Dominic T. J. O'Sullivan

Orcid: 0000-0001-7370-471X

According to our database1, Dominic T. J. O'Sullivan authored at least 12 papers between 2013 and 2022.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

Legend:

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Links

On csauthors.net:

Bibliography

2022
Using Model Selection and Reduction to Develop an Empirical Model to Predict Energy Consumption of a CNC Machine.
Proceedings of the Leveraging Applications of Formal Methods, Verification and Validation. Practice, 2022

2021
Editorial for the Special Section on Indigenous Use of Information and Communication Technologies: Information Systems and the Practice of Indigenous Self-determination.
Australas. J. Inf. Syst., 2021

Industry 4.0 driven statistical analysis of investment casting process demonstrates the value of digitalisation.
Proceedings of the 3rd International Conference on Industry 4.0 and Smart Manufacturing (ISM 2022), Virtual Event / Upper Austria University of Applied Sciences - Hagenberg Campus, 2021

2019
A Systematic Analysis of Real-World Energy Blockchain Initiatives.
Future Internet, 2019

A comparison of fog and cloud computing cyber-physical interfaces for Industry 4.0 real-time embedded machine learning engineering applications.
Comput. Ind., 2019

2018
Development and application of a machine learning supported methodology for measurement and verification (M&V) 2.0.
CoRR, 2018

2016
Utilising the Cross Industry Standard Process for Data Mining to Reduce Uncertainty in the Measurement and Verification of Energy Savings.
Proceedings of the Data Mining and Big Data, First International Conference, 2016

2015
An industrial big data pipeline for data-driven analytics maintenance applications in large-scale smart manufacturing facilities.
J. Big Data, 2015

Big data in manufacturing: a systematic mapping study.
J. Big Data, 2015

2014
A data access framework for integration to facilitate efficient building operation.
Proceedings of the 2014 IEEE Emerging Technology and Factory Automation, 2014

Implementing the Green Batch: A case study: Continuous statistical evaluation to achieve the most energy efficient and reliable process.
Proceedings of the 2014 IEEE Emerging Technology and Factory Automation, 2014

2013
Results from testing of a "cloud based" automated fault detection and diagnosis tool for AHU's.
Proceedings of 2013 IEEE 18th Conference on Emerging Technologies & Factory Automation, 2013


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