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Institution

Vienna University of Technology

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


Papers
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Journal ArticleDOI
TL;DR: In this article, the authors studied the center dominance in the maximal center gauge for SU(2) lattice gauge theory and showed that the center projection is associated with thin vortices of the projected configurations.
Abstract: We find, in close analogy to Abelian dominance in the maximal Abelian gauge, the phenomenon of center dominance in the maximal center gauge for SU(2) lattice gauge theory. The maximal center gauge is a gauge-fixing condition that preserves a residual ${Z}_{2}$ gauge symmetry; ``center projection'' is the projection of SU(2) link variables onto ${Z}_{2}$ center elements, and ``center dominance'' is the fact that the center-projected link elements carry most of the information about the string tension of the full theory. We present numerical evidence that the thin ${Z}_{2}$ vortices of the projected configurations are associated with ``thick'' ${Z}_{2}$ vortices in the unprojected configurations. The evidence also suggests that the thick ${Z}_{2}$ vortices may play a significant role in the confinement process.

240 citations

Proceedings ArticleDOI
08 Jul 2004
TL;DR: This framework for pairwise registration of shapes represented by point cloud data (PCD) can align PCDs even when they are placed far apart, and is experimentally found to be more stable than point-to-plane ICP.
Abstract: We propose a framework for pairwise registration of shapes represented by point cloud data (PCD). We assume that the points are sampled from a surface and formulate the problem of aligning two PCDs as a minimization of the squared distance between the underlying surfaces. Local quadratic approximants of the squared distance function are used to develop a linear system whose solution gives the best aligning rigid transform for the given pair of point clouds. The rigid transform is applied and the linear system corresponding to the new orientation is build. This process is iterated until it converges. The point-to-point and the point-to-plane Iterated Closest Point (ICP) algorithms can be treated as special cases in this framework. Our algorithm can align PCDs even when they are placed far apart, and is experimentally found to be more stable than point-to-plane ICP. We analyze the convergence behavior of our algorithm and of point-to-point and point-to-plane ICP under our proposed framework, and derive bounds on their rate of convergence. We compare the stability and convergence properties of our algorithm with other registration algorithms on a variety of scanned data.

240 citations

Journal ArticleDOI
TL;DR: Results show that the -value classification provides a robust basis for decisions regarding using either active or passive data alone, or an unweighted average in cases where relative weights cannot be estimated reliably, and that the weights estimated from TCA in almost all cases outperform the ternary decision upon which the ESA CCI SM v02.3 is based.
Abstract: We propose a method for merging soil moisture retrievals from spaceborne active and passive microwave instruments based on weighted averaging taking into account the error characteristics of the individual data sets. The merging scheme is parameterized using error variance estimates obtained from using triple collocation analysis (TCA). In regions where TCA is deemed unreliable, we use correlation significance levels ( $p$ -values) as indicator for retrieval quality to decide whether to use active data only, passive data only, or an unweighted average. We apply the proposed merging scheme to active retrievals from advanced scatterometer and passive retrievals from the Advanced Microwave Scanning Radiometer—Earth Observing System using Global Land Data Assimilation System-Noah to complement the triplet required for TCA. The merged time series is evaluated against soil moisture estimates from ERA-Interim/Land and in situ measurements from the International Soil Moisture Network using the European Space Agency’s (ESA’s) current Climate Change Initiative—Soil Moisture (ESA CCI SM) product version v02.3 as benchmark merging scheme. Results show that the $p$ -value classification provides a robust basis for decisions regarding using either active or passive data alone, or an unweighted average in cases where relative weights cannot be estimated reliably, and that the weights estimated from TCA in almost all cases outperform the ternary decision upon which the ESA CCI SM v02.3 is based. The proposed method forms the basis for the new ESA CCI SM product version v03.x and higher.

240 citations

Book ChapterDOI
01 Jan 2018
TL;DR: This chapter summarise the state-of-the-art techniques for qualitative and quantitative monitoring of CPS behaviours, and presents an overview of some of the important applications and describes the tools supporting CPS monitoring and compare their main features.
Abstract: The term Cyber-Physical Systems (CPS) typically refers to engineered, physical and biological systems monitored and/or controlled by an embedded computational core. The behaviour of a CPS over time is generally characterised by the evolution of physical quantities, and discrete software and hardware states. In general, these can be mathematically modelled by the evolution of continuous state variables for the physical components interleaved with discrete events. Despite large effort and progress in the exhaustive verification of such hybrid systems, the complexity of CPS models limits formal verification of safety of their behaviour only to small instances. An alternative approach, closer to the practice of simulation and testing, is to monitor and to predict CPS behaviours at simulation-time or at runtime. In this chapter, we summarise the state-of-the-art techniques for qualitative and quantitative monitoring of CPS behaviours. We present an overview of some of the important applications and, finally, we describe the tools supporting CPS monitoring and compare their main features.

239 citations

Journal ArticleDOI
TL;DR: In this paper, the authors measured the scattering properties of vegetation and terrain surfaces in a quantitative way, such as the width of the echo pulse and the backscatter cross-section, which is a measure of the electromagnetic energy intercepted and re-radiated by objects.
Abstract: Small-footprint full-waveform airborne laser scanning (ALS) is a remote sensing technique capable of mapping vegetation in three dimensions with a spatial sampling of about 0.5-2 m in all directions. This is achieved by scanning the laser beam across the Earth's surface and by emitting nanosecond-long infrared pulses with a high frequency of typically 50-150 kHz. The echo signals are digitized during data acquisition for subsequent off-line waveform analysis. In addition to delivering the three-dimensional (3D) coordinates of scattering objects such as leaves or branches, full-waveform laser scanners can be calibrated for measuring the scattering properties of vegetation and terrain surfaces in a quantitative way. As a result, a number of physical observables are obtained, such as the width of the echo pulse and the backscatter cross-section, which is a measure of the electromagnetic energy intercepted and re-radiated by objects. The main aim of this study was to build up an understanding of the scattering characteristics of vegetation and the underlying terrain. It was found that vegetation typically causes a broadening of the backscattered pulse, while the backscatter cross-section is usually smaller for canopy echoes than for terrain echoes. These scattering properties allowed classification of the 3D point cloud into vegetation and non-vegetation echoes with an overall accuracy of 89.9% for a dense natural forest and 93.7% for a baroque garden area. In addition, by removing the vegetation echoes before the filtering process, the quality of the digital terrain model could be improved.

239 citations


Authors

Showing all 16934 results

NameH-indexPapersCitations
Krzysztof Matyjaszewski1691431128585
Wolfgang Wagner1562342123391
Marco Zanetti1451439104610
Sridhara Dasu1401675103185
Duncan Carlsmith1381660103642
Ulrich Heintz136168899829
Matthew Herndon133173297466
Frank Würthwein133158494613
Alain Hervé132127987763
Manfred Jeitler132127889645
David Taylor131246993220
Roberto Covarelli131151689981
Patricia McBride129123081787
David Smith1292184100917
Lindsey Gray129117081317
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023171
2022379
20212,527
20202,811
20192,846
20182,650