The definitions and characteristics of the out-of-body experience were examined. It was concluded that none of the various definitions are specific enough wRh regard to the idea of an actual physical split between the consciousness and the body. The experimental evidence was outlined, the weaknesses highlighted and alternative explanations were given. The out-of-body experience associated with ...

Outcomes-Based Education (OBE) brought about a significant paradigm shift in the education and training of learners in South Africa. OBE requires a shift from focusing on the teacher input (instruction offerings or syllabuses expressed in terms of content), to focusing on learner outcomes. OBE is moving away from 'transmission' models to constructivistic, learner-centered models that put emphas...

This paper considers the problems of channel estimation and adaptive equalization in the novel framework of set-membership parameter estimation. Channel estimation using a class of set-membership identiication algorithms known as optimal bounding ellipsoid (OBE) algorithms and their extension to track time-varying channels are described. Simulation results show that the OBE channel estimators o...

The theoretical significance of out-of-body experiences in blind people is explored. In this context I report results of a survey of a small sample of blind adults. It is concluded that we have yet to locate a case of an out-ofbody experience in the blind that has critical implications for the interpretation of the experience among the general population. Instances of the out-of-body experience...

Self-processing has been related to the prefrontal cortex (PFC) and the temporo-parietal junction (TPJ) as well as to their connectivity. So far, out-of-body experiences (OBEs), impressive transient deviations of intact bodily self-integration, could be associated with the TPJ, but the mediation by the frontal lobe, and thus fronto-parietal connectivity, is yet unknown. Thus, we assessed switch...

Optimal Bounding Ellipsoid (OBE) algorithms offer an attractive alternative to traditional least squares methods for identifying linear-in-parameters signal and system models due to their low computational efficiency, superior tracking ability, and selective updating that permits processor sharing among tasks. These benefits are further enhanced by multiweight optimization (MWO) which yields im...