1,721,022 research outputs found
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe 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
Get PDF“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
Get PDFWe 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
Get PDFWe 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
Predicting Axial Force and Bending Moment in Pipelines Affected by Geohazard Using Machine Learning Techniques
No full textPipelines are vital to the safe and efficient transportation of energy resources, playing a critical role in meeting global energy demands and supporting economic stability. However, these critical infrastructures face significant risks from geohazards, particularly landslides, which can lead to sudden ground displacement and severe damage to pipelines. Such events not only compromise the structural integrity of pipelines but also pose environmental, economic, and public safety risks. Understanding the effects of landslides on pipeline design and safety is essential to developing robust strategies for mitigating these risks and ensuring the reliable transport of energy resources under challenging geohazard-induced conditions.
To address these challenges, this research focuses on predicting the structural responses of pipelines, including axial force and bending moment, under geohazard-induced conditions, such as landslides. Employing machine learning models, this study aims to provide a robust and efficient alternative to numerical methods. Specifically, Support Vector Regression (SVR), Neural Networks, and Random Forest models are developed and systematically evaluated for their ability to predict these responses, offering insights into the performance and applicability of each technique.
The dataset used in this study was generated through Python-based numerical simulations, leveraging theoretical models grounded in the Euler-Bernoulli beam theory. Parameters such as axial displacement (u′), lateral displacement (v′), and curvature (v′′) were sampled over ranges reflective of real-world pipeline deformation scenarios. This comprehensive dataset captures a realistic spectrum of elastic, plastic, and strain-hardening behaviours, ensuring accurate modelling of pipeline responses under diverse loading scenarios.
The generated dataset was used to train and evaluate the machine learning models, ensuring a comprehensive representation of diverse pipeline deformation scenarios. Model performance was assessed through key metrics, including Mean Squared Error (MSE), Mean Absolute Error (MAE), and Coefficient of determination (R²), alongside computational efficiency metrics such as training times. These metrics and comparisons were crucial in verifying that the models did not overfit or underfit the data, ensuring their ability to generalize effectively across unseen scenarios and diverse geohazard-induced conditions.
Recall performance and trend comparison were conducted to evaluate the models’ consistency and their ability to generalize across diverse scenarios. The recall comparison assessed the efficiency of each model in sequential and batch tasks, providing insights into their suitability for different operational requirements. Trend analysis examined the models' ability to capture theoretical relationships between input parameters and pipeline responses, validating their alignment with established frameworks.
The results demonstrated that Neural Networks provided the best balance of accuracy and computational efficiency, achieving high R² values (0.999 for axial force and 0.997 for bending moment) and moderate training times (37 seconds for axial force and 13 seconds for bending moment). SVR exhibited the highest R² values (0.999 for axial force and 0.996 for bending moment), indicating exceptional predictive accuracy; however, this came at the cost of significantly higher training times, particularly for bending moment predictions (3473 seconds). Random Forest, while computationally efficient in sequential recall tasks, lagged in predictive accuracy (R² values of 0.992 for axial force and 0.983 for bending moment) and struggled to capture complex trends, limiting its applicability to the studied scenarios.
This study is subject to several limitations. The dataset was generated using numerical simulations based on predefined parameter ranges, which may not fully capture the variability of real-world pipeline deformation scenarios. Additionally, the reliance on synthetic data and the lack of validation against experimental or field data limit the ability to confirm the models’ robustness in practical applications.
This research opens several avenues for future studies. Expanding the range of input parameters, such as u′, v′, and v′′, could enhance the generalizability of the predictive models, allowing them to handle a wider variety of deformation scenarios. Customizing material and geometric properties, such as pipe diameter, wall thickness, and soil characteristics, would provide deeper insights into the influence of these factors on axial force and bending moment predictions. Additionally, validating the findings with real-world data, instead of relying solely on synthetic datasets, would test the robustness of the models under practical conditions and increase their applicability to real-world engineering challenges. These efforts could further refine the models and broaden their relevance in pipeline safety and reliability studies
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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