1,720,970 research outputs found
Going Beyond Counting First Authors in Author Co-citation Analysis
The 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
“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
We 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
A novel anomaly detection model for the industrial Internet of Things using machine learning techniques
In recent decades, the pervasive integration of the Internet of Things (IoT) technologies has revolutionized various sectors, including industry 4.0, telecommunications, cloud computing, and healthcare systems. Industry 4.0 applications, characterized by real-time data exchange, increased reliance on automation, and limited computational resources at the edge, have reshaped global business dynamics, aiming to innovate business models through enhanced automation technologies. However, ensuring security in these environments remains a critical challenge, with real-time data streams introducing vulnerabilities to zero-day attacks and limited resources at the edge demanding efficient intrusion detection solutions. This study addresses this pressing need by proposing a novel intrusion detection model (IDS) specifically designed for Industry 4.0 environments. The proposed IDS leverages a Random Forest classifier with Principal Component Analysis (PCA) for feature selection. This approach addresses the challenges of real-time data processing and resource limitations while offering high accuracy. Based on the Bot-IoT dataset, the model achieves a competitive accuracy of 98.9% and a detection rate of 97.8%, outperforming conventional methods. This study demonstrates the effectiveness of the proposed IDS for securing Industry 4.0 ecosystems, offering valuable contributions to the field of cybersecurity
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