1,720,957 research outputs found
Distributed Optical Fiber-Based Monitoring of Smart Passive Anchors for Soil Stabilization
No full textGeotechnical structures, such as piles and anchors, play a critical role in providing stability and support in a wide range of civil engineering applications. Ensuring the integrity and safety of these structures and reliably understanding their structural behavior are of paramount importance. This paper explores the application of distributed fiber optic sensors (DFOS) as a cutting-edge technology for monitoring the performance and health of passive composite anchors for soil stabilization. These anchors comprise a conventional carbon steel self-drilling bar with one or more embedded harmonic steel tendons, cemented within the central cavity of the bar. The system is finalized by an external plate for securing the bar and a protective cover for safeguarding the tendon head. Within this context, DFOS technology offers a non-invasive and cost-effective solution for real-time monitoring of various parameters, such as strain and temperature, along the entire length of the fiber optic cable. This technology enables continuous, high-resolution monitoring data collection, providing a comprehensive understanding of the long-term behavior of this specific geotechnical structure. The capability of DFOS to provide spatially distributed information facilitates the detection of localized stress concentrations and deformation patterns. The paper covers some practical considerations, such as installation techniques, data analysis and preliminary results on recently case study. The limitations and challenges associated with DFOS technology in geotechnical applications will be also discussed, including the need for specialized expertise in interpreting the data, the potential for signal attenuation in long cables and the particular care that these sensors require during cable installation and management
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
Smart Monitoring by Fiber-Optic Sensors of Strain and Temperature of a Concrete Double Arch Dam
No full textAn innovative method integrating two deep learning networks and hyperparameter optimization for identifying fiber optic temperature measurements in earth-rock dams
No full textSince one of the main threats to the safety of earth-rock dams is leakage, its timely and accurate identification is crucial. Distributed fiber optic sensing system (DFOS) is considered as one of the ideal methods for leakage monitoring in earth-rock dams. However, the working conditions of earth-rock dams are complex, and the identification of fiber optic temperature measurements has issues such as low efficiency and high misjudgment rate. For improving the identification efficiency and accuracy of fiber optic temperature measurements in earth-rock dams, a signal identification method integrating least squares generative adversarial network (LSGAN), one-dimensional convolutional neural network (1DCNN), and white shark optimization (WSO) algorithm is presented. Firstly, the LSGAN model is used to augment the signals of different categories to reduce the effect of data set unbalance on the identification result. According to the variation characteristics of fiber optic temperature measurement signals in earth-rock dams, a 1DCNN model is designed to extract signal features for classification. To reduce the blindness in hyperparameter setting of 1DCNN model, the WSO algorithm is introduced to optimize its key hyperparameters, which further enhances the identification accuracy of the model. The new method is applied to a data set specifically acquired with tests on a physical model of an earth-rock dam. The identification accuracy obtained with the new method reaches 99.76 %, which is better than the accuracy of other commonly used identification methods. Upon completion of the pre-training, the new method can fulfill the practical needs of fast identification and has promising applications
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