Felix Schmitt

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We present a particle-in-cell simulation of the relativistic Kelvin-Helmholtz Instability (KHI) that for the first time delivers angularly resolved radiation spectra of the particle dynamics during the formation of the KHI. This enables studying the formation of the KHI with unprecedented spatial, angular and spectral resolution. Our results are of great(More)
INTRODUCTION The role of reactive carbonyl species, such as methylglyoxal (MG), has been overlooked within the context of the sepsis syndrome. The aims of this study were to assess the impact of MG formation in different inflammatory settings and to evaluate its use for early diagnosis as well as prognosis of the sepsis syndrome. METHODS In total, 120(More)
This paper outlines our current research program in the fields of ambient intelligence and context-aware computing and the tools we are building to accomplish this research program. From a discussion of our conception of mental models in the domain of ambient context-aware computer systems we derive hypotheses which we intend to test empirically. A modular(More)
Inverse Reinforcement Learning (IRL) describes the problem of learning an unknown reward function of a Markov Decision Process (MDP) from observed behavior of an agent. Since the agent’s behavior originates in its policy and MDP policies depend on both the stochastic system dynamics as well as the reward function, the solution of the inverse problem is(More)
In this paper we present a concept for integrating Multimedia-Enriched Learning Objects (MELOs) within a unifying technological framework for schools. First, we discuss the general role of objects for child development and learning. We then outline the framework architecture of the proposed Networked Environment for Multimedia Objects (NEMO). Afterwards, we(More)
In this paper, we describe our current research concerning users’ mental models of what can be called “disappearing computer systems”. This notion comprises computer systems, applications, and appliances related to ubiquitous, pervasive, or ambient computing which blend more or less seamlessly into the users’ natural environment. Mental models enable users(More)
Utilizing accelerators in heterogeneous systems is an established approach for designing peta-scale applications. Today, CUDA offers a rich programming interface for GPU accelerators but requires developers to incorporate several layers of parallelism on both CPU and GPU. From this increasing program complexity emerges the need for sophisticated performance(More)
Driver distraction strongly contributes to crash-risk. Therefore, assistance systems that warn drivers if their distraction poses a hazard to road safety, promise a great safety benefit. Current approaches either seek to detect critical situations using environmental sensors or estimate a driver's attention state solely from his/her behavior. However, this(More)
Programming of high performance computing systems has become more complex over time. Several layers of parallelism need to be exploited to efficiently utilize the available resources. To support application developers and performance analysts we propose a technique for identifying the most performance critical optimization targets in distributed(More)
More and more computationally intensive scientific applications make use of hardware accelerators like general purpose graphics processing units (GPGPUs). Compared to software development for typical multi-core processors their programming is fairly complex and needs hardware specific optimizations to utilize the full computing power. To achieve high(More)