1,721,228 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
Novel Prospects of Image Restoration Inspired by Concepts of Quantum Mechanics
No full textLa décomposition d'images numériques en d'autres bases ou dictionnaires que les domaines temporel ou spatial est une approche très courante et efficace dans le traitement et l'analyse d'images. Une telle décomposition est couramment obtenue à l'aide de transformations fixes ou de dictionnaires appris à partir de bases de données d'exemple ou à partir du signal ou de l'image eux-mêmes. Ces dernières années, avec la croissance de la puissance de calcul, les stratégies exploitant la redondance des patchs extraits d'une ou de plusieurs images pour faciliter leur décomposition parcimonieuse sont devenues très populaire, notamment grâce à leur efficacité à restaurer des images. Un des objectifs de cette thèse est de savoir comment concevoir une telle transformation adaptative à l’aide de principes de la mécanique quantique. Cette thèse explore de nouvelles approches de construction de telles bases dépendantes de l'image inspirées de la mécanique quantique. Tout d'abord, nous construisons une base dépendante de l'image en utilisant les solutions d'onde de l'équation de Schrödinger. En particulier, en considérant l'image comme un potentiel dans l'équation de Schrödinger discrétisée, nous obtenons les solutions d'onde qui constitue une base et qui joue le rôle de transformée. L'efficacité de la décomposition proposée est illustrée par des résultats de débruitage dans le cas des bruits Gaussiens, de Poisson et de speckle et par comparaison aux algorithmes de l'état de l'art. Cette décomposition adaptative est ensuite généralisée en s’inspirant de la théorie quantique à plusieurs corps. Sur la base de l'analyse par patchs, les mesures de similarité dans un voisinage d'image local sont formalisées par un terme apparenté à l'interaction en mécanique quantique qui peut efficacement préserver les structures locales des images. La nature polyvalente de cette base adaptative étend la portée de son application à des scénarios de bruit indépendants ou dépendants de l'image sans aucun ajustement. Nous effectuons une comparaison rigoureuse avec les méthodes existantes pour démontrer la capacité de débruitage de l'algorithme proposé, quelles que soient les caractéristiques de l'image, les statistiques de bruit et l'intensité. Nous montrons la capacité de nos approches à traiter des données médicales réelles telles que le débruitage d'images de tomodensitométrie dentaire clinique et les applications de despeckling d'images d'échographie médicale. Nous étendons encore notre travail aux tâches de déconvolution d'image et de super-résolution en exploitant nos algorithmes de debruitage adaptatifs quantiques proposés. En particulier, suite à des développements récents, nous imposons ces débruiteurs externes comme fonction préalable au sein des approches de type Plug-and-Play et Régularisation par Débruitage. Enfin, nous présentons une architecture de réseau neuronal profond dépliant notre proposition d'algorithme de débruitage adaptatif, reposant sur la théorie de la physique quantique à plusieurs corps. Les ingrédients clés de la méthode proposée sont d'une part, sa capacité à gérer des structures d'image non locales à travers le terme d'interaction patch et l'opérateur Hamiltonien quantique, et, d'autre part, sa flexibilité pour adapter les hyperparamètres aux caractéristiques de chaque patch. De plus, il est démontré qu'avec de très légères modifications, ce réseau peut être amélioré pour résoudre des tâches de restauration d'image plus difficiles telles que le défloutage d'image, la super-résolution et l'inpainting. Malgré une architecture compacte et interprétable (d'un point de vue physique), le réseau d'apprentissage profond proposé améliore plusieurs algorithmes de référence récents de la littérature, conçus spécifiquement pour chaque tâche. Enfin, nous abordons le problème de l'amélioration des image échocardiographiques clinique pour démontrer le potentiel de notre réseau profond dans des applications médicales réelles.Decomposition of digital images into other basis or dictionaries than time or space domains is a very common and effective approach in image processing and analysis. Such a decomposition is commonly obtained using fixed transformations (e.g., Fourier or wavelet) or dictionaries learned from example databases or from the signal or image itself. In recent years, with the growth of computing power, data-driven strategies exploiting the redundancy within patches extracted from one or several images to increase sparsity have become more prominent. They have demonstrated very promising image restoration results. The question to pursue in this thesis is how to design such an adaptive transformation based on principles of quantum mechanics. In this thesis, we explore new possibilities of constructing such image-dependent bases inspired by quantum mechanics. First, we construct an image-dependent basis using the wave solutions of the Schrödinger equation, in particular, by considering the image as a potential in the discretized Schrödinger equation. The efficiency of the proposed decomposition is illustrated through denoising results in the case of Gaussian, Poisson, and speckle noises and compared to the state-of-the-art algorithms. We further generalize our proposed adaptive basis by exploiting the data-driven strategy inspired by quantum many-body theory. Based on patch analysis, the similarity measures in a local