Abstract-To reduce the amount of data transfer in networked control systems and wireless sensor networks, measurements are usually sampled only when an event occurs, rather than synchronous in time. Today's event sampling methodologies are triggered by the current value of the sensor. State-estimators are designed to cope with such methods. In this paper we propose a sampling method in which an event is triggered depending on the reduction of the estimator's uncertainty and estimation-error. As such, communication requirements are minimized while attaining a certain errorcovariance matrix and estimation error at the state-estimator. Furthermore, it is proven that the error-covariance matrix is asymptotically bounded in case the designed sampling protocol is combined with an event-based state-estimator. An illustrative example shows that the developed protocol provides an improved state estimation, while minimizing communication between sensor and state-estimator.

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Surveillance is normally performed by humans, since it requires visual intelligence. However, this can be dull and dangerous, especially for military operations. Therefore, unmanned autonomous visual-intelligence systems are desired. In this paper, we present a novel system that can recognize human actions, which are relevant to detect operationally significant activity. Central to the system is a break-down of high-level perceptual concepts (verbs) in simpler observable events. The system is trained on 3482 videos and evaluated on 2589 videos from the DARPA Mind's Eye program, with for each video human annotations indicating the presence or absence of 48 different actions. The results show that our system reaches good performance approaching the human average response.

This paper discusses the decomposition of hostile intentions into abnormal behaviors. A list of such behaviors has been compiled for the specific case of public transport. Some of the deviant behaviors are hard to observe by people, as they are in the midst of the crowd. Examples are deviant walking patterns, prohibited actions such as taking photos and waiting without taking the train. We discuss our visual analytics algorithms and demonstrate them on CCTV footage from the Amsterdam train station.

We aimed to assess lung fluid balance before and after gradual ascent to 5150m. Lung diffusion capacity for carbon monoxide (DLCO), alveolar-capillary membrane conductance (Dm) and ultrasound lung comets (ULCs) were assessed in 12 healthy lowlanders at sea-level, and on Day 1, Day 5 and Day 9 after arrival at Mount Everest Base Camp (EBC). EBC was reached following an 8-day hike at progressively increasing altitudes starting at 2860m. DLCO was unchanged from sea-level to Day 1 at EBC, but increased on Day 5 (11±10%) and Day 9 (10±9%) vs. sea-level (P≤0.047). Dm increased from sea-level to Day 1 (9±6%), Day 5 (12±8%), and Day 9 (17±11%) (all P≤0.001) at EBC. There was no change in ULCs from sea-level to Day 1, Day 5 and Day 9 at EBC. These data provide evidence that interstitial lung fluid remains stable or may even decrease relative to at sea-level following 8days of gradual exposure to high-altitude in healthy humans.