1,720,954 research outputs found
Prediction of Compressive Strength by Considering Practical Consideration Non-destructive Test by Artificial Neural Network
Full text linkAccurate assessment of concrete compressive strength is critical for evaluating structural performance. While nondestructive testing (NDT) methods, such as Schmidt rebound hammer tests, offer rapid and NDT gives result with reasonable accurate based on environmental factors such as temperature, humidity etc of site and condition in which test is performed. Destructive testing (DT) methods, like core cutting, provide direct and accurate results. This study aimed to bridge the gap between these approaches by developing predictive models that correlate DT and NDT results. Experimental work involved 126 laboratory-prepared samples (grades M10–M40) with curing age of 14 day and 28 day and 231 field samples from a 20-year-old structure, tested using both methods. Total 357 no. of data samples were created with different mix proportion of design, curing ages and on-site environmental exposed concrete structure without unknown grade. Most of the researches were done while preparation of samples in the laboratory. For these purposes of taking mixing both variations such as control (Laboratory) and uncontrolled(on-site) samples were to prepare as a practical condition for prediction. For generation of predict model 70% data was used with methods such as regression analysis and Cascade forward back propagation neural network (CFBPNN) were used for investigation. To validate the prediction 30% data was used which was not used in model generation. The prediction results show that the coefficients of determination (R2) of the Regression analysis and the CFBPNN prediction models for the test set of concrete compressive strength are 95% and 99% respectively ANN model founded to be more accurate as compare to regression analysis. The validation by R2 of the Regression analysis and the CFBPNN prediction model for the compressive strength for above dataset was 89.0% and 98%. Statistical metrics (MSE, RMSE, MAPE) further confirmed the neural network’s superior accuracy
Prediction of Compressive Strength by Considering Practical Consideration Non-destructive Test by Artificial Neural Network
Full text linkAccurate assessment of concrete compressive strength is critical for evaluating structural performance. While nondestructive testing (NDT) methods, such as Schmidt rebound hammer tests, offer rapid and NDT gives result with reasonable accurate based on environmental factors such as temperature, humidity etc of site and condition in which test is performed. Destructive testing (DT) methods, like core cutting, provide direct and accurate results. This study aimed to bridge the gap between these approaches by developing predictive models that correlate DT and NDT results. Experimental work involved 126 laboratory-prepared samples (grades M10–M40) with curing age of 14 day and 28 day and 231 field samples from a 20-year-old structure, tested using both methods. Total 357 no. of data samples were created with different mix proportion of design, curing ages and on-site environmental exposed concrete structure without unknown grade. Most of the researches were done while preparation of samples in the laboratory. For these purposes of taking mixing both variations such as control (Laboratory) and uncontrolled(on-site) samples were to prepare as a practical condition for prediction. For generation of predict model 70% data was used with methods such as regression analysis and Cascade forward back propagation neural network (CFBPNN) were used for investigation. To validate the prediction 30% data was used which was not used in model generation. The prediction results show that the coefficients of determination (R2) of the Regression analysis and the CFBPNN prediction models for the test set of concrete compressive strength are 95% and 99% respectively ANN model founded to be more accurate as compare to regression analysis. The validation by R2 of the Regression analysis and the CFBPNN prediction model for the compressive strength for above dataset was 89.0% and 98%. Statistical metrics (MSE, RMSE, MAPE) further confirmed the neural network’s superior accuracy
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
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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