Computing in Kent

 A  new paper recently published by Dr Leishi Zhang as co-author on transparency in Artificial Intelligence systems raises some interesting questions. https://researchspace.canterbury.ac.uk/94734/the-impact-of-system-transparenc  The Impact of System Transparency on Analytical Reasoning CHI EA '23: Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems April 2023 Article No.: 274 Pages 1–6 https://doi.org/10.1145/3544549.3585786 Abstract In this paper, we present the hypothesis that system transparency is critical for tasks that involve expert sensemaking. Artificial Intelligence (AI) systems can aid criminal intelligence analysts, however, they are typically opaque, obscuring the underlying processes that inform outputs, and this has implications for sensemaking. We report on an initial study with 10 intelligence analysts who performed a realistic investigation exercise using the Pan natural language system [10, 11], in which only half were p...

  image taken from   https://technicallygames.com.au/talks/games-outside-of-games/   Work presented by Gareth Ward, Canterbury Christ Church University present at the Technically Games Conference 2022  The games industry is highly competitive and the skills needed to be successful can also be used in other sectors. This talk explored transferable skills and the link between the games industry and a whole range of future careers that are XR related and do not exist yet. To read more go to https://repository.canterbury.ac.uk/item/9338y/games-outside-of-games The presentation  https://technicallygames.com.au/talks/games-outside-of-games/

  Optimal locations and computational frameworks of FSR and IMU sensors for measuring gait abnormalities Published in  VOLUME 9, ISSUE 4 ,  E15210 ,  APRIL 2023 DOI: https://doi.org/10.1016/j.heliyon.2023.e15210 Soumya K. Manna M.A. Hannan Bin Azhar   Ann Greace    Abstract Neuromuscular diseases cause abnormal joint movements and drastically alter gait patterns in patients. The analysis of abnormal gait patterns can provide clinicians with an in-depth insight into implementing appropriate rehabilitation therapies. Wearable sensors are used to measure the gait patterns of neuromuscular patients due to their non-invasive and cost-efficient characteristics. FSR and IMU sensors are the most popular and efficient options. When assessing abnormal gait patterns, it is important to determine the optimal locations of FSRs and IMUs on the human body, along with their computational framework. The gait abnormalities of different types and the gait analysis system...