Now showing items 1-10 of 185
Estimation of microphysical parameters of atmospheric pollution using machine learning
(Springer Verlag, 2018-09-27)
The estimation of microphysical parameters of pollution (effective radius and complex refractive index) from optical aerosol parameters entails a complex problem. In previous work based on machine learning techniques, ...
The Potential for Using Artificial Intelligence Techniques to Improve e-Learning Systems
There has been significant progress in the development of techniques to deliver more effective e-Learning systems in both education and commerce but our research has identified very few examples of comprehensive learning ...
Cerebellar output controls generalized spike-and-wave discharge occurence
Disrupting thalamocortical activity patterns has proven to be a promising approach to stop generalized spike-and-wave discharges (GSWDs) characteristic of absence seizures. Here, we investigated to what extent modulation ...
Dendritic Morphology Predicts Pattern Recognition Performance in Multi-compartmental Model Neurons with and without Active Conductances
In this paper we examine how a neuron’s dendritic morphology can affect its pattern recognition performance. We use two different algorithms to systematically explore the space of dendritic morphologies: an algorithm that ...
The application of machine learning to the modelling of percutaneous absorption: An overview and guide
Machine learning (ML) methods have been applied to the analysis of a range of biological systems. This paper reviews the application of these methods to the problem domain of skin permeability and addresses critically some ...
Combining machine learning and simulations of a morphologically realistic model to study modulation of neuronal activity in cerebellar nuclei
Epileptic absence seizures are characterized by synchronized oscillatory activity in the cerebral cortex that can be recorded as so-called spike-and-wave discharges (SWDs) by electroencephalogram. Although the cerebral ...