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Scope and arbitration in machine learning clinical EEG classification (2023)
Conference Proceeding
Zhu, Y., Canham, L., & Western, D. (2023). Scope and arbitration in machine learning clinical EEG classification. In 2023 IEEE Signal Processing in Medicine and Biology Symposium (SPMB). https://doi.org/10.1109/SPMB59478.2023.10372635

A key task in clinical EEG interpretation is to classify a recording or session as normal or abnormal. In machine learning approaches to this task, recordings are typically divided into shorter windows for practical reasons, and these windows inherit... Read More about Scope and arbitration in machine learning clinical EEG classification.

Understanding people's perceptions of their liveable neighbourhoods: A case study of East Bristol (2023)
Conference Proceeding
Covato, E., & Jeawak, S. (2023). Understanding people's perceptions of their liveable neighbourhoods: A case study of East Bristol. . https://doi.org/10.4230/LIPIcs.GIScience.2023.24

Liveable neighbourhoods are urban planning initiatives that aim to improve the quality of residential areas. In this paper, we focus on the East Bristol Liveable Neighbourhood (EBLN) to understand people’s perceptions of their neighbourhood’s urban r... Read More about Understanding people's perceptions of their liveable neighbourhoods: A case study of East Bristol.

Enhancing software fault prediction with deep neural networks: An empirical analysis of error-type metrics (2023)
Conference Proceeding
Phung, K., Ogunshile, E., & Aydin, M. E. (in press). Enhancing software fault prediction with deep neural networks: An empirical analysis of error-type metrics.

In the context of software quality assurance, Software Fault Prediction (SFP) serves as a critical technique to optimise costs and efforts by classifying software modules as faulty or not, using pertinent project characteristics. Despite considerable... Read More about Enhancing software fault prediction with deep neural networks: An empirical analysis of error-type metrics.

Computer vision and IoT research landscape for health and safety management on construction sites (2023)
Journal Article
Arshad, S., Akinade, O., Bello, S., & Bilal, M. (2023). Computer vision and IoT research landscape for health and safety management on construction sites. Journal of Building Engineering, 76, Article 107049. https://doi.org/10.1016/j.jobe.2023.107049

Aims: Perform a systematic review of current literature to evaluate and summarise the health and safety hazards on construction sites. Methods: Science Direct, SCOPUS and web of science databases were searched for research articles published from 201... Read More about Computer vision and IoT research landscape for health and safety management on construction sites.

Deep learning-based multi-target regression for traffic-related air pollution forecasting (2023)
Journal Article
Akinosho, T. D., Bilal, M., Hayes, E. T., Ajayi, A., Ahmed, A., & Khan, Z. (2023). Deep learning-based multi-target regression for traffic-related air pollution forecasting. Machine Learning with Applications, 12, Article 100474. https://doi.org/10.1016/j.mlwa.2023.100474

Traffic-related air pollution (TRAP) remains one of the main contributors to urban pollution and its impact on climate change cannot be overemphasised. Experts in developed countries strive to make optimal use of traffic and air qua... Read More about Deep learning-based multi-target regression for traffic-related air pollution forecasting.

Personalised learning through context-based adaptation in the serious games with gating mechanism (2023)
Journal Article
Shum, L. C., Rosunally, Y., Scarle, S., & Munir, K. (2023). Personalised learning through context-based adaptation in the serious games with gating mechanism. Education and Information Technologies, 28(10), 13077-13108. https://doi.org/10.1007/s10639-023-11695-8

When the traditional "one size fits all" approach is used in designing educational games, the game context is usually arranged in a fixed sequence. However, the designated content may not effectively support the diversity of players. The player's abi... Read More about Personalised learning through context-based adaptation in the serious games with gating mechanism.

10 is the safest number that there's ever been (2022)
Journal Article
Ritchie, F. (2022). 10 is the safest number that there's ever been. Transactions on data privacy, 15(2), 109-140

When checking frequency and magnitude tables for disclosure risk, the cell threshold (the minimum number of observations in each cell) is a crucial parameter. In rules-based environments, this is a hard limit on what can or can't be published. In pri... Read More about 10 is the safest number that there's ever been.