1,720,967 research outputs found
Denoising, Deblurring and Automatic Segmentation of XCT Data with Deep Learning and Synthetic XCT Training Data. A Case Study on Al-Si MMCs.
No full textWe employ in-house generated synthetic Al-Si matrix composite XCT data for training deep convolutional neural networks for XCT data conditioning and automatic segmentation. We propose an in-house multilevel deep conditioning framework capable of rectifying noise and blur in corrupted XCT data sequentially. Furthermore, for automatic segmentation, we utilize a special in-house network coupled with a novel iterative segmentation algorithm capable of generalized learning from synthetic data. We report a consistent SSIM efficiency of 92%, 99%, and 95% for the combined denoising/deblurring, standalone denoising, and standalone deblurring, respectively. The overall segmentation precision was over 85% according to the Dice coefficient. We used experimental XCT data from various scans of Al-Si matrix composites reinforced with ceramic particles and fibers
Alternative Drivetrain for Future Freight Trucks
No full textPresently, heavy-duty trucks are responsible for approximately 25% of global CO2 emissions. Although the world seems to incline towards the transport sector's electrification, the electrification of long-range freight trucks is profoundly challenging. The dominant disincentives are the required infrastructure, cost/size of batteries, limited mileage, and long charging sessions. However, despite the efforts to reduce emissions, current trends indicate that these continue to rise, mostly because of the continually increasing freight transit. Regional economies are heavily dependent on the latter. Thus, the imminent depletion of fossil fuels and the emerging environmental issues are disquieting aspects for the sustainability of this crucial sector. This thesis focuses on the possible alternative powertrain/drivetrain solutions for heavy-duty, long-range freight trucks in conjunction with sustainable energy carriers for the transportation sector overall. In terms of viable fuelling alternatives, the following are being reviewed: Electric Power, Bio-Fuels, and Synthetic Fuels, along with their current status, advantages, disadvantages and future prospects. In terms of powertrain/drivetrain alternatives, the following are being theoretically and critically evaluated and compared against a direct drive conventional Diesel engine truck (25.2% wheel efficiency): Battery Electric, Electric powered with overhead cables or underground conductive coils, combined Gas Turbine/Stirling Engine Hybrid Electric in series, combined Diesel engine/Stirling engine Hybrid Electric in series, and Diesel engine Hybrid Electric in series. It is concluded that the best scenario for future freight trucks, is the use of an electric drivetrain/powertrain in conjunction with overhead powering cables along the highways. However, due to uncertainties in the universal realization of such infrastructure, to ensure uninterrupted transportation of goods, a plausible transitional solution could be the use of a Diesel engine/Stirling engine Hybrid Electric in series technology. This could reduce emissions/consumption by a factor of 2.4 (60% wheel efficiency). For the case of Gas turbine/Stirling engine and Diesel engine (both) Hybrid Electric in-series arrangements, this factor drops to 1.7 and 1.4 (42.9% and 34.3% wheel efficiency), respectively. Furthermore, this can be a clean and sustainable solution if biofuels are employed as the prime energy carriers. Such an approach is future-proof for use with overhead cables, since the suggested powertrain is electric, rendering a freight truck as a very versatile heavy-duty, long-range vehicle. Electro-fuels are not considered as a viable option due to their inefficient formulation, elevated costs, and problematic handling (Hydrogen)
HIGHLY OPTIMIZED & COMPUTATIONALLY EFFICIENT COHESIVE ELEMENTS FOR MICROSTRUCTURAL MODELLING OF CFRCs
Full text linkCNN Architectures for Image Processing.
No full textDeep Convolutional Neural Networks (DCNNs) and their applications in (XCT) data conditioning and automatic segmentation. A case study in Al-Si MMCs with synthetic training data
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
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