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Continuously indexed Gaussian fields (GFs) are the most important ingredient in spatial statistical modelling and geostatistics. The specification through the covariance function gives an intuitive interpretation of the field properties. On the computational side, GFs are hampered with the big n problem, since the cost of factorizing dense matrices is cubic(More)
Continuously indexed Gaussian fields (GFs) is the most important ingredient in spatial statistical modelling and geo-statistics. The specification through the covariance function gives an intuitive interpretation of its properties. On the computational side, GFs are hampered with the big-n problem, since the cost of factorising dense matrices is cubic in(More)
We analyze the performance of a novel human tracking system, which uses the electric near field to sense human presence. The positioning accuracy with moving targets is measured using raw observations, observation centroids and Kalman filtered centroids. In addition to this, the multi-target discrimination performance is studied with two people and a(More)
A novel approach to background/foreground segmentation using an online EM algorithm is presented. The method models each layer as a Gaussian mixture, with local, per pixel, parameters for the background layer and global parameters for the foreground layer, utilising information from the entire scene when estimating the foreground. Additionally, the online(More)
AIMS To collect information on the use of the Reveal implantable loop recorder (ILR) in the patient care pathway and to investigate its effectiveness in the diagnosis of unexplained recurrent syncope in everyday clinical practice. METHODS AND RESULTS Prospective, multicentre, observational study conducted in 2006-2009 in 10 European countries and Israel.(More)
BACKGROUND Cohort studies of the relationship between air pollution exposure and chronic health effects require predictions of exposure over long periods of time. OBJECTIVES We developed a unified modeling approach for predicting fine particulate matter, nitrogen dioxide, oxides of nitrogen, and black carbon (as measured by light absorption coefficient)(More)
OBJECTIVE The aim of the study was to investigate how motion sickness, triggered by an optokinetic drum, affects short-term memory performance and to explore autonomic responses to perceived motion sickness. BACKGROUND Previous research has found that motion sickness decreases performance, but it is not known how short-term memory in particular is(More)
The development of models that provide accurate spatio-temporal predictions of ambient air pollution at small spatial scales is of great importance for the assessment of potential health effects of air pollution. Here we present a spatio-temporal framework that predicts ambient air pollution by combining data from several different monitoring networks and(More)
Continuously indexed Gaussian fields (GFs) is the most important ingredient in spatial statistical modelling and geo-statistics. The specification through the covariance function gives an intuitive interpretation of its properties. On the computational side, GFs are hampered with the big-n problem, since the cost of factorising dense matrices is cubic in(More)