Probabilistic point source inversion of strong-motion data in 3-D media using pattern recognition: A case study for the 2008 Mw5.4 Chino Hills earthquake

Despite the ever increasing availability of computational power, real-time source inversions based on physical modeling of wave propagation in realistic media remain challenging. We investigate how a nonlinear Bayesian approach based on pattern recognition and synthetic 3-D Green's functions can be used to rapidly invert strong-motion data for point source parameters by means of a case study for a fault system in the Los Angeles Basin. The probabilistic inverse mapping is represented in compact form by a neural network which yields probability distributions over source parameters. It can therefore be evaluated rapidly and with very moderate CPU and memory requirements. We present a simulated real-time inversion of data for the 2008 Mw 5.4 Chino Hills event. Initial estimates of epicentral location and magnitude are available ∼14 s after origin time. The estimate can be refined as more data arrive: by ∼40 s, fault strike and source depth can also be determined with relatively high certainty

Information modelling and semantic linking for a software workbench for interactive, time critical and self-adaptive cloud applications

Cloud environments can provide elastic, controllable on-demand services for supporting complex distributed applications. However the engineering methods and software tools used for developing, deploying and executing classical time critical applications do not, as yet, account for the programmability and controllability that can be provided by clouds, and so time-critical applications do not yet benefit from the full potential of virtualisation technologies. A software workbench for developing, deploying and controlling time-critical applications in cloud environments can address this, but needs to be able to interoperate with existing cloud standards and services in a fashion that can still adapt to the continuing evolution of the field. Semantic linking can enhance interoperability by creating mappings between different vocabularies and specifications, allowing different technologies to be plugged together, which can then be used to build such a workbench in a flexible manner. A semantic linking framework is presented that uses a multiple-viewpoint model of a cloud application workbench as a means to relate different cloud and quality of service standards in order to aid the development of time-critical applications. The foundations of such a model, developed as part of the H2020 project SWITCH, are also presented

Information modelling and semantic linking for a software workbench for interactive, time critical and self-adaptive cloud applications

Cloud environments can provide elastic, controllable on-demand services for supporting complex distributed applications. However the engineering methods and software tools used for developing, deploying and executing classical time critical applications do not, as yet, account for the programmability and controllability that can be provided by clouds, and so time-critical applications do not yet benefit from the full potential of virtualisation technologies. A software workbench for developing, deploying and controlling time-critical applications in cloud environments can address this, but needs to be able to interoperate with existing cloud standards and services in a fashion that can still adapt to the continuing evolution of the field. Semantic linking can enhance interoperability by creating mappings between different vocabularies and specifications, allowing different technologies to be plugged together, which can then be used to build such a workbench in a flexible manner. A semantic linking framework is presented that uses a multiple-viewpoint model of a cloud application workbench as a means to relate different cloud and quality of service standards in order to aid the development of time-critical applications. The foundations of such a model, developed as part of the H2020 project SWITCH, are also presented