image neighborhood are formalized through a term akin to interaction in quantum mechanics that can efficiently preserve the local structures of real images. The versatile nature of this adaptive basis extends the scope of its application to image-independent or image-dependent noise scenarios without any adjustment. We carry out a rigorous comparison with contemporary methods to demonstrate the denoising capability of the proposed algorithm regardless of the image characteristics, noise statistics and intensity. We show the ability of our approaches to deal with real-medical data such as clinical dental computed tomography image denoising and medical ultrasound image despeckling applications. We further extend our work to image deconvolution and super-resolution tasks exploiting our proposed quantum adaptive denoisers. In particular, following recent developments, we impose these external denoisers as a prior functions within the Plug-and-Play and Regularization by Denoising approaches. Lastly, we present a deep neural network architecture unfolding our proposed baseline adaptive denoising algorithm, relying on the theory of quantum many-body physics. The key ingredients of the proposed method are on one hand, its ability to handle non-local image structures through the patch-interaction term and the quantum-based Hamiltonian operator, and, on the other hand, its flexibility to adapt the hyperparameters patch wisely, due to the training process. Furthermore, it is shown that with very slight modifications, this network can be enhanced to solve more challenging image restoration tasks such as image deblurring, super-resolution and inpainting. Despite a compact and interpretable (from a physical perspective) architecture, the proposed deep learning network outperforms several recent benchmark algorithms from the literature, designed specifically for each task. Finally, we address the problem of clinical cardiac ultrasound image enhancement to demonstrate the potential of our proposed deep unfolded network in real-world medical applications
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
Author Under Sail The Imagination of Jack London, 1893-1902
No full textIn Author Under Sail, Jay Williams offers the first complete literary biography of Jack London as a professional writer engaged in the labor of writing. It examines the authorial imagination in London's work, the use of imagination in both his fiction and nonfiction, and the ways he defined imagination in the creative process in his business dealings with his publishers, editors, and agents. In this first volume of a two-volume biography, Williams traverses the years 1893 to 1902, from London's "Story of a Typhoon" to The People of the Abyss. The Jack London who emerges in the pages of Author Under Sail is a writer whose partnership with publishers, most notably his productive alliance with George Brett of Macmillan, was one of the most formative in American literary history. London pioneered many author models during the heyday of realism and naturalism, blurring the boundaries of these popular genres by focusing on absorption and theatricality and the representation of the seen and unseen. London created an impassioned, sincere, and extremely personal realism unlike that of other American writers of the time. Author Under Sail is a literary tour de force that reveals the full range of London as writer, creative citizen, and entrepreneur at the same time it sheds light on the maverick side of machine-age literature.Intro -- Title Page -- Copyright Page -- Dedication -- Contents -- Acknowledgments -- Introduction -- 1. Spirit Truth -- 2. From Absorption to Theatricality and Back Again -- 3. "I Will Build a New Present" -- 4. Sons as Authors -- 5. Fathers as Publishers -- 6. The Daughter as Author -- 7. Lovers as Authors -- 8. At Sea with the Family -- 9. Yellow News, Yellow Stories -- 10. The Return Home -- Notes -- Bibliography -- Index -- About Jay WilliamsIn Author Under Sail, Jay Williams offers the first complete literary biography of Jack London as a professional writer engaged in the labor of writing. It examines the authorial imagination in London's work, the use of imagination in both his fiction and nonfiction, and the ways he defined imagination in the creative process in his business dealings with his publishers, editors, and agents. In this first volume of a two-volume biography, Williams traverses the years 1893 to 1902, from London's "Story of a Typhoon" to The People of the Abyss. The Jack London who emerges in the pages of Author Under Sail is a writer whose partnership with publishers, most notably his productive alliance with George Brett of Macmillan, was one of the most formative in American literary history. London pioneered many author models during the heyday of realism and naturalism, blurring the boundaries of these popular genres by focusing on absorption and theatricality and the representation of the seen and unseen. London created an impassioned, sincere, and extremely personal realism unlike that of other American writers of the time. Author Under Sail is a literary tour de force that reveals the full range of London as writer, creative citizen, and entrepreneur at the same time it sheds light on the maverick side of machine-age literature.Description based on publisher supplied metadata and other sources.Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, YYYY. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries
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