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39 results

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  • WeedScan, a weed reporting system for Australia using an image classification model for identification

  • Alexander N. Schmidt-Lebuhn, Matt Bell, Carsten Eckelmann, Dane Evans, Andreas Glanznig, Rongxin Li, Andrew Mitchell, Tomas Mitchell-Storey, Michael Newton, Liam O’Duibhir, Richard Southerton, Emily Thomas, Hanwen Wu
  • Journal:
    Invasive Plant Science and Management / Volume 17 / Issue 3 / September 2024
    Published online by Cambridge University Press:
    14 November 2024, pp. 219-227
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  • Fast and efficient identification is critical for reducing the likelihood of weed establishment and for appropriately managing established weeds. Traditional identification tools require either knowledge of technical morphological terminology or time-consuming image matching by the user. In recent years, deep learning computer vision models have become mature enough to enable automatic identification. The major remaining bottlenecks are the availability of a sufficient number of high-quality, reliably identified training images and the user-friendly, mobile operationalization of the technology. Here, we present the first weed identification and reporting app and website for all of Australia. It includes an image classification model covering more than 400 species of weeds and some Australian native relatives, with a focus on emerging biosecurity threats and spreading weeds that can still be eradicated or contained. It links the user to additional information provided by state and territory governments, flags species that are locally reportable or notifiable, and allows the creation of observation records in a central database. State and local weed officers can create notification profiles to be alerted of relevant weed observations in their area. We discuss the background of the WeedScan project, the approach taken in design and software development, the photo library used for training the WeedScan image classifier, the model itself and its accuracy, and technical challenges and how these were overcome.

  • Investigating designers’ preferred learning media to design for additive manufacturing

  • Martins Obi, Patrick Pradel, Matt Sinclair, Richard Bibb, Mark Evans
  • Journal:
    Proceedings of the Design Society / Volume 4 / May 2024
    Published online by Cambridge University Press:
    16 May 2024, pp. 1779-1788
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  • In this exploratory study, designers’ preferred learning media in learning to design for Additive Manufacturing was explored. Furthermore, by deploying an online survey questionnaire, factors such as years of experience, and the categories of products designed were explored to understand how they influence designers’ learning media with a response from 201 respondents. The results show that designers have learned how to design for AM through experimentation and present the first step towards developing an appropriate Design for Additive Manufacturing knowledge dissemination approach.

  • 7 Day Follow-Up Arrangements Following Discharge From Psychiatric Hospital; How Do We Perform?

  • Jemima Alston, Rozet Balliou, Naomi Erlebach, Zach Evans, Anna Grieve, Silas Hand, Shreya Jindal, Phei Yi Lim, Matt Shaw, Chukyi Wama, Ben Meadowcroft, Douglas Murdie
  • Journal:
    BJPsych Open / Volume 8 / Issue S1 / June 2022
    Published online by Cambridge University Press:
    20 June 2022, p. S141
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  • Aims

    The first 7 days following discharge from inpatient to community psychiatric services is a period that is associated with an increased risk of suicide. NICE Guideline 53 recommends that patients discharged from inpatient psychiatric services should be reviewed by relevant community services within 7 days. We aim to determine how different teams in NHS Lothian performed in meeting this recommendation, and to ascertain the outcome of a specific intervention in North-West Edinburgh (NW).

    Methods

    We collected data of NW, North-East (NE), South-West (SW), South-East (SE) Edinburgh, East Lothian and Midlothian patients discharged from General Adult Psychiatry wards in the Royal Edinburgh Hospital for the calendar year of 2021. East and Midlothian were used as a comparison to Edinburgh services as the former have an integrated inpatient and community team.

    The data focused on the percentage of patients followed-up within 7 days of discharge. We also collected data for all NW CMHT patients discharged between January 2018 and November 2021 to analyse the intervention of using ‘Estimated Discharge Dates’ in ward rounds implemented in June 2020. Data were collected from NHS Lothian Analytical Services and anonymised in line with NHS Information Governance Policy.

    Furthermore, qualitative data were collected anonymously from staff within NHS Lothian in the form of an online questionnaire to ascertain strengths and weaknesses of the current systems.

    Results

    Over the calendar year of 2021, 1,398 patients were discharged. The average age was 41 years old.

    Regarding percentage of patients receiving 7 day follow-up, East Lothian (n = 191/249; 76.7%) and Midlothian (n = 95/122; 77.9%) performed better than Edinburgh services; NW (n = 173/268; 64.6%), NE (n = 172/301, 57.1%), SW (n = 155/247, 62.8%), SE (n = 123/211; 58.3%).

    The intervention in NW in June 2020 did not have a significant impact on 7 day follow-up.

    The questionnaire identified difficulties in transitions from inpatient to community care, particularly communication between teams.

    Conclusion

    The performance of East and Midlothian versus Edinburgh services is interesting given their integrated model. This appears to support the findings of the questionnaire.

    The lack of impact of the intervention in NW will need explored further with the team to identify difficulties.

    Rather than complete service remodelling, perhaps moving towards a more integrated approach such as allocated discharge-coordinating community and inpatient nurses would be worthwhile. We will involve the NHS Lothian Quality Improvement team in exploring this to improve patient outcomes.

The Babel Lexicon of Language
  • Dan McIntyre, Lesley Jeffries, Matt Evans, Hazel Price, Erica Gold
  • Published online:
    15 June 2022
    Print publication:
    09 June 2022
  • What's the word that describes the process of making supportive noises when you're listening to someone? What is syntax and how does it differ from grammar? Do you know what a morpheme is? And did you know that it's not only an atom that has a nucleus? The Babel Lexicon of Language is an entertaining and accessible introduction to the key terminology involved in the study of language. It defines over 500 terms and uses contemporary language examples, explaining complex issues in an easy-to-understand way. Written by the expert editorial team behind Babel, the popular language magazine, and assuming no prior knowledge of linguistics, The Babel Lexicon of Language is an invaluable resource for students, teachers and anyone with an interest in language.

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