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Institution

Dublin City University

EducationDublin, Ireland
About: Dublin City University is a education organization based out in Dublin, Ireland. It is known for research contribution in the topics: Context (language use) & Machine translation. The organization has 5904 authors who have published 17178 publications receiving 389376 citations. The organization is also known as: National Institute for Higher Education, Dublin & DCU.


Papers
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Journal ArticleDOI
TL;DR: The results demonstrate that eye‐tracking data, including pupil dilation measurements and gaze replays, in association with retrospective protocols promise to be a very effective methodology for future research into translation processes.
Abstract: Eye‐tracking has been used as a methodology for some time in various disciplines, but it has not been applied to date in translation studies. This paper presents results from a preliminary investigation which seeks to answer two questions: Firstly, is eye‐tracking, in general, a useful research methodology for investigating translators' interaction with Translation Memory tools? Secondly, what can eye-tracking data tell us about cognitive load when translators deal with different match types in Translation Memories? The results demonstrate that eye‐tracking data, including pupil dilation measurements and gaze replays, in association with retrospective protocols promise to be a very effective methodology for future research into translation processes. The results also suggest that the cognitive load for exact matches in Translation Memory tools is much lower than for other match types, that cognitive load for machine translation matches is close to fuzzy matches of between 80‐90% value, and that “no matche...

150 citations

Journal ArticleDOI
TL;DR: Two methods for processing raw UV-vis spectroscopic data generated from the Mb-CO assay are presented and comprehensively discussed here for the first time.
Abstract: The deoxy-myoglobin (deoxy-Mb)/carbonmonoxy-myoglobin (Mb-CO) UV-vis assay is the principal method used for quantifying the rates of CO release from CO-releasing molecules (CO-RMs) that might possess therapeutic benefits. Some issues emerge when the Mb-CO assay is utilized for testing CO-RMs with novel structures, which are comprehensively discussed here for the first time. Two methods for processing raw UV-vis spectroscopic data generated from the assay are presented in this paper.

150 citations

Journal ArticleDOI
10 Oct 2011-Analyst
TL;DR: The covalent-orientated immobilization strategy was the best for SPR-based HFA immunoassay and can detect 0.6-20.0 ng/mL of HFA in less than 10 min.
Abstract: Antibody immobilization strategies (random, covalent, orientated and combinations of each) were examined to determine their performance in a surface plasmon resonance-based immunoassay using human fetuin A (HFA) as the model antigen system. The random antibody immobilization strategy selected was based on passive adsorption of anti-HFA antibody on 3-aminopropyltriethoxysilane (APTES)-functionalized gold (Au) chips. The covalent strategy employed covalent crosslinking of anti-HFA antibody on APTES-functionalized chips using 1-ethyl-3-[3-dimethylaminopropyl]carbodiimide (EDC) and sulfo-N-hydroxysuccinimide (SNHS). The orientation strategy used passive adsorption of protein A (PrA) on Au chips, with subsequent binding of the anti-HFA antibody in an orientated fashion via its fragment crystallisable (Fc) region. In the covalent-orientated strategy, PrA was first bound covalently, to the surface, which in turn, then binds the anti-HFA antibody in an orientated manner. Finally, in the most widely used strategy, covalent binding of anti-HFA antibody to carboxymethyldextran (CM5-dextran) was employed. This immobilization strategy gave the highest anti-HFA antibody immobilization density, whereas the highest HFA response was obtained with the covalent-orientated immobilization strategy. Therefore, the covalent-orientated strategy was the best for SPR-based HFA immunoassay and can detect 0.6–20.0 ng/mL of HFA in less than 10 min.

150 citations

Journal ArticleDOI
27 Aug 2012
TL;DR: A critical need of an intensive investigation is stressed into the mechanisms of EDC-based amine-carboxyl coupling under various experimental conditions to improve the cost-effectiveness and analytical performance of immunoassays on APTES-functionalized platforms.
Abstract: 1-Ethyl-3-(3-dimethylaminopropyl) carbodiimide (EDC) alone, and in combination with N-hydroxysuccinimide (NHS) or sulfoNHS were employed for crosslinking anti-human fetuin A (HFA) antibodies on 3-aminopropyltriethoxysilane (APTES)-functionalized surface plasmon resonance (SPR) gold chip and 96-well microtiter plate. The SPR immunoassay and sandwich enzyme linked immunosorbent immunoassay (ELISA) for HFA clearly demonstrated that EDC crosslinks anti-HFA antibodies to APTES-functionalized bioanalytical platforms more efficiently than EDC/NHS and EDC/sulfoNHS at a normal pH of 7.4. Similar results were obtained by sandwich ELISAs for human Lipocalin-2 and human albumin, and direct ELISA for horseradish peroxidase. The more efficient crosslinking of antibodies by EDC to the APTES-functionalized platforms increased the cost-effectiveness and analytical performance of our immunoassays. This study will be of wide interest to researchers developing immunoassays on APTES-functionalized platforms that are being widely used in biomedical diagnostics, biosensors, lab-on-a-chip and point-of-care-devices. It stresses a critical need of an intensive investigation into the mechanisms of EDC-based amine-carboxyl coupling under various experimental conditions.

150 citations

Proceedings ArticleDOI
25 Jul 2004
TL;DR: An overview of the techniques used to develop and evaluate a text categorisation system to automatically classify racist texts is presented, and three representations of a web page within an SVM are looked at.
Abstract: In this poster we present an overview of the techniques we used to develop and evaluate a text categorisation system to automatically classify racist texts. Detecting racism is difficult because the presence of indicator words is insufficient to indicate racist texts, unlike some other text classification tasks. Support Vector Machines (SVM) are used to automatically categorise web pages based on whether or not they are racist. Different interpretations of what constitutes a term are taken, and in this poster we look at three representations of a web page within an SVM -- bag-of-words, bigrams and part-of-speech tags.

149 citations


Authors

Showing all 6059 results

NameH-indexPapersCitations
Joseph Wang158128298799
David Cameron1541586126067
David Taylor131246993220
Gordon G. Wallace114126769095
David A. Morrow11359856776
G. Hughes10395746632
David Wilson10275749388
Muhammad Imran94305351728
Haibo Zeng9460439226
David Lloyd90101737691
Vikas Kumar8985939185
Luke P. Lee8441322803
James Chapman8248336468
Muhammad Iqbal7796123821
Michael C. Berndt7622816897
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202367
2022261
20211,110
20201,177
20191,030
2018935