@misc{HillerVredeveld, author = {Hiller, Benjamin and Vredeveld, Tjark}, title = {Stochastic dominance analysis of Online Bin Coloring algorithms}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-16502}, abstract = {This paper proposes a new method for probabilistic analysis of online algorithms. It is based on the notion of stochastic dominance. We develop the method for the online bin coloring problem introduced by Krumke et al (2008). Using methods for the stochastic comparison of Markov chains we establish the result that the performance of the online algorithm GreedyFit is stochastically better than the performance of the algorithm OneBin for any number of items processed. This result gives a more realistic picture than competitive analysis and explains the behavior observed in simulations.}, language = {en} } @misc{OrlowskiWernerWessaely, author = {Orlowski, Sebastian and Werner, Axel and Wess{\"a}ly, Roland}, title = {Estimating trenching costs in FTTx network planning}, issn = {1438-0064}, doi = {10.1007/978-3-642-29210-1_15}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-14884}, abstract = {In this paper we assess to which extent trenching costs of an FTTx network are unavoidable, even if technical side constraints are neglected. For that purpose we present an extended Steiner tree model. Using a variety of realistic problem instances we demonstrate that the total trenching cost can only be reduced by about 5 percent in realistic scenarios. This work has been funded by BMBF (German Federal Ministry of Education and Research) within the program "KMU-innovativ".}, language = {en} } @misc{HillerVredeveld, author = {Hiller, Benjamin and Vredeveld, Tjark}, title = {Probabilistic alternatives for competitive analysis}, issn = {1438-0064}, doi = {10.1007/s00450-011-0149-1}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-15131}, abstract = {In the last 20 years competitive analysis has become the main tool for analyzing the quality of online algorithms. Despite of this, competitive analysis has also been criticized: It sometimes cannot discriminate between algorithms that exhibit significantly different empirical behavior, or it even favors an algorithm that is worse from an empirical point of view. Therefore, there have been several approaches to circumvent these drawbacks. In this survey, we discuss probabilistic alternatives for competitive analysis.}, language = {en} } @misc{WiebelVosHege, author = {Wiebel, Alexander and Vos, Frans M. and Hege, Hans-Christian}, title = {Perception-Oriented Picking of Structures in Direct Volumetric Renderings}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-14343}, number = {11-45}, abstract = {Radiologists from all application areas are trained to read slice-based visualizations of 3D medical image data. Despite the numerous examples of sophisticated three-dimensional renderings, especially all variants of direct volume rendering, such methods are often considered not very useful by radiologists who prefer slice-based visualization. Just recently there have been attempts to bridge this gap between 2D and 3D renderings. These attempts include specialized techniques for volume picking that result in repositioning slices. In this paper, we present a new volume picking technique that, in contrast to previous work, does not require pre-segmented data or metadata. The positions picked by our method are solely based on the data itself, the transfer function and, most importantly, on the way the volumetric rendering is perceived by viewers. To demonstrate the usefulness of the proposed method we apply it for automatically repositioning slices in an abdominal MRI scan, a data set from a flow simulation and a number of other volumetric scalar fields. Furthermore we discuss how the method can be implemented in combination with various different volumetric rendering techniques.}, language = {en} } @misc{ClasenPaarProhaska, author = {Clasen, Malte and Paar, Philip and Prohaska, Steffen}, title = {Level of Detail for Trees Using Clustered Ellipsoids}, issn = {1438-0064}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-14251}, number = {11-41}, abstract = {We present a level of detail method for trees based on ellipsoids and lines. We leverage the Expectation Maximization algorithm with a Gaussian Mixture Model to create a hierarchy of high-quality leaf clusterings, while the branches are simplified using agglomerative bottom-up clustering to preserve the connectivity. The simplification runs in a preprocessing step and requires no human interaction. For a fly by over and through a scene of 10k trees, our method renders on average at 40 ms/frame, up to 6 times faster than billboard clouds with comparable artifacts.}, language = {en} } @misc{Wolf, author = {Wolf, Thomas}, title = {A Study of Genetic Algorithms solving a combinatorial Puzzle}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-3445}, number = {SC-98-01}, abstract = {The suitability of Genetic Algorithms (GAs) to solve a combinatorial problem with only one solution is investigated. The dependence of the performance is studied for GA-hard and GA-soft fitness functions, both with a range of different parameter values and different encodings.}, language = {en} }