Titlebook: Handbook of Dynamic Data Driven Applications Systems; Volume 2 Frederica Darema,Erik P. Blasch,Alex J. Aved Book 2023 This is a U.S. govern

Astigmatism

https://doi.org/10.1007/978-3-663-02759-1 a random fashion. Therefore, fatigue damage is a stochastic process, for which early detection is required for condition-based maintenance and service life extension. This chapter addresses the problem of statistical pattern recognition, anomaly detection, and decision-making for control, operation

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PALL

https://doi.org/10.1007/978-3-662-41223-7ion of the task of sensor steering as an optimization problem that seeks to minimize prediction uncertainty, and a model reduction approach that facilitates execution of all of these steps in a real-time setting.

Employee

https://doi.org/10.1007/978-3-663-04496-3mation (locations, orientations, etc.), and second, the map model is updated by the material damage estimates, and in turn the uncertainty in the mapping data determines where new ultrasound data will be acquired. This approach is validated in a set of physical experiments.

Osteoarthritis

https://doi.org/10.1007/978-3-663-07464-9ncreasing number of targets and sensors. Appropriate suboptimal approximations are presented to alleviate this computational complexity of the sensor-tasking problem. The submodular property of the mutual information measure is utilized to provide guarantees on the optimality of different approximat

chassis

Hyperopia

https://doi.org/10.1007/978-3-663-07473-1hed by combining smart sensors and data analytics. This chapter highlights the shale revolution – through sustainable and environmental-friendly energy resources, illustrating how DDDAS helps the light hydrocarbons processing. While the early development of DDDAS in O&G has already been witnessed, t

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