Vienna University of Technology

About: Vienna University of Technology is a education organization based out in Vienna, Austria. It is known for research contribution in the topics: Laser & Context (language use). The organization has 16723 authors who have published 49341 publications receiving 1302168 citations.

The role of rankings in growing city competition

Abstract: This paper concentrates on the question of how cities cope with the results of national and international city rankings and how a specific ranking approach can be used as a strategic instrument for policy advice. Introducing this topic, the first section provides a discussion of benefits and limits of city rankings. Based on this discussion, a comprehensive city-ranking approach is developed, which tries to meet the requirements of knowledge-based economic urban development by defining and applying an innovative sample of indicators. Finally, the paper elaborates the meaning of city rankings as a knowledge-based instrument as well as the possibilities for cities to make use of ranking results. Answering these issues, the paper concludes with proposals for making city rankings a more significant and effective instrument for steering economic, social and spatial processes in cities: it suggests recommendations for researchers and analysts dealing with the design and methodology of city rankings, on the one ...

Inverse magnetic catalysis in dense holographic matter

Abstract: We study the chiral phase transition in a magnetic field at finite temperature and chemical potential within the Sakai-Sugimoto model, a holographic top-down approach to (large-N c ) QCD. We consider the limit of a small separation of the flavor D8-branes, which corresponds to a dual field theory comparable to a Nambu-Jona Lasinio (NJL) model. Mapping out the surface of the chiral phase transition in the parameter space of magnetic field strength, quark chemical potential, and temperature, we find that for small temperatures the addition of a magnetic field decreases the critical chemical potential for chiral symmetry restoration — in contrast to the case of vanishing chemical potential where, in accordance with the familiar phenomenon of magnetic catalysis, the magnetic field favors the chirally broken phase. This “inverse magnetic catalysis” (IMC) appears to be associated with a previously found magnetic phase transition within the chirally symmetric phase that shows an intriguing similarity to a transition into the lowest Landau level. We estimate IMC to persist up to 1019 G at low temperatures.

Object stereo — Joint stereo matching and object segmentation

Abstract: This paper presents a method for joint stereo matching and object segmentation. In our approach a 3D scene is represented as a collection of visually distinct and spatially coherent objects. Each object is characterized by three different aspects: a color model, a 3D plane that approximates the object's disparity distribution, and a novel 3D connectivity property. Inspired by Markov Random Field models of image segmentation, we employ object-level color models as a soft constraint, which can aid depth estimation in powerful ways. In particular, our method is able to recover the depth of regions that are fully occluded in one input view, which to our knowledge is new for stereo matching. Our model is formulated as an energy function that is optimized via fusion moves. We show high-quality disparity and object segmentation results on challenging image pairs as well as standard benchmarks. We believe our work not only demonstrates a novel synergy between the areas of image segmentation and stereo matching, but may also inspire new work in the domain of automatic and interactive object-level scene manipulation.

The Multidimensional Knapsack Problem: Structure and Algorithms

Abstract: We study the multidimensional knapsack problem, present some theoretical and empirical results about its structure, and evaluate different integer linear programming (ILP)-based, metaheuristic, and collaborative approaches for it. We start by considering the distances between optimal solutions to the LP relaxation and the original problem and then introduce a new core concept for the multidimensional knapsack problem (MKP), which we study extensively. The empirical analysis is then used to develop new concepts for solving the MKP using ILP-based and memetic algorithms. Different collaborative combinations of the presented methods are discussed and evaluated. Further computational experiments with longer run times are also performed to compare the solutions of our approaches to the best-known solutions of another so-far leading approach for common MKP benchmark instances. The extensive computational experiments show the effectiveness of the proposed methods, which yield highly competitive results in significantly shorter run times than do previously described approaches.