Richard Picking
Glyndŵr University
21 Papers
157 Citations
Richard Picking is an academic researcher from Glyndŵr University. The author has contributed to research in topics: Computer science & Smart environment. The author has an hindex of 6, co-authored 21 publications. Previous affiliations of Richard Picking include University of Wales & University of Zaragoza.
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Papers
User Modelling in Ambient Intelligence for Elderly and Disabled People
Roberto Casas,Rubén Blasco Marín,Alexia Robinet,Armando Roy Delgado,Armando Roy Yarza,John McGinn,Richard Picking,Vic Grout +7 more
- 09 Jul 2008
TL;DR: An intelligent system with a monitoring infrastructure that will help mainly elderly users with impairments to overcome their handicap and create a safe and intuitive environment that will facilitate the achievement of household tasks in order to preserve independence of elderly residents for a while longer is presented.
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Supervised machine learning for audio emotion recognition
TL;DR: It was found that a small number of strong correlations exist between the features and that a greater number of features contribute significantly to the predictive power of emotional valence, rather than arousal.
Assessing Wellbeing in People Living with Dementia Using Reminiscence Music with a Mobile App (Memory Tracks): A Mixed Methods Cohort Study
Stewart Cunningham,Stewart Cunningham,Mark Brill,J. Harry Whalley,Rebecca Read,Gordon Anderson,Sarah Edwards,Richard Picking +7 more
TL;DR: The qualitative results suggest that use of the mobile app produced positive changes in terms of behaviour, ability, and routine in the life of residents living with dementia.
Robot companion cats for people at home with dementia: a qualitative case study on companotics
TL;DR: The analysis suggests that benefits of the robot pet were evident, and although this was a small-scale study, where they were accepted, robot pets provided positive outcomes for the participants and their families.
Using the metagraph approach for addressing RDF knowledge representation limitations
Valeriy M. Chernenkiy,Yuriy E. Gapanyuk,Anatoly Nardid,Maria Skvortsova,Anton V. Gushcha,Yuriy S. Fedorenko,Richard Picking +6 more
- 09 Nov 2017
TL;DR: It is shown that the metagraph model addresses RDF limitations in a natural way without emergence loss and allows clear and emergent description of the examined problems.