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Chinedu I. Ossai
Chinedu I. Ossai
Faculty of Health, Arts and Design, School of Health Sciences; Department of Health Sciences and
Verified email at swin.edu.au - Homepage
Title
Cited by
Cited by
Year
Pipeline failures in corrosive environments–A conceptual analysis of trends and effects
CI Ossai, B Boswell, IJ Davies
Engineering Failure Analysis 53, 36-58, 2015
2442015
Advances in asset management techniques: An overview of corrosion mechanisms and mitigation strategies for oil and gas pipelines
CI Ossai
International Scholarly Research Notices 2012, 2012
1352012
Corrosion defect modelling of aged pipelines with a feed-forward multi-layer neural network for leak and burst failure estimation
CI Ossai
Engineering Failure Analysis 110, 104397, 2020
672020
Markov chain modelling for time evolution of internal pitting corrosion distribution of oil and gas pipelines
CI Ossai, B Boswell, I Davies
Engineering failure analysis 60, 209-228, 2016
662016
A data-driven machine learning approach for corrosion risk assessment—a comparative study
CI Ossai
Big Data and Cognitive Computing 3 (2), 28, 2019
642019
Nanostructure and nanomaterial characterization, growth mechanisms, and applications
CI Ossai, N Raghavan
Nanotechnology Reviews 7 (2), 209-231, 2018
552018
A Markovian approach for modelling the effects of maintenance on downtime and failure risk of wind turbine components
CI Ossai, B Boswell, IJ Davies
Renewable energy 96, 775-783, 2016
482016
Application of Markov modelling and Monte Carlo simulation technique in failure probability estimation—A consideration of corrosion defects of internally corroded pipelines
CI Ossai, B Boswell, IJ Davies
Engineering Failure Analysis 68, 159-171, 2016
422016
The role of AI for developing digital twins in healthcare: The case of cancer care
R Kaul, C Ossai, ARM Forkan, PP Jayaraman, J Zelcer, S Vaughan, ...
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 13 (1 …, 2023
392023
Predictive modelling of internal pitting corrosion of aged non-piggable pipelines
CI Ossai, B Boswell, IJ Davies
Journal of The Electrochemical Society 162 (6), C251, 2015
362015
Sustainable asset integrity management: Strategic imperatives for economic renewable energy generation
CI Ossai, B Boswell, IJ Davies
Renewable energy 67, 143-152, 2014
272014
Estimation of internal pit depth growth and reliability of aged oil and gas pipelines—A Monte Carlo simulation approach
CI Ossai, B Boswell, IJ Davies
Corrosion 71 (8), 977-991, 2015
262015
Pipeline corrosion prediction and reliability analysis: a systematic approach with Monte Carlo simulation and degradation models
CI Ossai
Int. J. Sci. Technol. Res 2 (3), 58-69, 2013
252013
GLCM and statistical features extraction technique with Extra-Tree Classifier in Macular Oedema risk diagnosis
CI Ossai, N Wickramasinghe
Biomedical Signal Processing and Control 73, 103471, 2022
182022
Intelligent decision support with machine learning for efficient management of mechanical ventilation in the intensive care unit–A critical overview
CI Ossai, N Wickramasinghe
International Journal of Medical Informatics 150, 104469, 2021
182021
Statistical characterization of the state-of-health of lithium-ion batteries with Weibull distribution function—A consideration of random effect model in charge capacity decay …
CI Ossai, N Raghavan
batteries 3 (4), 32, 2017
182017
Stochastic modelling of perfect inspection and repair actions for leak–failure prone internal corroded pipelines
CI Ossai, B Boswell, IJ Davies
Engineering Failure Analysis 60, 40-56, 2016
182016
Optimal renewable energy generation – Approaches for managing ageing assets mechanisms
CI Ossai
Renewable and Sustainable Energy Reviews 72, 269-280, 2017
172017
Digital twins to enable better precision and personalized dementia care
N Wickramasinghe, N Ulapane, A Andargoli, C Ossai, N Shuakat, ...
JAMIA open 5 (3), ooac072, 2022
162022
Real-time state-of-health monitoring of lithium-ion battery with anomaly detection, Levenberg–Marquardt algorithm, and multiphase exponential regression model
CI Ossai, IP Egwutuoha
Neural Computing and Applications 33 (4), 1193-1206, 2021
152021
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