A5050873951- Maritime Navigation and Safety
- EEG and Brain-Computer Interfaces
- Remote-Sensing Image Classification
- Target Tracking and Data Fusion in Sensor Networks
- Ship Hydrodynamics and Maneuverability
- Spectroscopy and Chemometric Analyses
- Time Series Analysis and Forecasting
- Neural dynamics and brain function
- Remote Sensing in Agriculture
- Bayesian Modeling and Causal Inference
- Blind Source Separation Techniques
Stellenbosch University
2020-2022
• A combination of ICA and WNN is introduced to eliminate EOG artefacts. This method corrects only artefacts within a contaminated component. Minimal low frequency underlying cerebral activity lost. EEG quality increased. Eye has larger electrical potential than the average electroencephalogram (EEG) recording, thus making it one major sources Ocular (OA) must be removed as completely possible with little or no loss obtain higher EEG. Using independent component analysis (ICA), separated...
Automatic Identification System (AIS) is one of the most prominent systems for monitoring vessel activity. Although significant advances in AIS coverage have been achieved recent times, a will typically still experience gaps reception within its voyage. These can vary from few seconds to multiple hours depending on route. A typical approach when dealing with these vessel's voyage move pointal domain trajectory using prediction algorithm. In this paper, we compare performance two algorithms...
As maritime activities increase globally, there is a greater dependency on technology in monitoring, control, and surveillance of vessel activity. One the most prominent systems for monitoring activity Automatic Identification System (AIS). An both vessels fitted with AIS transponders satellite terrestrial receivers has resulted significant messages received globally. This resultant rich spatial temporal data source related to provides analysts ability perform enhanced movement analytics,...
In this paper we present a novel hypertemporal unsupervised sequential classification algorithm. We illustrate the usefulness of algorithm at hand case study. For our study, consider Moderate Resolution Imaging Spectroradiometer dataset containing two prominent South Afrcian land cover classes, namely natural vegetation and settlement. study considered in paper, proposed approach performed on average 1.33 times better than conventional k-means.