origines diverses. Dans cette thèse nous nous focalisons sur les problèmes d’ordonnancement cumulatif. Un problème d’ordonnancement consiste à déterminer les dates de débuts et de fins d’un ensemble de tâches, tout en respectant certaines contraintes de capacité et de précédence. Les contraintes de capacité concernent aussi bien des contraintes cumulatives classiques où l’on restreint la somme des hauteurs des tâches intersectant un instant donné, que des contraintes cumulatives colorées où l’on restreint le nombre maximum de couleurs distinctes prises par les tâches. Un des objectifs récemment identifiés pour la programmation par contraintes est de traiter des problèmes de grandes tailles, habituellement résolus à l’aide d’algorithmes dédiés et de métaheuristiques. Par exemple, l’utilisation croissante de centres de données virtualisés laisse apparaitre des problèmes d’ordonnancement et de placement multi-dimensionnels de plusieurs milliers de tâches. Pour atteindre cet objectif, nous utilisons l’idée de balayage synchronisé considérant simultanément une conjonction de contraintes cumulative et des précédences, ce qui nous permet d’accélérer la convergence au point fixe. De plus, de ces algorithmes de filtrage nous dérivons des procédures gloutonnes qui peuvent être appelées à chaque nœud de l’arbre de recherche pour tenter de trouver plus rapidement une solution au problème. Cette approche permet de traiter des problèmes impliquant plus d’un million de tâches et 64 ressources cumulatives. Ces algorithmes ont été implémentés dans les solveurs de contraintes Choco et SICStus, et évalués sur divers problèmes déplacement et d’ordonnancement.Constraint programming is an approach often used to solve combinatorial problems in different application areas. In this thesis we focus on the cumulative scheduling problems. A scheduling problem is to determine the starting dates of a set of tasks while respecting capacity and precedence constraints. Capacity constraints affect both conventional cumulative constraints where the sum of the heights of tasks intersecting a given time point is limited, and colored cumulative constraints where the number of distinct colors assigned to the tasks intersecting a given time point is limited. A newly identified challenge for constraint programming is to deal with large problems, usually solved by dedicated algorithms and metaheuristics. For example, the increasing use of virtualized datacenters leads to multi dimensional placement problems of thousand of jobs. Scalability is achieved by using a synchronized sweep algorithm over the different cumulative and precedence constraints that allows to speed up convergence to the fix point. In addition, from these filtering algorithms we derive greedy procedures that can be called at each node of the search tree to find a solution more quickly. This approach allows to deal with scheduling problems involving more than one million jobs and 64 cumulative resources. These algorithms have been implemented within Choco and SICStussolvers and evaluated on a variety of placement and scheduling problems
koamabayili/VECTRON-author-checklist: VECTRON author checklist
We 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.
Author-wise bibliometric analysis based on entropy.</p
Cumulative scheduling in constraint programming : energetic characterization of reasoning and robust solutions
La programmation par contraintes est une approche régulièrement utilisée pour traiter des problèmes d’ordonnancement variés. Les problèmes d’ordonnancement cumulatifs représentent une classe de problèmes dans laquelle des tâches non morcelable peuvent être effectuées en parallèle. Ces problèmes apparaissent dans de nombreux contextes réels, tels que par exemple l’allocation de machines virtuelles ou l’ordonnancement de processus dans le "cloud", la gestion de personnel ou encore d’un port. De nombreux mécanismes ont été adaptés et proposés en programmation par contraintes pour résoudre les problèmes d’ordonnancement. Les différentes adaptations ont abouti à des raisonnements qui semblent à priori significativement distincts. Dans cette thèse nous avons effectué une analyse détaillée des différents raisonnements, proposant à la fois une notation unifiée purement théorique mais aussi des règles de dominance, permettant une amélioration significative du temps d’exécution d’algorithmes issus de l’état de l’art, pouvant aller jusqu’à un facteur sept. Nous proposons aussi un nouveau cadre de travail pour l’ordonnancement cumulatif robuste, permettant de trouver des solutions supportant qu’à tout moment une ou plusieurs tâches soit retardées, sans remise en cause de l’ordonnancement généré et en gardant une date de fin de projet satisfaisante. Dans ce cadre, nous proposons une adaptation d’un algorithme de l’état de l’art, Dynamic Sweep.Constraint programming is an approach regularly used to treat a variety of scheduling problems. Cumulative scheduling problems represent a class of problems in which non-preemptive tasks can be performed in parallel. These problems appear in many contexts, such as for example the allocation of virtual machines, the ordering process in the "cloud", personnel management or a port. Many mechanisms have been adapted and offered in constraint programming to solve scheduling problems. The various adaptations have resulted in reasoning that appear a priori significantly different. In this thesis we performed a detailed analysis of the various arguments, offering both a theoretical unified caracterization but also dominance rules, allowing a significant improvement in execution time of algorithms from the state of the art, up to a factor of seven. we also propose a new framework for robust cumulative scheduling, to find solutions that support at any time one or more tasks to be delayed while keeping a satisfactory end date of the project and without calling into question the generated scheduling. In this context, we propose an adaptation of an algorithm of the state of the art, Dynamic Sweep
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