1,721,141 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
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
Diagnostic based on vibration signal analysis of rotating machine under variable regime
No full textDepuis une dizaine d'années, plusieurs méthodes de traitement du signal vibratoire ont été développées pour le diagnostic des machines tournantes en régime stationnaire. Or, de plus en plus de machines sous surveillance fonctionnent en régime variable telles que les éoliennes, les concasseurs, etc... Les méthodes développées pour la surveillance et le diagnostic de ces machines en régime stationnaire ne sont plus adaptées en régime variable. Certains outils proposés pour le régime variable sont limités à des applications bien spécifiques ou offrent un cadre théorique qui limite leur utilisation dans les situations réelles. Le but de cette thèse est justement de pallier ces limitations, et ce, en proposant une nouvelle approche permettant d'analyser les signaux vibratoires acquis en régime variable. La stratégie mise en oeuvre dans cette thèse repose sur une modélisation du signal vibratoire dans l'espace d'état et une estimation H∞ des grandeurs caractéristiques de l’état de fonctionnement de la machine. Tout d’abord, nous avons décrit le signal vibratoire dans l'espace d'état grâce à une projection de l'enveloppe de chaque composante fréquentielle du signal sur la base canonique orthogonale. Ensuite, nous avons proposé une estimation de l’enveloppe. Cette approche d'estimation repose sur une optimisation minimax et consiste à minimiser le maximum de l'erreur d'estimation sans faire d'hypothèse sur la nature statistique des bruits du modèle d'état. Cette stratégie a conduit à ce que nous avons appelé dans cette thèse ‘estimateur BCOH∞’. La nouvelle approche proposée a été appliquée à des signaux synthétiques et expérimentaux pour le diagnostic de l’état des engrenages et des roulements en régime variable.Over the past ten years, several vibration signal-processing methods have been developed for the diagnosisof stationary rotating machines. However, more and more machines under surveillance operate in variable speed condition such as wind turbines, crushers, etc... The methods developed for the monitoring and diagnosis of these machines in steady state are no longer suitable for variable regimes. Some tools proposed for the variable regime case are limited to specific applications or offer a theoretical framework that limits their use in real situations. The purpose of this thesis is precisely to overcome these limitations, and this, by proposing a new approach to analyse the vibration signal acquired in variable regime. The strategy implemented in this thesis is based on a modelling of the vibration signal in the state space and an estimation H∞ of the characteristic quantities of the operating state of the machine. First, we described the vibration signal in the state space through a projection of the envelope of each frequency component of the signal on the orthogonal canonical basis. Then we proposed an estimate of the envelope. This estimation approach is based on a minimax optimization and consists of minimizing the maximum of the estimation error without making any assumptions about the statistical nature of the state model noise. This strategy ledto what we called in this thesis 'BCOH∞ estimator'. The proposed new approach has been applied to synthetic and experimental signals for the diagnosis of gears and bearings condition in variable speed
Prédiction de séries temporelles : de l'économétrie à l'apprentissage profond
No full textLa prédiction des séries temporelles (TSF) est essentielle dans divers domaines. Cette thèse explore profondément la TSF, contribuant aux domaines économétriques et de l’apprentissage profond. Dans cette thèse, nous avons étudié les méthodes de prédiction économétriques, y compris les modèles ARIMA, ETS, VAR et leurs variations, ainsi que les méthodes de décomposition des séries temporelles comme la décomposition canonique et STL. Nous avons aussi discuté de la méthode Theta et évalué ces techniques avec la décomposition STL sur les données du M3-Competition.Parallèlement, nous avons examiné les modèles d’apprentissage profond (DL) pour la TSF, tels que les MLP, CNN, RNN, le mécanisme d’attention, et les dérivés du modèle Transformer. Nous avons évalué trois modèles DL pour la prédiction multi-étapes de TSF,identifiant des pièges et proposant des solutions. Nous avons également présenté deux nouveaux modèles basés sur Transformer, Rankformer et STLformer, pour la prédiction à long terme de TSF, démontrant une performance supérieure. En outre, nous avons développé une application web prototype utilisant Python, Flask, Bootstrap, Plotly, et Docker, adhérant à un modèle MVC, facilitant le déploiement et offrant une interface utilisateur intuitive. L’application est en phase de test et sera bientôt déployée avec des fonctionnalités supplémentaires.Time series forecasting (TSF) is vital in fields like finance, economics, and meteorology. This thesis extensively probes TSF, contributing to econometrics and deep learning.In this thesis, we reviewed econometric forecasting methods such as ARIMA, ETS, VAR models, and time series decomposition methods, including canonical decomposition and STL. The Theta method is also discussed. We evaluated these techniques using STL decomposition on the M3-Competition datasets. Simultaneously, we investigated deep learning (DL) models for TSF, including MLPs,CNNs, RNNs, Attention Mechanism, and Transformer derivatives. We evaluated three DL models—DA-RNN, LSTNet, TPA-LSTM—for multi-step TSF problems, highlighting certain pitfalls and proposing solutions. We introduced two novel Transformer-based models, Rankformer and STLformer, exhibiting superior performance for long-term TSFtasks. We also developed a prototype web application that demonstrates our models, using Python and libraries like Flask, Bootstrap, and Plotly, following a MVC design pattern. The Docker-containerized application provides a user-friendly interface and visualizes outcomes
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
- …
