1,721,323 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
Property modification of rigid polyurethane foam by end-of-life polyvinyl chloride foam particles
No full textEnd-of-life (EoL) rigid crosslinked polyvinyl chloride (PVC) foams are subjected to hazardous procedure of incineration or landfilling for waste management. This work aims to valorize PVC waste for the property variation of rigid polyurethane (PU) foam. PVC waste was sieved to obtain different sized particles and were mixed homogenously in polyol/isocyanate mixture. The geometrical density of modified foams increased with the progressive addition of the PVC particles, the effect of which was more pronounced with 300 μm PVC particles. Morphological analysis of these foams revealed a reduction in cell size and an increase in the open porosity of the PU cell structure. Moreover, PU foams loaded with PVC particles did not manifest a severe reduction of the former's insulating property. The effect of damping in PU foams was also verified by resonance tests where a size effect was observed, increasing the damping ratio and thus enhancing the usefulness of such insulating structures
Optimizing Clustering Algorithms for Anti-Microbial Evaluation Data: A Majority Score-Based Evaluation of K-Means, Gaussian Mixture Model, and Multivariate T-Distribution Mixtures
Full text linkThis study presents a detailed analysis of the performance of the majority score clustering algorithm on three different datasets of anti-microbial evaluation, namely the minimum inhibitory concentration (MIC) of bacteria, and the antifungal activity of chemical compounds against 4 bacteria (E. coli, P. aeruginosa, S. aureus, S. pyogenes) and 2 fungi (C. albicans, As. fumigatus). Clustering is an unsupervised machine learning method used to group chemical compounds based on their similarity. In this paper, we apply the k-means clustering, Gaussian mixture model (GMM), and mixtures of multivariate t distribution to antibacterial activity datasets. To determine the optimal number of clusters and which clustering algorithm performs best, we use a variety of clustering validation indices (CVIs) which include within sum square (to be minimized), connectivity (to be minimized), Silhouette Width (to be maximized), and the Dunn Index (to be maximized). Based on the majority score clustering algorithm, we conclude that the k-means and mixture of multivariate t-distribution methods perform best in terms of the maximum CVIs, while GMM performs best in terms of the minimum CVIs. K-means clustering and mixture of multivariate t-distribution provide 3 optimal clusters for the anti-microbial evaluation of antibacterial activity dataset and 5 optimal clusters for the MIC bacteria dataset. K-means clustering, mixture of multivariate t-distribution, and GMM provide 3 optimal clusters for both the antibacterial and antifungal activity datasets. K-means clustering algorithm performs the best in terms of the majority-based clustering algorithm. This study may be useful for the pharmaceutical industry, chemists, and medical professionals in the future
Managerial Gaps in E-banking Quality Drivers: An Empirical Assessment
No full textABSTRACT
Quality provided to the customer is a main issue for e-banking. The extant literature on e-services has preferentially examined quality factors as perceived by customers. However, on the other side, quality depends on the managerial perceptions about quality drivers and the decisions that would follow from these perceptions. According to SERVQUAL - the most known service quality model - any gaps between management’s and customers’ perceptions would affect the experienced quality and then the customer satisfaction. The aim of the paper is to explore how bank managers perceive quality drivers for e-banking through a preliminary empirical survey
Machinability of recycled aluminum alloys
No full textThe use of recycled (hereafter called secondary) aluminum alloys is increasing more and more in light of sustainability as the energy needed for their production is much lower than in the case of the primary alloys and they may have mechanical properties comparable to those of the latter. Most of the secondary aluminum alloys are used to fabricate parts through casting processes, which may need further machining operations to get the part’s final shape. While the mechanical properties of the secondary aluminum alloys have been comprehensively addressed in the literature and correlated to the different intermetallic particles that characterize their microstructure, the same is not true when addressing machinability. In this framework, the paper investigates the machinability of one primary and two secondary aluminum alloys in terms of cutting forces and surface finish after turning trials carried out at fixed cutting parameters. A detailed characterization of the alloys’ microstructure was carried out making use of both optical and scanning electron microscopy to identify the size, morphology, and distribution of intermetallics. The highest cutting force was registered when machining the primary alloy, being characterized by the highest specific cutting energy. The surface damage in terms of tearings induced by cutting was comparable between the primary and secondary alloys. In contrast, the different roughness features that characterize the machined surfaces of the considered alloys can be partly ascribed to the different intermetallics they present. Nevertheless, the surface topography analysis results must be interpreted based on the specific application
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