Conference or Workshop Item

Ruvinga, Stenford, Hunter, Gordon, Nebel, Jean-Christophe, Duran, Olga and Busquets, Rosa (2022) Monitoring and predicting important events in honeybee hives using acoustic signals and machine learning. In: UKAN+ Monitoring UK Biodiversity Symposium; 15 - 16 Jun 2022, Manchester, U.K.. (Unpublished)

Ruvinga, Stenford, Hunter, Gordon, Nebel, Jean-Christophe and Duran, Olga (2022) Prediction of honeybee swarms using audio signals and convolutional neural networks. In: Workshop on Edge AI for Smart Agriculture (EAISA 2022); 20-23 Jun 2022, Biarritz, France.

Ruvinga, Stenford, Hunter, Gordon J.A., Duran, Olga and Nebel, Jean-Christophe (2021) Use of LSTM neural networks to identify 'queenlessness' in honeybee hives from audio signals. In: 17th International Conference on Intelligent Environments; 21 - 24 Jun 2021, Dubai, United Arab Emirates (held online).

Hunter, Gordon, Davis, Mastaneh and Ruvinga, Stenford (2018) A quantitative investigation into student progression in STEM subjects at a post-92 UK university. In: Demographic gaps in recruitment, retention and attainment: what is really going on?; 22 August 2018, University of Sheffield, U.K.. (Unpublished)

Ruvinga, Stenford, Davis, Mastaneh and Hunter, Gordon (2017) A statistical study of “attainment gaps” (and their causes) in students’ performance in STEM subjects at a post-1992 UK university. In: Horizons in STEM Higher Education Conference: Making Connections, Innovating and Sharing Pedagogy 2017; 29-30 Jun 2017, Edinburgh, U.K.. (Unpublished)

Thesis

Ruvinga, Stenford (2018) A quantitative investigation into "attainment gaps" within the SEC undergraduate student cohorts at Kingston University. (MSc(R) thesis), Kingston University, .