TY - CHAP A1 - Donner, Ralf A1 - Rabel, Matthias A1 - Scholl, Ingrid A1 - Ferrein, Alexander A1 - Donner, Marc A1 - Geier, Andreas A1 - John, André A1 - Köhler, Christian A1 - Varga, Sebastian T1 - Die Extraktion bergbaulich relevanter Merkmale aus 3D-Punktwolken eines untertagetauglichen mobilen Multisensorsystems T2 - Tagungsband Geomonitoring Y1 - 2019 U6 - http://dx.doi.org/10.15488/4515 SP - 91 EP - 110 ER - TY - CHAP A1 - Steinbauer, Gerald A1 - Ferrein, Alexander T1 - CogRob 2018 : Cognitive Robotics Workshop. Proceedings of the 11th Cognitive Robotics Workshop 2018 co-located with 16th International Conference on Principles of Knowledge Representation and Reasoning (KR 2018). Tempe, AZ, USA, October 27th, 2018. T2 - CEUR workshop proceedings Y1 - 2019 SN - 1613-0073 N1 - edited by Gerald Steinbauer, Alexander Ferrein IS - Vol-2325 ER - TY - CHAP A1 - Schiffer, Fabian A1 - Bragard, Michael T1 - Cascaded LQ and Field-Oriented Control of a Mobile Inverse Pendulum (Segway) with Permanent Magnet Synchronous Machines T2 - 2019 20th International Conference on Research and Education in Mechatronics (REM) Y1 - 2019 SN - 978-1-5386-9257-8 U6 - http://dx.doi.org/10.1109/REM.2019.8744101 SP - 1 EP - 8 ER - TY - CHAP A1 - Bragard, Michael A1 - Sube, Maike A1 - Schneider, Maike A1 - Jungemann, Christoph T1 - Introducing a Cross-University Bachelor’s Programme with Orientation Semester - Enabling a Permeable Academic Education System T2 - 2019 20th International Conference on Research and Education in Mechatronics (REM) Y1 - 2019 SN - 978-1-5386-9257-8 U6 - http://dx.doi.org/10.1109/REM.2019.8744132 SP - 1 EP - 6 ER - TY - JOUR A1 - Orzada, Stephan A1 - Solbach, Klaus A1 - Gratz, Marcel A1 - Brunheim, Sascha A1 - Fiedler, Thomas M. A1 - Johst, Sören A1 - Bitz, Andreas A1 - Shooshtary, Samaneh A1 - Abuelhaija, Asjraf A1 - Voelker, Maximilian N. A1 - Rietsch, Stefan H. G. A1 - Kraff, Oliver A1 - Maderwald, Stefan A1 - Flöser, Martina A1 - Oehmingen, Mark A1 - Quick, Harald H. A1 - Ladd, Mark E. T1 - A 32-channel parallel transmit system add-on for 7T MRI JF - Plos one Y1 - 2019 U6 - http://dx.doi.org/10.1371/journal.pone.0222452 ER - TY - CHAP A1 - Weber, Niklas A1 - Wolf, Martin ED - Barton, Thomas T1 - Datenerhebung für die CDG-Forschung T2 - Prozesse, Technologie, Anwendungen, Systeme und Management 2017 : angewandte Forschung in der Wirtschaftsinformatik : Tagungsband zur 30. AKWI-Jahrestagung vom 17.09.2017 bis 20.09.2017 an der Hochschule Aschaffenburg / Arbeitskreis Wirtschaftsinformatik an Fachhochschulen (AKWI) Y1 - 2017 SN - 978-3-944330-56-3 SP - 218 EP - 227 PB - mana-Buch CY - Heide ER - TY - JOUR A1 - Noureddine, Yacine A1 - Kraff, Oliver A1 - Ladd, Mark E. A1 - Wrede, Karsten A1 - Chen, Bixia A1 - Quick, Harald H. A1 - Schaefers, Georg A1 - Bitz, Andreas T1 - Radiofrequency induced heating around aneurysm clips using a generic birdcage head coil at 7 Tesla under consideration of the minimum distance to decouple multiple aneurysm clips JF - Magnetic Resonance in Medicine Y1 - 2019 U6 - http://dx.doi.org/10.1002/mrm.27835 SN - 1522-2594 IS - Early view SP - 1 EP - 17 PB - Wiley CY - Weinheim ER - TY - BOOK ED - Wolf, Martin R. ED - Barton, Thomas ED - Herrmann, Frank ED - Meister, Vera G. ED - Müller, Christian ED - Seel, Christian T1 - Angewandte Forschung in der Wirtschaftsinformatik BT - Tagungsband zur 32. AKWI-Jahrestagung vom 15.09.2019 bis 18.09.2019 an der Fachhochschule für Angewandte Wissenschaften