1,720,962 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
Artificial intelligence for enhanced prehospital stroke care : focus on efficient mobile stroke unit allocation and travel time estimation
No full textStroke remains one of the leading causes of death and disability globally, underscoring the importance of timely and effective prehospital care to improve patient outcomes. This thesis aims to use artificial intelligence’s power to enhance prehospital stroke care. To accomplish this, we study challenges in prehospital stroke care by focusing on three interrelated research challenges: Mobile stroke unit (MSU) allocation, ambulance travel time estimation, and improving travel time calculations within emergency medical service (EMS) simulation. We develop and analyze different optimization and machine learning (ML) methods to achieve improved analysis and planning of prehospital stroke care. In particular, we propose methods to solve the MSU allocation problem, which aims to identify the optimal locations for a fixed number of MSUs at the existing ambulance station locations within a geographic region. Moreover, we develop a machine learning-based regression method for ambulance travel time estimation. Next, we apply our pre-trained ML-based regression method to improve ambulance travel time estimation within an EMS simulation framework. For the MSU allocation problem, we first propose a mathematical model, which we apply to identify the optimal MSU locations in the Blekinge and Kronoberg counties of Sweden. The experimental findings show both the correctness of the suggested model and the benefits of placing MSUs in the considered regions. Second, we propose a Genetic algorithm (GA) method with an efficient encoding scheme for the input data, representing the number of MSUs and potential sites. Additionally, we develop custom selection, crossover, and mutation operators tailored to the specific characteristics of the MSU allocation problem. We present a case study on the Southern Healthcare Region in Sweden to demonstrate the generality and robustness of our proposed GA method. Particularly, we demonstrate our method’s flexibility and adaptability through a series of experiments across multiple settings. Third, we propose the enhanced genetic algorithm with clustering (EGAC). By leveraging clustering, the EGAC provides diverse and comprehensive coverage, avoiding the pitfalls of starting with closely located and potentially less optimal solutions, thereby effectively steering and accelerating its convergence towards the optimal MSU placements. Our experimental results show that the EGAC significantly outperforms the traditional genetic algorithm, which does not make use of cluster-based starting solutions, by achieving remarkably faster convergence towards the optimal solution for different numbers of MSUs to allocate. We illustrate the performance of the EGAC through qualitative and quantitative analyses. For ambulance travel time estimation, we propose an ML-based regression method for estimating ambulance travel times. Ambulance travel time estimations play a pivotal role in ensuring timely and efficient emergency medical care by predicting the time needed by an ambulance to reach a specific location. Overlooking factors such as local traffic situations, day of the week, hour of the day, or the weather may create a risk of inaccurately estimating the ambulance travel times, which might lead to longer emergency response times, potentially impacting patient outcomes. We propose a machine learning approach to accurately estimate ambulance travel times, particularly using regression models and real-world spatiotemporal data from the Skåne region, Sweden. Our method includes data preprocessing and feature engineering, with a focus on variables significantly correlated with travel time. Through a comprehensive exploratory data analysis, we highlight the main characteristics, patterns, and underlying trends of the considered ambulance data set. We present an extensive empirical analysis comparing the performance of different machine learning models across different ambulance travel trips and feature sets, revealing insights into the importance of each feature in improving the estimation accuracy. Another focus of this thesis is the use of our ML-based regression method to improve the ambulance travel time estimation within EMS simulation. To illustrate the effectiveness of the proposed regression modeling, we utilize a modeling construction framework to construct an EMS simulation model for stroke patients and applied it in a scenario study covering Skåne County, Sweden. The result of the simulation shows differences in am- bulance driving times when using the ML-based module compared to existing routing engines designed for passenger cars. The observed differences emphasize the impacts of integrating ML-based estimations into EMS simulations.Felaktigt angiven serieuppgift i publikationen.</p
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
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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