It is greatly appreciated for researchers to acknowledge Research Computing Services in publications on research that used resources provided by Research Computing Services. These resources include, but are not limited to, the following:
- Computing or storage hardware
- Expertise, guidance or other support from our Research Computing Specialist
- Expertise or custom research software developed by our Research Software Development team
- Significant support from our System Administrator
The exact text of the acknowledgement will likely depend on the publication, but the following can be used as a starting point:
“This research was enabled in part by support provided by Research Computing Services (https://carleton.ca/rcs) at Carleton University.”
If you would like to include any details about the specific hardware you used please contact RCS and we can help you with a description. If you received significant support from any individual RCS team members, it would be greatly appreciated to acknowledge them by name. Lastly, it would be appreciated if you could please send us a reference of any publication which acknowledges RCS.
Published Work Acknowledging RCS
- Hobson, B.W., Markus, A.A., Gunay, H.B., Rizvi, F., “Minimum Sensor Grid Density and Configuration to Enable CO2-based Demand-Controlled Ventilation in an Office Building,” Energy and Buildings, Vol. 298, 2023
- Hovell, K., Ulrich, S., and Bronz, M., “Learned Multiagent Real-Time Guidance with Applications to Quadrotor Runway Inspection,” Field Robotics, Vol. 2, 2022, pp. 1105-1133.
- Hovell, K., and Ulrich, S., “Laboratory Experimentation of Spacecraft Robotic Capture using Deep Reinforcement Learning-based Guidance,” AIAA Journal of Guidance, Control, and Dynamics, Vol. 45, No. 11, 2022, pp. 2138-2146.
- Hovell, K., and Ulrich, S., “Laboratory Experimentation of Spacecraft Robotic Capture Using Deep Reinforcement Learning-based Guidance,” 33rd AAS/AIAA Space Flight Mechanics Meeting, Austin, TX, 2023.
- Romero, J., Islam, MD T., Taylor, R., Grayson, C., Schoenrock, A., and Wong, A., “High-throughput design of bacterial antisense RNAs using CAREng”, Bioinformatics Advances, Vol. 2, Issue 1, 2022