A density-based statistical analysis of graph clustering algorithm performance

This is a pre-copyedited, author-produced version of an article accepted for publication in Journal of Complex Networks following peer review. The version of record: Pierre Miasnikof, Alexander Y Shestopaloff, Anthony J Bonner, Yuri Lawryshyn, Panos M Pardalos, A density-based statistical analysis of graph clustering algorithm performance, Journal of Complex Networks, Volume 8, Issue 3, June 2020, cnaa012, https://doi.org/10.1093/comnet/cnaa012 is available online at: https://doi.org/10.1093/comnet/cnaa012© 2020 The authors. Published by Oxford University Press. All rights reserved. We introduce graph clustering quality measures based on comparisons of global, intra- A nd inter-cluster densities, an accompanying statistical significance test and a step-by-step routine for clustering quality assessment. Our work is centred on the idea that well-clustered graphs will display a mean intra-cluster density that is higher than global density and mean inter-cluster density. We do not rely on any generative model for the null model graph. Our measures are shown to meet the axioms of a good clustering quality function. They have an intuitive graph-theoretic interpretation, a formal statistical interpretation and can be tested for significance. Empirical tests also show they are more responsive to graph structure, less likely to breakdown during numerical implementation and less sensitive to uncertainty in connectivity than the commonly used measures

This is How We Do It – Pilot Validation of a Dose (CT)‐Based Control for Wastewater Disinfection with peracetic acid

In this paper, an innovative chemical dosing control technology, in which the disinfection CT dose is controlled, is presented. The paper demonstrates, through advanced modelling-based simulations as well as pilot-scale performance data, the benefits of dose-pacing control against conventional chemical dosing control strategies. The advanced model-based simulation tool is based on the comprehensive CFD model for PAA disinfection in municipal contact tanks published by Santoro et al. (2015). Field performance data was gathered by dosing PAA, using different control strategies, to secondary effluent upstream of a pilot scale serpentine chemical contact basin and monitoring influent and effluent viable fecal coliforms