It was further numerically demonstrated and benchmarked on both small- and large-scales, regarding the effectiveness and the scalability of TPC.
Using protein-stabilised oil-in-water model emulsions, the use of a partial least squares and a multi-linear regression approach for processing and analysis of time-domain NMR data is demonstrated, and benchmarked against the deployment of NIR spectroscopy.
To demonstrate this capability and benchmark 3DMGs, we have fabricated honeycomb-like MG architectures covering a wide range of relative densities.
The impact of different geometrical parameters on the load-carrying capacity is demonstrated and the design approaches are benchmarked against a large number of individual test results.
The framework developed forms the basis of a finite element implementation and is demonstrated on benchmark problems designed to bring out effects such as strengthening and hardening.
This has immediate implications for the scalability of subspace segmentation, which we demonstrate on a benchmark face recognition dataset and in simulations.
The advantages of proposed control scheme are demonstrated by benchmark simulation and reversed engineered industrial applications.
The methodology is applied and demonstrated on two benchmark networks.
The approach is demonstrated with benchmark examples of structure optimization and compliant mechanism design.
Experimental results based on synthetic dataset and benchmark datasets demonstrate the better performance of our method over other related methods.
