Today, health research and health care generate a steadily increasing amount of data. Making these available for secondary use cases is essential for efficiency gains in health research, e.g. by reducing time-and costs-intensive acquisition of data. In this contribution, we introduce our SAHRA software platform enabling reproducible research, e.g. by combining multiple data sources, performing data de-identification, and content filtering. We define an innovative research process combining retrospective and prospective research for the first time. Thus, authorized users, e.g. clinical researchers, are able to gain access through our system relevant research data and to perform interactive analyses. As a result, existing sensitive health data is securely transformed into de-identified research data, which can be used to improve future health research.

We investigate the feasibility of content distribution between devices mounted in moving vehicles using commodity WiFi. We assume that each device stores content in a set of files, and that each file has a version number. When two devices come into wireless range, they attempt to synchronize the latest versions of any files they have in common. This is challenging because connections are often short-lived and have variable link quality. Prior work demonstrates that current protocols perform badly under these conditions. To motivate this work, we use the example of Personal Navigation Devices (PNDs), or SatNavs, where the content to be exchanged includes maps and points-of-interest files.

Name services for mobile ad hoc networks are essential to discover and bind resources given by their name or URI to a specific network address. As there is no fixed infrastructure available in MANETs, nodes cannot rely on any DNS-like system as is taken for granted in the Internet. To keep up with the dynamicity of MANETs, a name service needs to be flexible and scalable. For this purpose, we propose MAPNaS (mobile ad-hoc peer-to-peer name service), a lightweight and locality-aware peer-to-peer based name service. MAPNaS runs on top of MADPastry (T. Zhan and J. Schiller, June 2005), a general-purpose DHT substrate especially designed for MANETs. Through simulation we compare the performance of MAPNaS - both in terms of the success rate and overall network traffic - against an unstructured, broadcast-based reference approach. We thereby demonstrate how to efficiently build a peer-to-peer based name service in mobile ad hoc networks

We describe a biological inspired model of binaural sound localization using interaural time differences (ITDs). To handle the problem of temporal coding and to facilitate a hardware implementation in analog VLSI, the simulation of the system is based on a spike response model. This neuron model takes up physiological properties like postsynaptic potentials (PSPs) and a refractory period. A winner-take-all (WTA) network selects the dominant source from the representation of the sound's angles of incidences, and can be biased by a multisensory support. We use simulations on real audio data to investigate the function and the practical application of the system.