6 Search Results for "Hill, Michael R."

Document
DOI: 10.4230/LITES.8.1.2
Micro- and Macroscopic Road Traffic Analysis using Drone Image Data

Authors: Friedrich Kruber, Eduardo Sánchez Morales, Robin Egolf, Jonas Wurst, Samarjit Chakraborty, and Michael Botsch

Published in: LITES, Volume 8, Issue 1 (2022): Special Issue on Embedded Systems for Computer Vision. Leibniz Transactions on Embedded Systems, Volume 8, Issue 1

Abstract
The current development in the drone technology, alongside with machine learning based image processing, open new possibilities for various applications. Thus, the market volume is expected to grow rapidly over the next years. The goal of this paper is to demonstrate the capabilities and limitations of drone based image data processing for the purpose of road traffic analysis. In the first part a method for generating microscopic traffic data is proposed. More precisely, the state of vehicles and the resulting trajectories are estimated. The method is validated by conducting experiments with reference sensors and proofs to achieve precise vehicle state estimation results. It is also shown, how the computational effort can be reduced by incorporating the tracking information into a neural network. A discussion on current limitations supplements the findings. By collecting a large number of vehicle trajectories, macroscopic statistics, such as traffic flow and density can be obtained from the data. In the second part, a publicly available drone based data set is analyzed to evaluate the suitability for macroscopic traffic modeling. The results show that the method is well suited for gaining detailed information about macroscopic statistics, such as traffic flow dependent time headway or lane change occurrences. In conclusion, this paper presents methods to exploit the remarkable opportunities of drone based image processing for joint macro- and microscopic traffic analysis.
Cite as

Friedrich Kruber, Eduardo Sánchez Morales, Robin Egolf, Jonas Wurst, Samarjit Chakraborty, and Michael Botsch. Micro- and Macroscopic Road Traffic Analysis using Drone Image Data. In LITES, Volume 8, Issue 1 (2022): Special Issue on Embedded Systems for Computer Vision. Leibniz Transactions on Embedded Systems, Volume 8, Issue 1, pp. 02:1-02:27, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@Article{kruber_et_al:LITES.8.1.2,
  author =	{Kruber, Friedrich and S\'{a}nchez Morales, Eduardo and Egolf, Robin and Wurst, Jonas and Chakraborty, Samarjit and Botsch, Michael},
  title =	{{Micro- and Macroscopic Road Traffic Analysis using Drone Image Data}},
  journal =	{Leibniz Transactions on Embedded Systems},
  pages =	{02:1--02:27},
  ISSN =	{2199-2002},
  year =	{2022},
  volume =	{8},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LITES.8.1.2},
  doi =		{10.4230/LITES.8.1.2},
  annote =	{Keywords: traffic data analysis, trajectory data, drone image data}
}
Document
DOI: 10.4230/OASIcs.iPMVM.2020.5
Optimized Routine of Machining Distortion Characterization Based on Gaussian Surface Curvature

Authors: Destiny R. Garcia, Barbara S. Linke, and Rida T. Farouki

Published in: OASIcs, Volume 89, 2nd International Conference of the DFG International Research Training Group 2057 – Physical Modeling for Virtual Manufacturing (iPMVM 2020)

Abstract
Machining distortion presents a significant problem in products with high residual stresses from materials processing and re-equilibration after machining removes a large part of the material volume and is common in the aerospace industries. While many papers research on mechanisms of machining distortion, few papers report on the measurement, processing and characterization of distortion data. Oftentimes only line plot data is used to give a maximum distortion value. This paper proposes a method of measurement tool selection, measurement parameter selection, data processing through filtering and leveling, and use of Bézier Surfaces and Gaussian Curvature for distortion characterization. The method is demonstrated with three sample pieces of different pocket geometry from quenched aluminum. It is apparent that samples with machining distortion can have complex surface shapes, where Bézier Surfaces and Gaussian Curvature provide more information than the commonly used 2D line plot data.
Cite as

