We present the first observation of self-amplified spontaneous emission (SASE) in a free-electron laser (FEL) in the vacuum ultraviolet regime at 109 nm wavelength (11 eV). The observed free-electron laser gain (approximately 3000) and the radiation characteristics, such as dependency on bunch charge, angular distribution, spectral width, and intensity fluctuations, are all consistent with the present models for SASE FELs.

Moving objects databases (MOD) manageParts of this article appeared as "Online Trajectory Data Reduction using Connection-preserving Dead Reckoning" in the Proceedings of the 5th International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services (MobiQuitous '08) [12] and as "Remote Real-Time Trajectory Simplification" in the Proceedings of the 7th IEEE International Conference on Pervasive Computing and Communications (PerCom '09) [15].

Moving objects databases (MODs) have been proposed for managing trajectory data, an important kind of information for pervasive applications. To save storage capacity, a MOD generally stores simplified trajectories only. A simplified trajectory approximates the actual trajectory of the mobile object according to a certain accuracy bound.In order to minimize the costs of communicating position information between mobile object and MOD, the trajectory simplification should be performed by the mobile object. To assure that the MOD always has a valid simplified trajectory of the remote object, we propose the generic remote trajectory simplification protocol (GRTS) allowing for computing and managing a simplified trajectory in such a system in real-time.We show how to combine GRTS with existing line simplification algorithms for computing the simplified trajectory and analyze trade-offs between the different algorithms. Our evaluations show that GRTS outperforms the two existing approaches by a factor of two and more in terms of reduction efficiency. Moreover, on average, the reduction efficiency of GRTS is only 12% worse compared to optimal offline simplification.

No abstract

Moving objects databases (MODs) store objects' trajectories by spatiotemporal polylines that approximate the actual movements given by sequences of sensed positions. Determining such a polyline with as few vertices as possible under the constraint that it does not deviate by more than a certain accuracy bound from the sensed positions is an algorithmic problem known as trajectory reduction.A specific challenge is online trajectory reduction, i.e. continuous reduction with position sensing in realtime. This particularly is required for moving objects with embedded position sensors whose movements are tracked and stored by a remote MOD.In this paper, we present Connection-preserving Dead Reckoning (CDR), a new approach for online trajectory reduction. It outperforms the existing approaches by 30 to 50%. CDR requires the moving objects to temporally store some of the previously sensed positions. Although the storage consumption of CDR generally is small, it is not bounded. We therefore further present CDR M whose storage allocation and execution time per position fix can be adjusted and limited. Even with very limited storage allocations of less than 1 kB CDR M outperforms the existing approach by 20 to 40%.