Subject - specific - frequency - band for motor imagery EEG signal recognition based on common spatial spectral pattern

Over the last decade, processing of biomedical signals using machine learning algorithms has gained widespread attention. Amongst these, one of the most important signals is electroencephalography (EEG) signal that is used to monitor the brain activities. Brain-computer-interface (BCI) has also become a hot topic of research where EEG signals are usually acquired using non-invasive sensors. In this work, we propose a scheme based on common spatial spectral pattern (CSSP) and optimization of temporal filters for improved motor imagery (MI) EEG signal recognition. CSSP is proposed as it improves the spatial resolution while the temporal filter is optimized for each subject as the frequency band which contains most significant information varies amongst different subjects. The proposed scheme is evaluated using two publicly available datasets: BCI competition III dataset IVa and BCI competition IV dataset 1. The proposed scheme obtained promising results and outperformed other state-of-the-art methods. The findings of this work will be beneficial for developing improved BCI systems

Cobalt impregnated pillared montmorillonite in the peroxymonosulfate induced catalytic oxidation of tartrazine

Aluminum pillared montmorillonite impregnated with cobalt (CoAP) was synthe-sized and characterized using chemical analysis, XRD and N-2-physisorption. CoAP was tested as a catalyst in the peroxymonosulfate (Oxone (R)) induced catalytic degradation of tartrazine. The influence of Oxone (R)/catalyst ratio and temperature on CoAP catalytic performance was investigated. The UV-Vis spectra obtained after predetermined periods of time of reaction were analyzed in order for tartrazine solution composition to be monitored. The reaction was more efficient at 50 degrees C than at 30 degrees C and the presence of new peaks for the reaction at 50 degrees C was observed. The peaks were deconvoluted and further analyzed. The intensity of two characteristic peaks gradually decreased during the investigated reaction following the first order kinetics. Newly formed peaks indicated the formation of degradation products. The initial increase of the intensity of some of them was followed by certain decrease as the reaction proceeded. CoAP was found to be efficient catalyst in Oxone (R) induced catalytic decolorization of tartrazine. The degradation of different products formed in tartrazine oxidation was evidenced