Destiny R. Garcia, Barbara S. Linke, and Rida T. Farouki. Optimized Routine of Machining Distortion Characterization Based on Gaussian Surface Curvature. In 2nd International Conference of the DFG International Research Training Group 2057 – Physical Modeling for Virtual Manufacturing (iPMVM 2020). Open Access Series in Informatics (OASIcs), Volume 89, pp. 5:1-5:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

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@InProceedings{garcia_et_al:OASIcs.iPMVM.2020.5,
  author =	{Garcia, Destiny R. and Linke, Barbara S. and Farouki, Rida T.},
  title =	{{Optimized Routine of Machining Distortion Characterization Based on Gaussian Surface Curvature}},
  booktitle =	{2nd International Conference of the DFG International Research Training Group 2057 – Physical Modeling for Virtual Manufacturing (iPMVM 2020)},
  pages =	{5:1--5:17},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-183-2},
  ISSN =	{2190-6807},
  year =	{2021},
  volume =	{89},
  editor =	{Garth, Christoph and Aurich, Jan C. and Linke, Barbara and M\"{u}ller, Ralf and Ravani, Bahram and Weber, Gunther H. and Kirsch, Benjamin},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.iPMVM.2020.5},
  URN =		{urn:nbn:de:0030-drops-137542},
  doi =		{10.4230/OASIcs.iPMVM.2020.5},
  annote =	{Keywords: Machining distortion, Metrology, Gaussian curvature}
}
Document
DOI: 10.4230/OASIcs.iPMVM.2020.11
Finite Element Simulation Combination to Predict the Distortion of Thin Walled Milled Aluminum Workpieces as a Result of Machining Induced Residual Stresses

Authors: Daniel Weber, Benjamin Kirsch, Christopher R. Chighizola, Julianne E. Jonsson, Christopher R. D’Elia, Barbara S. Linke, Michael R. Hill, and Jan C. Aurich

Published in: OASIcs, Volume 89, 2nd International Conference of the DFG International Research Training Group 2057 – Physical Modeling for Virtual Manufacturing (iPMVM 2020)

Abstract
Machining induced residual stresses (MIRS) are a main driver for distortion of monolithic thin walled aluminum workpieces. A typical machining process for manufacturing such geometries for the aerospace industry is milling. In order to avoid high costs due to remanufacturing or part rejection, a simulation combination, consisting of two different finite element method (FEM) models, is developed to predict the part distortion due to MIRS. First, a 3D FEM cutting simulation is developed to predict the residual stresses due to machining. This simulation avoids cost intensive residual stress measurements. The milling process of the aluminum alloy AA7050-T7451 with a regular end mill is simulated. The simulation output, MIRS, forces and temperatures, is validated by face milling experiments on aluminum. The model takes mechanical dynamic effects, thermomechanical coupling, material properties and a damage law into account. Second, a subsequent finite element simulation, characterized by a static, linear elastic model, where the simulated MIRS from the cutting model are used as an input and the distortion of the workpiece is calculated, is presented. The predicted distortion is compared to an additional experiment, where a 1 mm thick wafer was removed at the milled surface of the aluminum workpiece. Furthermore, a thin walled component that represents a down scaled version of an aerospace component is manufactured and its distortion is analyzed. The results show that MIRS could be forecasted with moderate accuracy, which leads to the conclusion that the FEM cutting model needs to be improved in order to use the MIRS for a correct prediction of the distortion with the help of the linear elastic FEM model. The linear elastic model on the other hand is able to predict the part distortion with higher accuracy when using measured data instead of MIRS from the cutting simulation.
Cite as

Daniel Weber, Benjamin Kirsch, Christopher R. Chighizola, Julianne E. Jonsson, Christopher R. D’Elia, Barbara S. Linke, Michael R. Hill, and Jan C. Aurich. Finite Element Simulation Combination to Predict the Distortion of Thin Walled Milled Aluminum Workpieces as a Result of Machining Induced Residual Stresses. In 2nd International Conference of the DFG International Research Training Group 2057 – Physical Modeling for Virtual Manufacturing (iPMVM 2020). Open Access Series in Informatics (OASIcs), Volume 89, pp. 11:1-11:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

