6 resultados para ink reduction software
em QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast
Resumo:
The initial rate of the photocatalysed oxidation of methylene blue, MB, by dissolved oxygen in solution, ri(MB), is measured for a series of titania on glass samples exhibiting a wide range of activities. The samples used include two different types of commercial self-cleaning glass and a lab-made sol-geltitania film. The activities of these samples are also assessed using a resazurin-based photocatalyst activity indicator ink, i.e. Rz paii, for which the initial rates of the photocatalysed reduction of Rz were measured, ri(Rz). A plot of ri(MB)vs. ri(Rz) reveals a goodstraight line, thereby demonstrating a linear correlation (for TiO2films on glass at least) between the slow (usually hours) photocatalysed oxidation of organic materials, such as MB, and the fast (typically minutes) photocatalysed irreversible reduction of a dye, like Rz, in a paii. The possible use of paii technology for assessing, in a simple, quick and inexpensive manner, photocatalytic films both in the laboratory and in situ is discussed briefly.
Resumo:
The creation of idealised, dimensionally reduced meshes for preliminary design and optimisation remains a time-consuming, manual task. A dimensionally reduced model is ideal for assessing design changes through modification of element properties without the need to create a new geometry or mesh. In this paper, a novel approach for automating the creation of mixed dimensional meshes is presented. The input to the process is a solid model which has been decomposed into a non-manifold assembly of smaller volumes with different meshing significance. Associativity between the original solid model and the dimensionally reduced equivalent is maintained. The approach is validated by means of a free-free modal analysis on an output mesh of a gas turbine engine component of industrial complexity. Extensions and enhancements to this work are also discussed.
Resumo:
Background and aims: Machine learning techniques for the text mining of cancer-related clinical documents have not been sufficiently explored. Here some techniques are presented for the pre-processing of free-text breast cancer pathology reports, with the aim of facilitating the extraction of information relevant to cancer staging.
Materials and methods: The first technique was implemented using the freely available software RapidMiner to classify the reports according to their general layout: ‘semi-structured’ and ‘unstructured’. The second technique was developed using the open source language engineering framework GATE and aimed at the prediction of chunks of the report text containing information pertaining to the cancer morphology, the tumour size, its hormone receptor status and the number of positive nodes. The classifiers were trained and tested respectively on sets of 635 and 163 manually classified or annotated reports, from the Northern Ireland Cancer Registry.
Results: The best result of 99.4% accuracy – which included only one semi-structured report predicted as unstructured – was produced by the layout classifier with the k nearest algorithm, using the binary term occurrence word vector type with stopword filter and pruning. For chunk recognition, the best results were found using the PAUM algorithm with the same parameters for all cases, except for the prediction of chunks containing cancer morphology. For semi-structured reports the performance ranged from 0.97 to 0.94 and from 0.92 to 0.83 in precision and recall, while for unstructured reports performance ranged from 0.91 to 0.64 and from 0.68 to 0.41 in precision and recall. Poor results were found when the classifier was trained on semi-structured reports but tested on unstructured.
Conclusions: These results show that it is possible and beneficial to predict the layout of reports and that the accuracy of prediction of which segments of a report may contain certain information is sensitive to the report layout and the type of information sought.
