The development of numerical solvers able to simulate compressible two-phase flows is still a great challenge in computational fluid dynamics. interaction between acoustic waves and interfaces major concern for several engineering biomedical applications, among which atomization combustion chambers, cavitation problems, underwater explosions bubble shock interactions. For instance, there are ex...

Numerical simulation of deformable objects is an important problem in biomechanical engineering and computational science. A significant class of problems in this area requires that the simulation results are presented both haptically and graphically in real time (an example being a medical training simulator based on virtual reality). In such cases various types of trade-offs between accuracy ...

Non-negative spectrogram factorization algorithms such as probabilistic latent component analysis (PLCA) have been shown to be quite powerful for source separation. When training data for all of the sources are available, it is trivial to learn their dictionaries beforehand and perform supervised source separation in an online fashion. However, in many real-world scenarios (e.g. speech denoisin...

Anonymous communication has become a building block of network services. Besides providing anonymity, speed (and thus real-time guarantees) are becoming crucial as well. In this paper we will introduce the global delaying adversary (GDA), an active attacker who is capable of arbitrarily delaying messages, while eavesdropping on all communication channels. This type of foe is particularly releva...

In this article a method is proposed for ball tracking using 100 Hz computer vision in a semi-automated foosball table. In this application the behavior of the ball is highly dynamic with speeds up to 10 m/s and frequent bounces occur against the sides of the table and the puppets. Moreover, in the overhead camera view of the field the ball is often fully or partially occluded and there are oth...

Reinforcement Learning (RL) is a very suitable technique for robot learning, as it can learn in unknown environments and in real-time computation. The main difficulties in adapting classic RL algorithms to robotic systems are the generalization problem and the correct observation of the Markovian state. This paper attempts to solve the generalization problem by proposing the Semi-Online NeuralQ...