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@InProceedings{weber_et_al:OASIcs.iPMVM.2020.11,
  author =	{Weber, Daniel and Kirsch, Benjamin and Chighizola, Christopher R. and Jonsson, Julianne E. and D’Elia, Christopher R. and Linke, Barbara S. and Hill, Michael R. and Aurich, Jan C.},
  title =	{{Finite Element Simulation Combination to Predict the Distortion of Thin Walled Milled Aluminum Workpieces as a Result of Machining Induced Residual Stresses}},
  booktitle =	{2nd International Conference of the DFG International Research Training Group 2057 – Physical Modeling for Virtual Manufacturing (iPMVM 2020)},
  pages =	{11:1--11:21},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-183-2},
  ISSN =	{2190-6807},
  year =	{2021},
  volume =	{89},
  editor =	{Garth, Christoph and Aurich, Jan C. and Linke, Barbara and M\"{u}ller, Ralf and Ravani, Bahram and Weber, Gunther H. and Kirsch, Benjamin},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.iPMVM.2020.11},
  URN =		{urn:nbn:de:0030-drops-137604},
  doi =		{10.4230/OASIcs.iPMVM.2020.11},
  annote =	{Keywords: Machining induced residual stresses, distortion, Finite element method simulation}
}
Document
Keynote Speakers
DOI: 10.4230/LIPIcs.AofA.2018.8
Periods in Subtraction Games (Keynote Speakers)

Authors: Bret Benesh, Jamylle Carter, Deidra A. Coleman, Douglas G. Crabill, Jack H. Good, Michael A. Smith, Jennifer Travis, and Mark Daniel Ward

Published in: LIPIcs, Volume 110, 29th International Conference on Probabilistic, Combinatorial and Asymptotic Methods for the Analysis of Algorithms (AofA 2018)

Abstract
We discuss the structure of periods in subtraction games. In particular, we discuss ways that a computational approach yields insights to the periods that emerge in the asymptotic structure of these combinatorial games.
Cite as

Bret Benesh, Jamylle Carter, Deidra A. Coleman, Douglas G. Crabill, Jack H. Good, Michael A. Smith, Jennifer Travis, and Mark Daniel Ward. Periods in Subtraction Games (Keynote Speakers). In 29th International Conference on Probabilistic, Combinatorial and Asymptotic Methods for the Analysis of Algorithms (AofA 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 110, pp. 8:1-8:3, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

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@InProceedings{benesh_et_al:LIPIcs.AofA.2018.8,
  author =	{Benesh, Bret and Carter, Jamylle and Coleman, Deidra A. and Crabill, Douglas G. and Good, Jack H. and Smith, Michael A. and Travis, Jennifer and Ward, Mark Daniel},
  title =	{{Periods in Subtraction Games}},
  booktitle =	{29th International Conference on Probabilistic, Combinatorial and Asymptotic Methods for the Analysis of Algorithms (AofA 2018)},
  pages =	{8:1--8:3},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-078-1},
  ISSN =	{1868-8969},
  year =	{2018},
  volume =	{110},
  editor =	{Fill, James Allen and Ward, Mark Daniel},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.AofA.2018.8},
  URN =		{urn:nbn:de:0030-drops-89015},
  doi =		{10.4230/LIPIcs.AofA.2018.8},
  annote =	{Keywords: combinatorial games, subtraction games, periods, asymptotic structure}
}
Document
DOI: 10.4230/DagSemProc.07361.3
A Case for Deconstructing Hardware Transactional Memory Systems

Authors: Mark D. Hill, Derek Hower, Kevin E. Moore, Michael M. Swift, Haris Volos, and David A. Wood

