1,720,972 research outputs found
A Distributed Event-Orchestrated Digital Twin Architecture for Optimizing Energy-Intensive Industries
No full textThis paper presents a novel distributed architecture designed to spawn digital twin solutions to improve energy efficiency in energy-intensive industrial scenarios. By executing user-defined workflows, our platform enables the implementation of real-time monitoring, forecasting, and simulation microservices to enhance decision-making strategies for optimizing industrial processes. Leveraging a stateless centralized orchestration mechanism built around an Apache Kafka-based backbone, the platform ensures scalability, fault tolerance, and efficient handling of heterogeneous data. Key features include intuitive workflow configuration, asynchronous communication for streamlined workflow execution, and API-driven scheduling for dynamic, event-based task management. This platform will be deployed and validated in several energy-intensive industrial scenarios, supporting the management of energy systems of different plants, to prove its effectiveness across a wide range of energy management challenges
Pain Assessment in Neonatal Clinical Practice via Facial Expression Analysis and Deep Learning
No full textSince newborns are unable to verbally communicate the experience of pain, accurate pain assessment using validated tools is crucial to determine the most effective pain management strategies. Traditional pain assessment relies on the use of pain scales that consider behavioural, physiological, and contextual indicators, but is highly depending on the subjective experience of healthcare professionals. Therefore, automated pain assessment systems are desirable in clinical practice for a more efficient and objective pain evaluation. This work proposes a deep learning framework for newborn pain assessment based on facial expression analysis, suitable for the real-world environment of the Neonatology Department. It exploits a pre-trained Convolutional Neural Network that is fine-tuned on image data recorded during neonatal heel prick. The trained model achieves an average accuracy of 87.4% and F1-score of 75.4% using a stratified 5-fold cross-validation to classify newborn images into pain or nonpain classes. The performance is further improved by including images from iCOPE dataset in the training process. Moreover, the application of a visual explanation technique highlights that the model predictions are based on the facial regions most closely associated to the pain experience. Our results show that automated pain detection from facial expressions is feasible in a real-world setup. By introducing an explainable artificial intelligence approach, we also contribute to the improvement of model transparency and trust for healthcare professionals. This paves the way for the development of an automated system that integrates, standardises, and improves human pain evaluation
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
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