1,721,228 research outputs found
Assessing privacy-friendly local open-source voice annotation for participants with Parkinson’s disease
Full text linkThere is significant potential clinical benefit to be gained in capturing symptom data from individuals with Parkinson’s Disease (PD). For this purpose, sensor data is often collected. However, labels (ground truth) data is also beneficial, both to train (supervised learning) and to validate outcomes from automated monitoring systems. With the increasing use of voice assistants, this modality has been proposed for labelling. In this study, we examine some design patterns for voice-agent-supported labelling, identify failure modes, and make use of the MDVR-KCL dataset to benchmark a widely used key component, a speech-to-text pipeline. We identify that this component shows rapid increase in several error metrics (WER, CER, WIL) when employed on data from mildly symptomatic participants. We identify some potential mitigating steps and discuss potential future work
Annotation and label validation of upper-tier tribunal decisions in immigration law
Full text linkUpper tribunal decisions form a vital component of the immigration appeal system in the United Kingdom (UK), since these decisions often act as a ‘corrective’ to initial judicial decision-making by the first-tier tribunal. This paper describes the process of annotating a corpus drawn from the UK’s Upper Tribunal Immigration and Asylum Chamber (UTIAC) decisions openly published by the tribunal, covering the years 2000 to 2021. A label taxonomy is developed and applied by two annotators for annotation of several types of features, including decision outcomes and the presence of and type of legal errors identified by the tribunal. Annotations were implemented via a low-cost, high-accessibility tool and validated calculating inter-annotator agreement. We discuss the pros and cons of our annotation tool and also critically reflect on annotator background. We successfully used the produced ground truth for supervised machine learning classification tasks, adding further confidence to the suitability of annotations for said tasks. We are considering ethics and data protection compliant ways to safely make the corpus and annotations available for future work
User perspectives of metadata use in electronic laboratory notebooks
No full textThe drive towards more transparency in research and open data increases the importance of being able to find information and make links to the data. The amount of electronic data produced and the move away from the familiar and convenient paper notebook to electronic lab notebooks (ELNs) provides more scope for sharing information, but also makes it more difficult to find. Machine generated metadata helps with sharing across software and systems and also assists with retrieval for machines, but not necessarily in a form friendly for the humans that need it. Metadata is an essential ingredient for use in ELNs to make experiment data and associated notes and interpretations easier to retrieve and more organized. Electronic lab notebooks and other recording software captures useful metadata like date, time, and location, but are reliant upon users to add meaningful metadata like topic and person after the recording process.The University of Southampton has developed an ELN that enables users to add their own metadata to notebook entries. A survey of 110 of these ELNs was completed to assess user behavior and patterns of metadata usage within ELNs. In addition, the user perceptions and expectations of metadata in ELNs were gathered through user interviews and user testing activities of different groups. The findings from both indicate that whilst some groups are comfortable with metadata and are able to design a metadata structure that works effectively, many users have no knowledge of where to start to define metadata or even an understanding of what it is, and why it is useful.Strategies for encouraging and improving metadata use in ELNs from the study findings including improving interface design, user education, standard schema designs, and encouraging collaboration between same discipline groups to promote consistency and best practices.<br/
Real life learning projects: Do students really like them?
No full textResearch tells us that education provides a backdrop for the real world. However, students need to practice and practice what is learnt. This research presents how an innovative learning project utilising real life clients for undergraduate students, and determined that students gained real life learning skills and experiences. Male students were significantly more likely than females to agree that real life projects helped them develop strong powers of understanding and reasoning skills. Female students were significantly more likely to agree that the project helped them develop their interpersonal skills. Experiences gained were that real life projects added value and exceeded their expectations, the role that the students played was useful and the project was real, gaining tangible benefits
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
Chris Koch (Volumnia), Rob Pensalfini (Coriolanus) in the Queensland Shakespeare Ensemble's 'Coriolanus', 2003
No full textPhotographs of productions of 'As You Like It', 'Pericles', 'Coriolanus' and 'The Madness of King Lear'; programs of 'The Two Gentlemen of Verona', 'Coriolanus' and 'The Madness of King Lear' and advertising flyers for 'The Two Gentlemen of Verona' and 'Coriolanus'. Photograph descriptions provided by the Queensland Shakespeare Ensemble
Suzanne Little (Rosalind), Matthew Clowes (Orlando) in the Queensland Shakespeare Ensemble's 'As You Like It', 2002
No full textPhotographs of productions of 'As You Like It', 'Pericles', 'Coriolanus' and 'The Madness of King Lear'; programs of 'The Two Gentlemen of Verona', 'Coriolanus' and 'The Madness of King Lear' and advertising flyers for 'The Two Gentlemen of Verona' and 'Coriolanus'. Photograph descriptions provided by the Queensland Shakespeare Ensemble
Stephen Daniels, Carolyn Davies, David Keirnan (servants to Aufidius) in the Queensland Shakespeare Ensemble's 'Coriolanus', 2003
No full textPhotographs of productions of 'As You Like It', 'Pericles', 'Coriolanus' and 'The Madness of King Lear'; programs of 'The Two Gentlemen of Verona', 'Coriolanus' and 'The Madness of King Lear' and advertising flyers for 'The Two Gentlemen of Verona' and 'Coriolanus'. Photograph descriptions provided by the Queensland Shakespeare Ensemble
Rob Pensalfini (Coriolanus) in the Queensland Shakespeare Ensemble's 'Coriolanus', 2003
No full textPhotographs of productions of 'As You Like It', 'Pericles', 'Coriolanus' and 'The Madness of King Lear'; programs of 'The Two Gentlemen of Verona', 'Coriolanus' and 'The Madness of King Lear' and advertising flyers for 'The Two Gentlemen of Verona' and 'Coriolanus'. Photograph descriptions provided by the Queensland Shakespeare Ensemble
- …