Published in: Dagstuhl Seminar Proceedings, Volume 7361, Programming Models for Ubiquitous Parallelism (2008)

Abstract
Major hardware and software vendors are curious about transactional memory (TM), but are understandably cautious about committing to hardware changes. Our thesis is that deconstructing transactional memory into separate, interchangeable components facilitates TM adoption in two ways. First, it aids hardware TM refinement, allowing vendors to adopt TM earlier, knowing that they can more easily refine aspects later. Second, it enables the components to be applied to other uses, including reliability, security, performance, and correctness, providing value even if TM is not widely used. We develop some evidence for our thesis via experience with LogTM variants and preliminary case studies of scalable watchpoints and race recording for deterministic replay.
Cite as

Mark D. Hill, Derek Hower, Kevin E. Moore, Michael M. Swift, Haris Volos, and David A. Wood. A Case for Deconstructing Hardware Transactional Memory Systems. In Programming Models for Ubiquitous Parallelism. Dagstuhl Seminar Proceedings, Volume 7361, pp. 1-8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2008)

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@InProceedings{hill_et_al:DagSemProc.07361.3,
  author =	{Hill, Mark D. and Hower, Derek and Moore, Kevin E. and Swift, Michael M. and Volos, Haris and Wood, David A.},
  title =	{{A Case for Deconstructing Hardware Transactional Memory Systems}},
  booktitle =	{Programming Models for Ubiquitous Parallelism},
  pages =	{1--8},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2008},
  volume =	{7361},
  editor =	{Albert Cohen and Mar{\'\i}a J. Garzar\'{a}n and Christian Lengauer and Samuel P. Midkiff},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.07361.3},
  URN =		{urn:nbn:de:0030-drops-13759},
  doi =		{10.4230/DagSemProc.07361.3},
  annote =	{Keywords: Hardware transactional memory}
}
Document
DOI: 10.4230/DagSemProc.06061.4
A New Quartet Tree Heuristic for Hierarchical Clustering

Authors: Rudi Cilibrasi and Paul M. B. Vitany

Published in: Dagstuhl Seminar Proceedings, Volume 6061, Theory of Evolutionary Algorithms (2006)

Abstract
We present a new quartet heuristic for hierarchical clustering from a given distance matrix. We determine a dendrogram (ternary tree) by a new quartet method and a fast heuristic to implement it. We do not assume that there is a true ternary tree that generated the distances and which we with to recover as closeley as possible. Our aim is to model the distance matrix as faithfully as possible by the dendrogram. Our algorithm is essentially randomized hill-climbing, using parallellized Genetic Programming, where undirected trees evolve in a random walk driven by a prescribed fitness function. Our method is capable of handling up to 60--80 objects in a matter of hours, while no existing quartet heuristic can directly compute a quartet tree of more than about 20--30 objects without running for years. The method is implemented and available as public software at www.complearn.org. We present applications in many areas like music, literature, bird-flu (H5N1) virus clustering, and automatic meaning discovery using Google.
Cite as

Rudi Cilibrasi and Paul M. B. Vitany. A New Quartet Tree Heuristic for Hierarchical Clustering. In Theory of Evolutionary Algorithms. Dagstuhl Seminar Proceedings, Volume 6061, pp. 1-13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2006)

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@InProceedings{cilibrasi_et_al:DagSemProc.06061.4,
  author =	{Cilibrasi, Rudi and Vitany, Paul M. B.},
  title =	{{A New Quartet Tree Heuristic for Hierarchical Clustering}},
  booktitle =	{Theory of Evolutionary Algorithms},
  pages =	{1--13},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2006},
  volume =	{6061},
  editor =	{Dirk V. Arnold and Thomas Jansen and Michael D. Vose and Jonathan E. Rowe},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.06061.4},
  URN =		{urn:nbn:de:0030-drops-5985},
  doi =		{10.4230/DagSemProc.06061.4},
  annote =	{Keywords: Genetic programming, hierarchical clustering, quartet tree method}
}
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