A MACHINE LEARNING-BASED APPROACH TO EPILEPTIC SEIZURE PREDICTION USING ELECTRO-ENCEPHALOGRAPHIC SIGNALS.

The brain is made up of billions of neurons, which control all actions performed by us. In epilepsy, the pattern order of brain signals is altered, causing epileptiform discharges in an individual's brain. Approximately 1% of the world population has epilepsy and, therefore, there is a need for studies that can help in the diagnosis and treatment of this disorder.

Development of an electronic nose to characterize odours emitted from different stages in a wastewater treatment plant.

Wastewater treatment plants have widely been described as a significant source of odour nuisance, which has led to an increase of neighbourhood complaints. Therefore, to mitigate the negative impact of odours, the detection and analysis of these emissions are required. This paper presents a measurement system based on an electronic nose for quantitative and qualitative odour analysis of samples collected from six different stages on a wastewater plant.