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AbstractAbstract-This study describes a method for programming a plug-in electric vehicle agent that can be used in power system models and in embedded systems implemented in real plug-in electric vehicles. Implementing the software in reallife applications and in simulation tools enables research with a high degree of detail and practical relevance. Agent-based programming, therefore, is an important tool for investigating the future power system. To demonstrate the plugin electric vehicle agent behavior, an optimization algorithm is presented and two battery aging methods as well as their effect on V2G operation are analyzed. Aging costs based on the depth of discharge result in shallow cycles and a strong dependency on driving behavior, because the state-of-charge affects the discharging process. In contrast, aging costs based on energy throughput calculations results in deeper cycles and V2G operation which is less dependent on driving behavior.
We study integrated prefetching and caching in single and parallel disk systems. There exist two very popular approximation algorithms called Aggressive and Conservative for minimizing the total elapsed time in the single disk problem. For D parallel disks, approximation algorithms are known for both the elapsed time and stall time performance measures. In particular, there exists a D-approximation algorithm for the stall time measure that uses D−1 additional memory locations in cache.In the first part of the paper we investigate approximation algorithms for the single disk problem. We give a refined analysis of the Aggressive algorithm, showing that the original analysis was too pessimistic. We prove that our new bound is tight. Additionally we present a new family of prefetching and caching strategies and give algorithms that perform better than Aggressive and Conservative.In the second part of the paper we investigate the problem of minimizing stall time in parallel disk systems. We present a polynomial time algorithm for computing a prefetching/ caching schedule whose stall time is bounded by that of an optimal solution. The schedule uses at most 3(D − 1) extra memory locations in cache. This is the first polynomial time algorithm for computing schedules with a minimum stall time. Our algorithm is based on the linear programming approach of [1]. However, in order to achieve minimum stall times, we introduce the new concept of synchronized schedules in which fetches on the D disks are performed completely in parallel. * Work supported by the Deutsche Forschungsgemeinschaft, project project AL 464/3-1, and by the EU, projects APPOL and APPOL II.
This paper shows that the X-ray analysis method known from the medical field, using a priori information, can provide a lot more information than the common analysis for high-speed experiments. Via spatial registration of known 3D shapes with the help of 2D X-ray images, it is possible to derive the spatial position and orientation of the examined parts. The method was demonstrated on the example of the sabot discard of a subcaliber projectile. The velocity of the examined object amounts up to 1600 m/s. As a priori information, the geometry of the experimental setup and the shape of the projectile and sabot parts were used. The setup includes four different positions or points in time to examine the behavior over time. It was possible to place the parts within a spatial accuracy of 0.85 mm (standard deviation), respectively 1.7 mm for 95% of the errors within this range. The error is mainly influenced by the accuracy of the experimental setup and the tagging of the feature points on the X-ray images.
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