Aachen Y1 - 2019 SN - 978-3-944330-62-4 N1 - Buch ist in der Bereichsbibliothek Eupener Str. vorhanden. Signatur: 21 QGT 95-2019 PB - Mana-Buch CY - Heide ER - TY - JOUR A1 - Orzada, Stephan A1 - Fiedler, Thomas M. A1 - Bitz, Andreas A1 - Ladd, Mark E. A1 - Quick, Harald H. T1 - Local SAR compression with overestimation control to reduce maximum relative SAR overestimation and improve multi-channel RF array performance JF - Magnetic Resonance Materials in Physics, Biology and Medicine N2 - Objective In local SAR compression algorithms, the overestimation is generally not linearly dependent on actual local SAR. This can lead to large relative overestimation at low actual SAR values, unnecessarily constraining transmit array performance. Method Two strategies are proposed to reduce maximum relative overestimation for a given number of VOPs. The first strategy uses an overestimation matrix that roughly approximates actual local SAR; the second strategy uses a small set of pre-calculated VOPs as the overestimation term for the compression. Result Comparison with a previous method shows that for a given maximum relative overestimation the number of VOPs can be reduced by around 20% at the cost of a higher absolute overestimation at high actual local SAR values. Conclusion The proposed strategies outperform a previously published strategy and can improve the SAR compression where maximum relative overestimation constrains the performance of parallel transmission. Y1 - 2020 SN - 1352-8661 U6 - http://dx.doi.org/10.1007/s10334-020-00890-0 IS - 34 (2021) SP - 153 EP - 164 PB - Springer CY - Heidelberg ER - TY - CHAP A1 - Chajan, Eduard A1 - Schulte-Tigges, Joschua A1 - Reke, Michael A1 - Ferrein, Alexander A1 - Matheis, Dominik A1 - Walter, Thomas T1 - GPU based model-predictive path control for self-driving vehicles T2 - IEEE Intelligent Vehicles Symposium (IV) N2 - One central challenge for self-driving cars is a proper path-planning. Once a trajectory has been found, the next challenge is to accurately and safely follow the precalculated path. The model-predictive controller (MPC) is a common approach for the lateral control of autonomous vehicles. The MPC uses a vehicle dynamics model to predict the future states of the vehicle for a given prediction horizon. However, in order to achieve real-time path control, the computational load is usually large, which leads to short prediction horizons. To deal with the computational load, the control algorithm can be parallelized on the graphics processing unit (GPU). In contrast to the widely used stochastic methods, in this paper we propose a deterministic approach based on grid search. Our approach focuses on systematically discovering the search area with different levels of granularity. To achieve this, we split the optimization algorithm into multiple iterations. The best sequence of each iteration is then used as an initial solution to the next iteration. The granularity increases, resulting in smooth and predictable steering angle sequences. We present a novel GPU-based algorithm and show its accuracy and realtime abilities with a number of real-world experiments. KW - Heuristic algorithms KW - Computational modeling KW - model-predictive control KW - GPU KW - autonomous driving Y1 - 2021 SN - 978-1-7281-5394-0 U6 - http://dx.doi.org/10.1109/IV48863.2021.9575619 N1 - 2021 IEEE Intelligent Vehicles Symposium (IV) July 11-17, 2021. Nagoya, Japan SP - 1243 EP - 1248 PB - IEEE ER -