Kai Meng Mok

Learn More
Understanding and predicting dynamic change of algae population in freshwater reservoirs is particularly important, as algae-releasing cyanotoxins are carcinogens that would affect the health of public. However, the high complex nonlinearity of water variables and their interactions makes it difficult in modeling its growth. Recently, extreme learning(More)
Multilayer perceptron (MLP), normally trained by the offline backpropagation algorithm, could not adapt to the changing air quality system and subsequently underperforms. To improve this, the extended Kalman filter is adopted into the learning algorithm to build a time-varying multilayer perceptron (TVMLP) in this study. Application of the TVMLP to model(More)
The Macau storage reservoir (MSR) has experienced algal blooms in recent years, with high levels of Cylindrospermopsis and Microcystis and detectable concentrations of cyanotoxins. To analyze the cyanotoxin-producing genotypes and relate the corresponding cyanotoxins to the water quality parameters, a quantitative real-time polymerase chain reaction was(More)
Monitoring of cyanobacteria and their toxins are traditionally conducted by cell counting, chlorophyll-a (chl-a) determination and cyanotoxin measurements, respectively. These methods are tedious, costly, time consuming, and insensitive to rapid changes in water quality and cyanobacterial abundance. We have applied and tested an online phycocyanin (PC)(More)
  • 1