3 Search Results for "Lange, Andreas"

Document
DOI: 10.4230/OASIcs.iPMVM.2020.2
Physical Modeling of Process-Machine-Interactions in Micro Machining

Authors: Andreas Lange, Benjamin Kirsch, Marius Heintz, 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
Increasing demands for smaller and smarter devices in a variety of applications requires the investigation of process-machine-interactions in micro manufacturing to ensure process results that guarantee part functionality. One approach is the use of simulation-based physical models. In this contribution, methods for the physical modeling of high-precision air bearing and magnetic bearing spindles are presented in addition to a kinematic model of the micro milling process. Both models are superimposed in order to carry out investigations of the slot bottom surface roughness in micro end milling. The results show that process-machine-interactions in micro manufacturing can be modeled by the superposition of a physical model of the machine tool spindle taking cutting forces into consideration and a purely kinematic model of the machining process, providing the necessary tools for a variety of further investigations into process-machine-interactions in micro manufacturing.
Cite as

Andreas Lange, Benjamin Kirsch, Marius Heintz, and Jan C. Aurich. Physical Modeling of Process-Machine-Interactions in Micro Machining. 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. 2:1-2:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

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@InProceedings{lange_et_al:OASIcs.iPMVM.2020.2,
  author =	{Lange, Andreas and Kirsch, Benjamin and Heintz, Marius and Aurich, Jan C.},
  title =	{{Physical Modeling of Process-Machine-Interactions in Micro Machining}},
  booktitle =	{2nd International Conference of the DFG International Research Training Group 2057 – Physical Modeling for Virtual Manufacturing (iPMVM 2020)},
  pages =	{2:1--2:20},
  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.2020.2},
  URN =		{urn:nbn:de:0030-drops-137512},
  doi =		{10.4230/OASIcs.iPMVM.2020.2},
  annote =	{Keywords: multiphysics, air bearing, magnetic bearing, surface roughness modeling, micro milling}
}
Document
DOI: 10.4230/LIPIcs.STACS.2015.594
Visibly Counter Languages and Constant Depth Circuits

Authors: Andreas Krebs, Klaus-Jörn Lange, and Michael Ludwig

Published in: LIPIcs, Volume 30, 32nd International Symposium on Theoretical Aspects of Computer Science (STACS 2015)

Abstract
We examine visibly counter languages, which are languages recognized by visibly counter automata (a.k.a. input driven counter automata). We are able to effectively characterize the visibly counter languages in AC^0 and show that they are contained in FO[+].
Cite as

Andreas Krebs, Klaus-Jörn Lange, and Michael Ludwig. Visibly Counter Languages and Constant Depth Circuits. In 32nd International Symposium on Theoretical Aspects of Computer Science (STACS 2015). Leibniz International Proceedings in Informatics (LIPIcs), Volume 30, pp. 594-607, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2015)

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@InProceedings{krebs_et_al:LIPIcs.STACS.2015.594,
  author =	{Krebs, Andreas and Lange, Klaus-J\"{o}rn and Ludwig, Michael},
  title =	{{Visibly Counter Languages and Constant Depth Circuits}},
  booktitle =	{32nd International Symposium on Theoretical Aspects of Computer Science (STACS 2015)},
  pages =	{594--607},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-939897-78-1},
  ISSN =	{1868-8969},
  year =	{2015},
  volume =	{30},
  editor =	{Mayr, Ernst W. and Ollinger, Nicolas},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.STACS.2015.594},
  URN =		{urn:nbn:de:0030-drops-49447},
  doi =		{10.4230/LIPIcs.STACS.2015.594},
  annote =	{Keywords: visibly counter automata, constant depth circuits, AC0, FO\lbrack+\rbrack}
}
Document
DOI: 10.4230/DagSemProc.05471.9
High-accuracy peak picking of proteomics data

Authors: Eva Lange, Clemens Gröpl, Oliver Kohlbacher, and Andreas Hildebrandt

Published in: Dagstuhl Seminar Proceedings, Volume 5471, Computational Proteomics (2006)

Abstract
A new peak picking algorithm for the analysis of mass spectrometric (MS) data is presented. It is independent of the underlying machine or ionization method, and is able to resolve highly convoluted and asymmetric signals. The method uses the multiscale nature of spectrometric data by first detecting the mass peaks in the wavelet-transformed signal before a given asymmetric peak function is fitted to the raw data. In an optional third stage, the resulting fit can be further improved using techniques from nonlinear optimization. In contrast to currently established techniques (e.g. SNAP, Apex) our algorithm is able to separate overlapping peaks of multiply charged peptides in ESI-MS data of low resolution. Its improved accuracy with respect to peak positions makes it a valuable preprocessing method for MS-based identification and quantification experiments. The method has been validated on a number of different annotated test cases, where it compares favorably in both runtime and accuracy with currently established techniques. An implementation of the algorithm is freely available in our open source framework OpenMS (www.open-ms.de).
Cite as

Eva Lange, Clemens Gröpl, Oliver Kohlbacher, and Andreas Hildebrandt. High-accuracy peak picking of proteomics data. In Computational Proteomics. Dagstuhl Seminar Proceedings, Volume 5471, pp. 1-9, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2006)

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@InProceedings{lange_et_al:DagSemProc.05471.9,
  author =	{Lange, Eva and Gr\"{o}pl, Clemens and Kohlbacher, Oliver and Hildebrandt, Andreas},
  title =	{{High-accuracy peak picking of proteomics data}},
  booktitle =	{Computational Proteomics},
  pages =	{1--9},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2006},
  volume =	{5471},
  editor =	{Christian G. Huber and Oliver Kohlbacher and Knut Reinert},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.05471.9},
  URN =		{urn:nbn:de:0030-drops-5358},
  doi =		{10.4230/DagSemProc.05471.9},
  annote =	{Keywords: Mass spectrometry, peak detection, peak picking}
}
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