Search for: All records

Benchmark and system parameters often have a significant impact on performance evaluation, which raises a long-lasting question about which settings we should use. This paper studies the feasibility and benefits of extensive evaluation. A full extensive evaluation, which tests all possible settings, is usually too expensive. This work investigates whether it is possible to sample a subset of the settings and, upon them, generate observations that match those from a full extensive evaluation. Towards this goal, we have explored the incremental sampling approach, which starts by measuring a small subset of random settings, builds a prediction model on these samples using the popular ANOVA approach, adds more samples if the model is not accurate enough, and terminates otherwise. To summarize our findings: 1) Enhancing a research prototype to support extensive evaluation mostly involves changing hard-coded configurations, which does not take much effort. 2) Some systems are highly predictable, which means that they can achieve accurate predictions with a low sampling rate, but some systems are less predictable. 3) We have not found a method that can consistently outperform random sampling + ANOVA. Based on these findings, we provide recommendations to improve artifact predictability and strategies for selecting parameter values during evaluation. 

We herein report the fabrication of a Velcro-mimicking surface based on polymer brushes. Using poly(ε-caprolactone) (PCL) as the model polymer, polymer loop brushes (PLBs) and singly tethered polymer brushes (STPBs) with nearly identical tethering point density and brush heights were synthesized using a polymer single crystal (PSC)-assisted grafting-to method. Atomic force microscopy-based single molecular force spectroscopy (AFM-SMFS) and macroscale lap-shear experiments both demonstrated that the PLBs led to strong adhesion that is up to ∼10 times greater than the STPBs, which is attributed to the enriched chain entanglement between the probing polymer and the brushes. We envisage that our results will pave the way towards a new materials design for strong adhesives and nanocomposites.