7 citations · 11 across the 8 of their papers we have counts for
6 papers · 1 filter
Unsupervised anomaly detection in spatio-temporal stream network sensor data
Edgar Santos-Fernandez, Jay M. Ver Hoef, Erin E. Peterson +6
The use of in-situ digital sensors for water quality monitoring is becoming increasingly common worldwide. While these sensors provide near real-time data for science, the data are…
Factors associated with injurious from falls in people with early stage Parkinson's disease
Sarini Abdullah, James McGree, Nicole White +2
Falls are common in people with Parkinson's disease (PD) and have detrimental effects which can lower the quality of life. While studies have been conducted to learn about falling…
Profile regression for subgrouping patients with early stage Parkinson's disease
Sarini Abdullah, James McGree, Nicole White +2
Falls are detrimental to people with Parkinson's Disease (PD) because of the potentially severe consequences to the patients' quality of life. While many studies have attempted to…
Assessing the predictive ability of the UPDRS for falls classification in early stage Parkinson's disease
Sarini Abdullah, Nicole White, James McGree +2
Identification of risk factors associated with falls in people with Parkinson's Disease (PD) is important due to their high risk of falling. In this study, various ways of utilizin…
Predicting Sediment and Nutrient Concentrations in Rivers Using High Frequency Water Quality Surrogates
Catherine Leigh, Sevvandi Kandanaarachchi, James M. McGree +4
A particular focus of water-quality monitoring is the concentrations of sediments and nutrients in rivers, constituents that can smother biota and cause eutrophication. However, th…
A framework for automated anomaly detection in high frequency water-quality data from in situ sensors
Catherine Leigh, Omar Alsibai, Rob J. Hyndman +9
River water-quality monitoring is increasingly conducted using automated in situ sensors, enabling timelier identification of unexpected values. However, anomalies caused by techni…