1,721,085 research outputs found
Dataset supporting the University of Southampton Doctoral Thesis "Mechanical Properties of Re-used Ballast"
No full textThis dataset comprises of 1. Images, 2. Spreadsheets, 3. Data in txt files and 4. Matlab codes used in the production of my (Akash Gupta) thesis. The title of the thesis is: Mechanical Properties of Re-used Ballast.</span
Mechanical properties of re-used ballast
No full textThere is an urgent need to decarbonise transport– this includes the infrastructure. Railways have a key role to play in decarbonising transport because they are very energy-efficient, but the infrastructure and its upkeep are costly in money and carbon. Infrastructure maintenance requirements are likely to increase if the number, speed and weight of trains increase. This makes reducing the maintenance needs of the railways even more urgent. Traditionally, ballast has been considered to be life-expired after 10-50 tamps – typically about 30 years of service on moderate to busy lines. Overall maintenance needs could be reduced by reducing the need to maintain and then to replace ballast. This can be achieved by better understanding the performance of used ballast – cleaned and recovered. This thesis presents quantitative research into the relative shape properties of fresh and used ballast and relates these quantitative measures of shape to tested performance. Methods of evaluating surface roughness for railway ballast are proposed. Shape characterisation showed no significant difference in form between fresh and used ballast, a slight reduction in angularity in used ballast, and a significant reduction in roughness in used ballast. Scaled used ballast was synthesised for triaxial shear testing in the laboratory by abrading scaled fresh ballast in the Micro-Deval apparatus to a target shape equal to that of the used ballast. Effects of surface roughness and grain attrition due to loading on frictional properties of ballast were also investigated. Fresh and used ballast showed similar contact frictional properties. The study found that although the roughness of used ballast was smaller than that of fresh, both were similar in shape and showed similar strength properties. Ballast developed a stable structure over a few hundred thousand loading cycles. The resilient modulus increased by up to 60% with an increase in load cycles until about 200000 cycles; after this point, there was no significant increment. Cyclic loading improved the ballast strength by up to 15%. The study found that life-expired ballast of granitic origin could be reused
Grain characterisation of fresh and used railway ballast
No full textBallasted railway track requires regular maintenance to reverse the effects of plastic deformation of the trackbed, which leads to a gradual loss of level. Maintenance is usually by tamping, an aggressive process, which damages ballast grains such that the interval between maintenance interventions steadily reduces with increasing number of tamps. After a certain number of tamps, the ballast is deemed life expired and renewed, with the recovered ballast usually being down-cycled to lower grade uses. The ability to re-use the recovered ballast in the trackbed would make a significant contribution to decarbonising and improving the sustainability of railway infrastructure. This requires detailed knowledge of how the grain characteristics affecting mechanical behaviour differ between fresh and used ballast—specifically grain shape. This paper compares the shape parameters of form, angularity and surface roughness of fresh and used ballast, and proposes a method to synthesize full-size and scaled used ballast for use in laboratory and model tests
Supporting Data for: UltraMNIST Classification: A Benchmark to Train CNNs for Very Large Images
No full textConvolutional neural network (CNN) approaches available in the current literature are designed to work primarily with low-resolution images. When applied on very large images, challenges related to GPU memory, smaller receptive field than needed for semantic correspondence and the need to incorporate multi-scale features arise. The resolution of input images can be reduced, however, with significant loss of critical information. Based on the outlined issues, we introduce a novel research problem of training CNN models for very large images, and present ‘UltraMNIST dataset’, a simple yet representative benchmark dataset for this task. UltraMNIST has been designed using the popular MNIST digits with additional levels of complexity added to replicate well the challenges of real-world problems. We present two variants of the problem: ‘UltraMNIST classification’ and ‘Budget-aware UltraMNIST classification’. The standard UltraMNIST classification benchmark is intended to facilitate the development of novel CNN training methods that make the effective use of the best available GPU resources. The budget-aware variant is intended to promote development of methods that work under constrained GPU memory. For the development of competitive solutions, we present several baseline models for the standard benchmark and its budget-aware variant. We study the effect of reducing resolution on the performance and present results for baseline models involving pretrained backbones from among the popular state-of-the-art models. Finally, with the presented benchmark dataset and the baselines, we hope to pave the ground for a new generation of CNN methods suitable for handling large images in an efficient and resource-light manner. UltraMNIST dataset comprises very large-scale images, each of 4000x4000 pixels with 3-5 digits per image. Each of these digits has been extracted from the original MNIST dataset. Your task is to predict the sum of the digits per image, and this number can be anything from 0 to 27
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
A Study on the Evolution of Ballast Particle Surface Damage
No full textThe role of railway ballast is to spread traffic loads to the underlying ground. The contact area between ballast particles is often very small, leading to high contact stresses and surface abrasion, which is considered to degrade ballast quality and eventually necessitating ballast replacement. It is desirable to recycle and reuse as much of this “life-expired” ballast as possible, in whole or in certain particle sizes, as it would lead to a more sustainable engineering practice. However, research on the effect that particle surface damage has on the mechanics of ballast is required to understand the differences in behavior between recycled and fresh ballast, with a view to improving performance and increasing the length of maintenance cycles. This paper presents a study of ballast particle surface damage in terms of surface roughness using variable focus microscopy. Nanometer-scale surface scans of fresh and recycled ballast particles were acquired at predetermined resolutions and preselected areas. Methods of evaluating surface roughness for railway ballast are proposed, which indicate significant differences in roughness between fresh and recycled ballast. Laboratory tests with a Micro-Deval apparatus were used to quantify damage and the corresponding link to surface roughness
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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