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Biomedical subjects

M A Lund

Publications and source records attributed to M A Lund.

7 recordsLinked to original sources

Removing filterable reactive phosphorus from highly coloured stormwater using constructed wetlands.

A constructed wetland design, consisting of 16 repeating cells was proposed for Henley Brook (Perth, Western Australia) to optimise the removal of FRP from urban stormwater. Three replicate experimental ponds (15 x 5 m), were constructed to represent at a 1:1 scale a single cell from this design. Three 5 m zones of each pond were sampled: shallow (0.3 m) vegetated (Schoenoplectus validus) inflow and outflow zones and a deeper (1 m), V-shaped central zone. In 1998/99, inflows and outflow waters were intensively sampled and analysed for FRP and Total P. In addition, all major pools of P (plants, sediment) within the ponds, and important P removal processes (benthic flux, uptake by biofilm and S. validus) were quantified. A removal efficiency of 5% (1998) and 10% (1999) was obtained for FRP. Initial uptake was mainly in plant biomass, although the sediment became an increasingly important sink. Benthic flux experiments showed that anoxia did not cause release of P from sediments, indicating that most of the P was bound as apatite rather than associated with Fe or Mn. The highly coloured waters were believed responsible for the very low biofilm biomass recorded (<1 g x m(-2)). We have demonstrated that constructed wetlands can be effective for removing FRP immediately after construction, although their long-term removal capacity needs further research.

Biodegradation, Environmental↗

A robust sequential test for text-independent speaker verification.

A robust speaker verification algorithm based on sequential hypothesis testing is presented. In speaker verification, the system performance is severely degraded by deviations from the nominal statistical speaker models caused by insufficient training data, varying microphone and transmission line characteristics, and different levels and types of background noise. Historically, this problem has been addressed by using an empirical method to determine an adequate decision threshold for a desired operating point. The robust detection algorithm presented here is based on a minimax criterion, such that the worst-case performance over a class of distributions is minimized. The sequential test provides further robustness by using additional data if a decision cannot be reached with the desired level of confidence. The sequential detector has been implemented and tested on a realistic database collected specifically for this purpose, and the performance has been shown to be comparable to or better than that of the corresponding heuristic detectors previously described in the literature.

Algorithms↗