We present a technique for the rapid and reliable prediction of linear-functional outputs of coercive and non-coercive linear elliptic partial differential equations with affine parameter dependence. The essential components are: (i) rapidly convergent global reduced basis approximations – (Galerkin) projection onto a space WN spanned by solutions of the governing partial differential equation ...

In image-guided radiation therapy (IGRT), volumetric information on patient anatomy at treatment conditions is made available with in-room imaging devices capable of cone-beam CT. Setup error and inter-fraction rigid motion can be corrected online. The planning margin can therefore be reduced significantly. However, to compensate for uncertainties including organ deformation and intra-fraction ...

Thermal gradients from internal and external heat sources cause instabilities which affect the machine tool positional accuracy. Positioning error results from deformation of the machine structure due to linear thermal expansions of some machine parts combined with the thermal behaviour of associated complex discrete structures producing non linear thermal distortions. Thermal gradients due to ...

In recent years, it has been shown that multidimensional recurrent neural networks (MDRNN) perform very well in offline handwriting recognition problems like the OpenHaRT 2013 Document Image Recognition (DIR) task. With suitable writing preprocessing and dictionary lookup, our ARGUS software completed this task with an error rate of 26.27% in its primary setup. Keywords—handwriting recognition,...

The European Organization for Nuclear Research (CERN) is the largest research organization for particle physics. ALICE, short for A Large I on C ollider Experiment, serves as one of the main detectors at CERN and produces approximately 15 petabytes of data each year. The computing associated with an ALICE experiment consists of both online and offline processing. An online cluster retrieves dat...

We present reduced basis approximations and associated a posteriori error bounds for nonaffine linear time-varying parabolic partial differential equations. We employ the Empirical Interpolation Method in order to construct “affine” coefficient-function approximations of the “nonaffine” parametrized functions. To this end, we extend previous work on time-invariant functions to time-varying func...

In this paper, we study methods to enhance the precision of the online estimation process of a recently proposed approach, ensemble speaker and speaking environment modeling (ESSEM), and therefore improve its overall performance. The ESSEM approach consists of two integral phases, offline and online. In the offline phase, an ensemble environment configuration is prepared by a large collection o...

In recent years, the planning community has observed that techniques for learning heuristic functions have yielded improvements in performance. One approach is to use offline learning to learn predictive models from existing heuristics in a domain dependent manner. These learned models are deployed as new heuristic functions. The learned models can in turn be tuned online using a domain indepen...

Energy efficiency is a key concern in the design of modern computer systems. One promising approach to energyefficient computation, approximate computing, trades off output precision for energy efficiency. However, this tradeoff can have unexpected effects on computation quality. This paper presents dynamic-analysis tools to debug and monitor the quality of approximate computations. We propose ...