1,721,049 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
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
Photoacoustic imaging of layered microcircuits for non-destructive evaluation of sub-surface defects
No full textScanning PhotoAcoustic Microscopy (SPAM) was used for the imaging of surface and sub-surface layers in electronic circuits and ad hoc specimens. Depth-profiling SPAM was used, as it allows the imaging of opaque samples and sub-surface features; the signal contrast comes from variations in the optical, thermal or mechanical properties of the samples. In SPAM an intensity-modulated, highly-focused light beam (ion argon laser, 488 nm, 20 mW) scans the surface of the sample in the photoacoustic cell, with micrometric resolution. By varying the modulation frequency of the light beam, the thermal diffusion length of the heat waves inside the sample is changed, thus probing different layers beneath the sample surface. From the comparison of the SPAM images of multi-layer microcircuits obtained at different modulation frequencies, features of the first layers, circuit tracks and conductive connections between the layers can be detected. The SPAM images also correspond dimensionally with the actual layout of the circuits and may reveal the presence of defective parts. The preliminary results presented here suggest the introduction of the SPAM technique in the production process for NDE of layered microcircuits and, in general, for the quality control of sample parts. © 1995
Ensembles of Deep Neural Networks for the Automatic Detection of Building Facade Defects From Images
No full textPreserving the value of buildings and ensuring performance levels within acceptable parameters throughout their lifespan necessitates constant monitoring. In recent years, artificial intelligence has provided a valuable supplement to conventional inspection practices, potentially offering a supporting tool for building maintenance in smart cities. Exploiting machine learning algorithms for detecting or classifying building facade defects from acquired images has emerged as a promising automatic building monitoring strategy. However, an effective approach should be capable of accurately classifying fine-grained defects, thus requiring ad-hoc solutions to maximize predictive accuracy. For this reason, in this work, we introduced a novel and effective classification protocol, based on different ensemble strategies of complex and recent deep neural networks, namely Vision Transformers and ConvNexts, for building facade defects automatic classification. First, we validated our method on a popular benchmark dataset with different damage
classification tasks, outperforming the state-of-the-art available works. Then, we analyzed a custom dataset, named Facade Building Defects (FBD), containing building facade images labeled into four different defect classes, that we introduced in this work and released as open access. The proposed ensemble showed a test
accuracy of 90.9%, achieving an improvement of 1.6% with respect to the best single model, thus empirically proving the benefit of model ensembling for the task of automatic building facade defects classification
A Prosumer Approach for Feeding the Digital Twin. Testing the MUST Application in the Old Harbour Waterfront of Genoa
No full textSupporting the settlement systems’ life cycle management through synchronisation of the real world with a virtual platform constitutes the horizon for the MUST team research (Maintenance Urban Sharing Tools) with the Departments of Architecture (DiARC) and Structures for engineering and architecture (DiSt) of the University of Naples, Stress Scarl and ETT SpA. Living digital simulation models are based on information analysis and constant data supply. The research identifies the involvement of the settlement systems users through creating collaborative information flows, one of the driving factors of the digital revolution. The paper introduces the connotative aspects of the MUST application (Smau Innovation Award 2019, Campania Start-Up 2020 funded project) to identify the building and urban system loss of functionality. With the support of an experiment conducted in the waterfront area of the old harbour of Genoa, the paper identifies strengths and weaknesses in using the MUST application to support and streamline the Digital Twin that ETT S.p.A. is implementing with the DSH2030 (Digital Sustainable Harbor 2030) project. A prosumer perspective is the foundation of this research focusing on the sense of responsibility of communities towards the built environment and on the willingness of individuals to invest in care actions. The paper returns the research results achieved to date with an open and public model design, equipped with different interfaces to meet the diverse needs of the groups involved, allowing expert citizens to interact and report in progress feedback
Neural Signal Manager: a collection of classical and innovative tools for multichannel spike train analysis.
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