1,721,357 research outputs found
Characterization of porous materials in compressed and uncompressed conditions using a three-microphones method
No full textConventional methods to evaluate the absorption coefficient of materials use either a large reverberation room or wave guides such as standing-wave tubes or impedance tubes. These last methods have recently been extended so that other material properties such as airflow resistivity can also be evaluated using the same tubes. An advantage of the impedance tubes is that they can also be used to measure the acoustical and non-acoustical properties when the materials are under compression. The current study investigates the differences between two-microphone systems and three-microphone systems, and assess both the absorption coefficient and the flow resistivity of porous materials such as rock wool and fibreglass in both compressed and uncompressed conditions. Finally, the results of the study are discussed
The acoustic research in the Department of Architectural Science Ryerson University
No full textThe building science laboratory in the Department of Architectural Science has capabilities to conduct research activities in the field of room acoustics and noise control. Four impedance tubes, with both two-microphone and three-microphone systems, are available to evaluate the absorption coefficient as well as a number of other material properties. A scale model wind tunnel is also available for source localization experiments. Detailed finite element modelling, through COMSOL, are used to predict acoustic performance of passive silencers, Helmholtz resonators as well as sound propagation in the available wind tunnels. Similarly, aero-acoustic simulations are also possible by using the software ACTRAN. Finally, auditorium and room acoustic researches are conducted through simulations as well as through in field measurements
Special issue: Canadian acoustics cities = Édition spéciale : Acoustique canadienne des villes
No full text
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
Learning stochastic filtering
No full textWe quantify the performance of approximations to stochastic filtering by the Kullback-Leibler divergence to the optimal Bayesian filter. Using a two-state Markov process that drives a Brownian measurement process as prototypical test case, we compare two stochastic filtering approximations: a static low-pass filter as baseline, and machine learning of Volterra expansions using nonlinear Vector Auto-Regression (nVAR). We highlight the crucial role of the chosen per-formance metric, and present two solutions to the specific challenge of predicting a likelihood bounded between 0 and 1
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