Arvind Rajan is a scholar from the School of Engineering at the Monash University Sunway Malaysia campus. Arvind’s project, “Analytical Uncertainty Evaluation of Multivariate Polynomial”, supported by Monash University Malaysia (HDR scholarship) and the Malaysia Fundamental Research Grant Scheme, extends analytical method of “Guide to the Expression of Uncertainty in Measurement (GUM)” by the development of a systematic framework – the Analytical Standard Uncertainty Evaluation (ASUE) for the analytical standard measurement uncertainty evaluation of non-linear systems. The framework is the first step towards the simplification and standardisation of the GUM analytical method for non-linear systems.
The ASUE Toolbox
The R@CMon team supported the ASUE team at Sunway in deploying the framework on the NeCTAR Research Cloud. The project has been given access to the Monash-licensed Windows Server 2012 image and Windows-optimised instance flavour for configuration of the Internet Information Services (IIS) and ASP.NET stack. The ASUE team developed and deployed the framework on NeCTAR using remote desktop access (yes once again – even from overseas!). Mathematica, specifically webMathematica is then used on the NeCTAR instance to power the web-based dynamic ASUE Toolbox. The ASUE toolbox has been published in Measurement, a journal by International Measurement Confederation (IMEKO) and IEEE Access, an open access journal:
Y. C. Kuang, A. Rajan, M. P.-L. Ooi, and T. C. Ong, “Standard uncertainty evaluation of multivariate polynomial,” Measurement, vol. 58, pp. 483-494, Dec. 2014
A. Rajan, M. P. Ooi, Y. C. Kuang, and S. N. Demidenko, “Analytical Standard Uncertainty Evaluation Using Mellin Transform,” Access, IEEE, vol. 3, pp. 209-222, 2015
“The NeCTAR Research Cloud is a great service for researchers to host their own website and share the outcome of their research with engineers, practitioners and other professional community. Honestly, if it is not for the NeCTAR Research Cloud, I doubt our team could have made it this far. The support has been incredible so far. I will continue to publish my work using this service.”
Monash University Scholar
Electrical and Computer Systems Engineering
Back in early 2014, the R@CMon team assisted SBI Australia to deploy the VISIONET (Visualizing Transcriptomic Profiles Integrated with Overlapping Transcription Factor Networks) visualisation web service on the Monash node of the NeCTAR Research Cloud. Since then, VISIONET has been further enhanced to support more complex transcription factor network topologies. To date, VISIONET has been published in two papers.
Nim, H.T., Boyd, S.E., and Rosenthal, N.A. (2014). Systems approaches in integrative cardiac biology: Illustrations from cardiac heterocellular signalling studies. Progress in Biophysics and Molecular Biology 117, 69-77.
Nim, H.T., Furtado, M.E., Costa, M.W., Rosenthal, N.A, Kitano, H., and Boyd, S.E.. (2015). VISIONET: intuitive visualisation of overlapping transcription factor networks, with applications in cardiogenic gene discovery. BMC Bioinformatics.
The R@CMon team will continue supporting SBI Australia with its plan to further develop the VISIONET web service this year.
A mere six months ago Paul Lajbcygier and his research group used R@CMon Phase 2 “specialist kit” for processing and analysing higher frequency stock data, as part of their stock price impact models study. Since then, they’ve been running extraction queries continuously and recently published a paper highlighting their latest findings while acknowledging the NeCTAR Research Cloud infrastructure.
Lajbcygier, P., Sojka, J. (2015). The Viability of Alternative Indexation when including all Costs”, International Review of Financial Analysis
The group will continue to use the high-memory instance on R@CMon Phase 2 as they progress their research pipeline and the R@CMon team will continue to support them on their journey.
“I expect that over the coming months we will fully utilise the generous resources on the Monash node of the NeCTAR Research Cloud as we extend our research into this cutting edge and exciting data intensive topic.”
Associate Professor Paul Lajbcygier
Faculty of Business and Economics
Department of Accounting and Finance
Department of Banking and Finance