Intelligent multimedia indexing and retrieval through multi-source information extraction and merging

This paper reports work on automated meta-data\ud creation for multimedia content. The approach results\ud in the generation of a conceptual index of\ud the content which may then be searched via semantic\ud categories instead of keywords. The novelty\ud of the work is to exploit multiple sources of\ud information relating to video content (in this case\ud the rich range of sources covering important sports\ud events). News, commentaries and web reports covering\ud international football games in multiple languages\ud and multiple modalities is analysed and the\ud resultant data merged. This merging process leads\ud to increased accuracy relative to individual sources

Cumulative effects of offshore renewables : From pragmatic policies to holistic marine spatial planning tools

Acknowledgement This work was supported by Supergen Offshore Renewable Energy (ORE) Hub, funded by the Engineering and Physical Sciences Research Council (EPSRC EP/S000747/1), the UK Department for Business, Energy & Industrial Strategy's (BEIS) offshore energy Strategic Environmental Assessment Programme, PELAgIO https://ecowind.uk/projects/pelagio/ funded by NERC (NE/X008835/1) and EcoNex https://ukerc.ac.uk/project/the-marine-energy-biodiversity-and-food-nexus-econex/ funded by UKERC.Peer reviewedPublisher PD

A new strategic framework to structure cumulative impact assessment (CIA)

Funding Information: This work was supported by Supergen Offshore Renewable Energy (ORE) Hub, funded by the Engineering and Physical Sciences Research Council (EPSRC EP/S000747/1) and the UK Department for Business, Energy & Industrial Strategy (BEIS) offshore energy Strategic Environmental Assessment Programme.Peer reviewedPostprin

A new strategic framework to structure Cumulative Impact Assessment (CIA)

Funding Information: This work was supported by Supergen Offshore Renewable Energy (ORE) Hub, funded by the Engineering and Physical Sciences Research Council (EPSRC EP/S000747/1) and the UK Department for Business, Energy & Industrial Strategy's (BEIS) offshore energy Strategic Environmental Assessment Programme. Publisher Copyright: © 2022, European Wave and Tidal Energy Conference. All rights reserved.Peer reviewedPublisher PD

Language control in regional dialect speakers – monolingual by name, bilingual by nature?

While research on bilingual language processing is sensitive to different usage contexts, monolinguals are still often treated as a homogeneous control group, despite frequently using multiple varieties that may require engagement of control mechanisms during lexical access. Adapting a language-switching task for speakers of (Scottish) Standard English and Orcadian Scots, we demonstrate switch cost asymmetries with longer naming latencies when switching back into Orcadian. This pattern, which is reminiscent of unbalanced bilinguals, suggests that Orcadian is the dominant variety of these participants - despite the fact they might be regarded as English monolinguals because of sociolinguistic factors. In conjunction with the observed mixing cost and cognate facilitation effect (indicative of proactive language control and parallel language activation, respectively), these findings show that ‘monolinguals’ need to be scrutinised for routine use of different varieties to gain a better understanding of whether and how mechanisms underlying their lexical access resemble those of bilinguals

Ontology Lexicalisation: The lemon Perspective

Ontologies (Guarino1998) capture knowledge but fail to capture the structure and use of terms in expressing and referring to this knowledge in natural language. The structure and use of terms is the concern of terminology as well as lexicology. In recent years, the relevance of terminology in knowledge representation has been recognized again (for example the advent of SKOS1) but less consideration has been given to lexical and linguistic issues in knowledge representation (Buitelaar2010)

Positron emission tomography PET/CT harmonisation study of different clinical PET/CT scanners using commercially available software

Objectives: Harmonisation is the process whereby standardised uptake values from different scanners can be made comparable. This PET/CT pilot study aimed to evaluate the effectiveness of harmonisation of a modern scanner with image reconstruction incorporating resolution recovery (RR) with another vendor older scanner operated in two-dimensional (2D) mode, and for both against a European standard (EARL). The vendor-proprietary software EQ•PET was used, which achieves harmonisation with a Gaussian smoothing. A substudy investigated effect of RR on harmonisation. Methods: Phantom studies on each scanner were performed to optimise the smoothing parameters required to achieve successful harmonisation. 80 patients were retrospectively selected; half were imaged on each scanner. As proof of principle, a cohort of 10 patients was selected from the modern scanner subjects to study the effects of RR on harmonisation. Results: Before harmonisation, the modern scanner without RR adhered to EARL specification. Using the phantom data, filters were derived for optimal harmonisation between scanners and with and without RR as applicable, to the EARL standard. The 80-patient cohort did not reveal any statistically significant differences. In the 10-patient cohort SUVmax for RR > no RR irrespective of harmonisation but differences lacked statistical significance (one-way ANOVA F(3.36) = 0.37, p = 0.78). Bland-Altman analysis showed that harmonisation reduced the SUVmax ratio between RR and no RR to 1.07 (95% CI 0.96–1.18) with no outliers. Conclusions: EQ•PET successfully enabled harmonisation between modern and older scanners and against the EARL standard. Harmonisation reduces SUVmax and dependence on the use of RR in the modern scanner. Advances in knowledge: EQ•PET is feasible to harmonise different PET/CT scanners and reduces the effect of RR on SUVmax

Interchanging lexical resources on the Semantic Web

Lexica and terminology databases play a vital role in many NLP applications, but currently most such resources are published in application-specific formats, or with custom access interfaces, leading to the problem that much of this data is in ‘‘data silos’’ and hence difficult to access. The Semantic Web and in particular the Linked Data initiative provide effective solutions to this problem, as well as possibilities for data reuse by inter-lexicon linking, and incorporation of data categories by dereferencable URIs. The Semantic Web focuses on the use of ontologies to describe semantics on the Web, but currently there is no standard for providing complex lexical information for such ontologies and for describing the relationship between the lexicon and the ontology. We present our model, lemon, which aims to address these gap