Conformally Mapped Polynomial Chaos Expansions for Maxwell's Source Problem with Random Input Data

Generalized Polynomial Chaos (gPC) expansions are well established for forward uncertainty propagation in many application areas. Although the associated computational effort may be reduced in comparison to Monte Carlo techniques, for instance, further convergence acceleration may be important to tackle problems with high parametric sensitivities. In this work, we propose the use of conformal maps to construct a transformed gPC basis, in order to enhance the convergence order. The proposed basis still features orthogonality properties and hence, facilitates the computation of many statistical properties such as sensitivities and moments. The corresponding surrogate models are computed by pseudo-spectral projection using mapped quadrature rules, which leads to an improved cost accuracy ratio. We apply the methodology to Maxwell's source problem with random input data. In particular, numerical results for a parametric finite element model of an optical grating coupler are given

Reservation-Based Federated Scheduling for Parallel Real-Time Tasks

This paper considers the scheduling of parallel real-time tasks with arbitrary-deadlines. Each job of a parallel task is described as a directed acyclic graph (DAG). In contrast to prior work in this area, where decomposition-based scheduling algorithms are proposed based on the DAG-structure and inter-task interference is analyzed as self-suspending behavior, this paper generalizes the federated scheduling approach. We propose a reservation-based algorithm, called reservation-based federated scheduling, that dominates federated scheduling. We provide general constraints for the design of such systems and prove that reservation-based federated scheduling has a constant speedup factor with respect to any optimal DAG task scheduler. Furthermore, the presented algorithm can be used in conjunction with any scheduler and scheduling analysis suitable for ordinary arbitrary-deadline sporadic task sets, i.e., without parallelism

CAN LAYMEN OUTPERFORM EXPERTS? THE EFFECTS OF USER EXPERTISE AND TASK DESIGN IN CROWDSOURCED SOFTWARE TESTING

In recent years, crowdsourcing has increasingly gained attention as a powerful sourcing mechanism for problem-solving in organizations. Depending on the type of activity addressed by crowdsourcing, the complexity of the tasks and the role of the crowdworkers may differ substantially. It is crucial that the tasks are designed and allocated according to the capabilities of the targeted crowds. In this pa-per, we outline our research in progress which is concerned with the effects of task complexity and user expertise on performance in crowdsourced software testing. We conduct an experiment and gath-er empirical data from expert and novice crowds that perform different software testing tasks of vary-ing degrees of complexity. Our expected contribution is twofold. For crowdsourcing in general, we aim at providing valuable insights for the process of framing and allocating tasks to crowds in ways that increase the crowdworkers’ performance. Secondly, we intend to improve the configuration of crowdsourced software testing initiatives. More precisely, the results are expected to show practition-ers what types of testing tasks should be assigned to which group of dedicated crowdworkers. In this vein, we deliver valuable decision support for both crowdsourcers and intermediaries to enhance the performance of their crowdsourcing initiatives

Glacial abrupt climate change as a multi-scale phenomenon resulting from monostable excitable dynamics

Paleoclimate proxies reveal abrupt transitions of the North Atlantic climate during past glacial intervals known as Dansgaard--Oeschger (DO) events. A central feature of DO events is a sudden warming of about 10$^{\circ}$C in Greenland marking the beginning of relatively mild phases termed interstadials. These exhibit gradual cooling over several hundred to a few thousand years until a final abrupt decline brings the temperatures back to cold stadial levels. As of now, the exact mechanism behind this millennia-scale variability remains inconclusive. Here, we propose an excitable model to explain Dansgaard-Oeschger cycles, where interstadials occur as noise-induced state space excursions. Our model comprises the mutual multi-scale interactions between four dynamical variables representing Arctic atmospheric temperatures, Nordic Seas' temperatures and sea ice cover, and the Atlantic Meridional Overturning Circulation. The model's atmosphere-ocean heat flux is moderated by the sea ice, which in turn is subject to large perturbations dynamically generated by fast-evolving intermittent noise. If supercritical, perturbations trigger interstadial-like state space excursions during which all four model variables undergo qualitative changes that consistently resemble the signature of interstadials in corresponding proxy records. As a physical intermittent process generating the noise we propose convective events in the ocean or atmospheric blocking events. Our model accurately reproduces the DO cycle shape, return times and the dependence of the interstadial and stadial durations on the background conditions. In contrast to the prevailing understanding that DO variability is based on bistability in the underlying dynamics, we show that multi-scale, monostable excitable dynamics provide a promising alternative to explain millennial-scale climate variability associated with DO events

FugueGenerator - Collaborative Melody Composition Based on a Generative Approach for Conveying Emotion in Music

(Abstract to follow