1,720,953 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
Optimization Techniques and Machine Learning Strategies for Small and Dense Energy Efficient LoRa Networks
No full textLow-Power Wide-Area Network (LPWAN) technologies, particularly LoRa and Lo- RaWAN, are pivotal in the rapidly expanding Internet of Things (IoT) landscape, en- abling wide-area communication with minimal power consumption. However, these technologies face significant challenges related to energy efficiency, scalability, and secu- rity, especially in dense deployments specially in smart cities and other IoT applications. This research addresses these challenges through a comprehensive investigation into op- timization strategies, machine learning applications, and security measures designed to enhance the performance of LoRa networks. Initially, the study introduces the importance of LoRa (Long Range) and LoRaWAN (Long Range Wide Area Network) in wireless communication, emphasizing the necessity for energy-efficient strategies in wireless sensor networks (WSNs). Common optimiza-tion techniques and machine learning models for energy prediction and detection are discussed, setting the stage for subsequent research aimed at improving LoRaWAN de- ployments in IoT environments. Recognizing the limitations of existing energy-efficient methods, such as Adaptive Data Rate (ADR) and its adaptations, especially for mobile devices within WSNs, the research identifies the impracticality of traditional energy optimization techniques re-quiring frequent updates on channel conditions due to LoRa’s duty cycle constraints. To address this, two novel algorithms are introduced, designed to dynamically opti-mize transmission power and Spreading Factor (SF) based on node distance, thereby minimizing energy consumption. These algorithms offer significant advancements in energy-efficient communication for WSNs, particularly beneficial in scenarios involving mobile devices. The theoretical descriptions are strengthened by the hardware imple- mentation of the algorithms. This practical validation not only confirms the conceptual foundations but also showcases the algorithm’s real-world feasibility and performance. However, the algorithms are developed for dynamic nodes and not generalized for a large scale deployment. The next step is to focus on generalizing the algorithm on a network management level where mathematical optimization models are aimed at opti-mizing communication efficiency by balancing energy consumption and delivery ratios. An integer linear programming model was introduced to offer a structured method for network configuration. By optimizing SF and transmission power settings, the algo- Abstract rithm enhances packet delivery ratios and energy efficiency, ensuring the sustainability and performance of IoT networks in dense deployment scenarios. This two-step ap-proach effectively addresses the objectives of minimizing time on air and transmission power while maintaining robust communication. The integration of machine learning (ML) models are explored, proposing an ML-based system for predicting energy consumption in LPWAN-based WSNs. By training ML models with historical data on transmission parameters, environmental conditions, and energy consumption patterns, the system can have optimal settings for transmission parameters tailored to current environmental factors. Real-time monitoring facilitated by ML models allows dynamic adjustments of parameters in response to changing net- work conditions, ensuring optimal network performance. This system also helps identify excessive energy consumption and greedy behavior, enabling proactive management of network resources. An extensive evaluation of twelve machine learning regression models was conducted to pinpoint the most effective model for predicting energy consumption. Performance metrics were utilized throughout the evaluation process to assess the ac- curacy and reliability of each model. Finally, a detection algorithm and a classification model are employed to distinguish between power greedy and standard nodes in the network. By utilizing data from the network, detection and classification models were devised to differentiate between stan-dard and greedy nodes based on their transmission parameters and energy consumption patterns. They aim to develop a method that can effectively identify nodes consuming excessive energy or operating sub-optimally, enabling better management and optimiza-tion of the network. In conclusion, the key findings and contributions of the research are summarized, emphasizing the significance of the developed strategies in addressing en- ergy constraints and enhancing the sustainability of IoT applications. Potential avenues for future research are outlined, including further refinement of optimization techniques, integration of emerging technologies such as artificial intelligence and edge computing, and expanding the applicability of these solutions to other IoT domains
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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