All Outputs (4)

Machine learning-enhanced acoustic emission technique for impact source identification and classification in steel pipes. (2024)
Presentation / Conference Contribution
FATUKASI O.S., ABOLLE-OKOYEAGU, J., PRATHURU, A. and SOLADEMI, O. 2024. Machine learning-enhanced acoustic emission technique for impact source identification and classification in steel pipes. Presented at the 12th Annual conference of Society of structural integrity and life (DIVK12), 17-19 November 2024, Belgrade, Serbia.

External impacts represent a prevalent source of structural damage in pipes/piping systems. Detecting and identifying the nature, and the severity of these impacts would enhance the reliability and operational safety of such critical infrastructure.... Read More about Machine learning-enhanced acoustic emission technique for impact source identification and classification in steel pipes..

Investigating the role of diversity and inclusion in STEM education in the UK. (2024)
Presentation / Conference Contribution
ABOLLE-OKOYEAGU, C.J., ONOSHAKPOR, C., AKERELE, E. and OKPU, A. 2024. Investigating the role of diversity and inclusion in STEM education in the UK. In Abstract book of proceedings of the 6th Global conference on education and teaching 2024 (GLOBALET 2024), 25-27 October 2024, Nice, France. Vilnius, Lithuania: Diamond Scientific Publishing [online], abstract number 19-4078. Available from: https://www.dpublication.com/wp-content/uploads/2024/10/19-4078.pdf

Equality Diversity and Inclusion (EDI) is a very important driver in progressing the ever-evolving fields of Science, Technology, Engineering, and Mathematics (STEM). This aspect of EDI has become increasingly prominent in the professional societies... Read More about Investigating the role of diversity and inclusion in STEM education in the UK..

Investigating AI-driven assessment tools in engineering education: enhancing personalized learning for Industry 4.0 competencies. (2024)
Presentation / Conference Contribution
ABOLLE-OKOYEAGU, C.J., MAHON, R., OKPU, A. and FERNANDO, W. 2024. Investigating AI-driven assessment tools in engineering education: enhancing personalized learning for Industry 4.0 competencies. In Abstract book of the proceedings of the 6th Global conference on education and teaching 2024 (GLOBALET 2024), 25-27 October 2024, Nice, France. Vilnius, Lithuania: Diamond Scientific Publishing [online], abstract number 30-4124. Available from: https://www.dpublication.com/wp-content/uploads/2024/10/30-4124.pdf

With Industry 4.0 constantly improving the industrial landscape, engineering education is subsequently fraught with the immediate challenge of ensuring synchrony between the ever-changing needs of automation, smart manufacturing as well as digital tr... Read More about Investigating AI-driven assessment tools in engineering education: enhancing personalized learning for Industry 4.0 competencies..

Measurement and simulation of the propagation of impulsive acoustic emission sources in pipes. (2024)
Journal Article
ABOLLE-OKOYEAGU, C.J., FATUKASI, S. and REUBEN, B. 2024. Measurement and simulation of the propagation of impulsive acoustic emission sources in pipes. Acoustics [online], 6(3), pages 620-637. Available from: https://doi.org/10.3390/acoustics6030034

Acoustic Emission (AE) testing is a non-destructive evaluation technique that has gained significant attention in pipeline monitoring. Pencil-lead breaks (PLBs) are commonly used in reproducing and characterising sensors used in AE applications and h... Read More about Measurement and simulation of the propagation of impulsive acoustic emission sources in pipes..