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 - https://doi.org/10.1109/REM.2019.8744132 SP - 1 EP - 6 ER - TY - CHAP A1 - Leise, Philipp A1 - Altherr, Lena A1 - Simon, Nicolai A1 - Pelz, Peter F. T1 - Finding global-optimal gearbox designs for battery electric vehicles T2 - Optimization of complex systems - theory, models, algorithms and applications : WCGO 2019 N2 - In order to maximize the possible travel distance of battery electric vehicles with one battery charge, it is mandatory to adjust all components of the powertrain carefully to each other. While current vehicle designs mostly simplify the powertrain rigorously and use an electric motor in combination with a gearbox with only one fixed transmission ratio, the use of multi-gear systems has great potential. First, a multi-speed system is able to improve the overall energy efficiency. Secondly, it is able to reduce the maximum momentum and therefore to reduce the maximum current provided by the traction battery, which results in a longer battery lifetime. In this paper, we present a systematic way to generate multi-gear gearbox designs that—combined with a certain electric motor—lead to the most efficient fulfillment of predefined load scenarios and are at the same time robust to uncertainties in the load. Therefore, we model the electric motor and the gearbox within a Mixed-Integer Nonlinear Program, and optimize the efficiency of the mechanical parts of the powertrain. By combining this mathematical optimization program with an unsupervised machine learning algorithm, we are able to derive global-optimal gearbox designs for practically relevant momentum and speed requirements. KW - Powertrain KW - Gearbox KW - Optimization KW - BEV KW - WLTP Y1 - 2019 SN - 978-3-030-21802-7 U6 - https://doi.org/10.1007/978-3-030-21803-4_91 SP - 916 EP - 925 PB - Springer CY - Cham ER - TY - CHAP A1 - Stenger, David A1 - Altherr, Lena A1 - Abel, Dirk T1 - Machine learning and metaheuristics for black-box optimization of product families: a case-study investigating solution quality vs. computational overhead T2 - Operations Research Proceedings 2018 N2 - In product development, numerous design decisions have to be made. Multi-domain virtual prototyping provides a variety of tools to assess technical feasibility of design options, however often requires substantial computational effort for just a single evaluation. A special challenge is therefore the optimal design of product families, which consist of a group of products derived from a common platform. Finding an optimal platform configuration (stating what is shared and what is individually designed for each product) and an optimal design of all products simultaneously leads to a mixed-integer nonlinear black-box optimization model. We present an optimization approach based on metamodels and a metaheuristic. To increase computational efficiency and solution quality, we compare different types of Gaussian process regression metamodels adapted from the domain of machine learning, and combine them with a genetic algorithm. We illustrate our approach on the example of a product family of electrical drives, and investigate the trade-off between solution quality and computational overhead. KW - Product family optimization KW - Mixed-integer nonlinear black-box optimization KW - Engineering optimization KW - Machine learning Y1 - 2019 SN - 978-3-030-18499-5 (Print) SN - 978-3-030-18500-8 (Online) U6 - https://doi.org/10.1007/978-3-030-18500-8_47 SP - 379 EP - 385 PB - Springer CY - Cham ER - TY - CHAP A1 - Hofmann, Till A1 - Limpert, Nicolas A1 - Mataré, Victor A1 - Ferrein, Alexander A1 - Lakemeyer, Gerhard T1 - Winning the RoboCup Logistics League with Fast Navigation, Precise Manipulation, and Robust Goal Reasoning T2 - RoboCup 2019: Robot World Cup XXIII. RoboCup Y1 - 2019 SN - 978-3-030-35699-6 U6 - https://doi.org/10.1007/978-3-030-35699-6_41 N1 - Lecture Notes in Computer Science, vol 11531 SP - 504 EP - 516 PB - Springer CY - Cham ER - TY - CHAP A1 - Finger, Felix A1 - Khalsa, R. A1 - Kreyer, Jörg A1 - Mayntz, Joscha A1 - Braun, Carsten A1 - Dahmann, Peter A1 - Esch, Thomas A1 - Kemper, Hans A1 - Schmitz, O. A1 - Bragard, Michael T1 - An approach to propulsion system modelling for the conceptual design of hybrid-electric general aviation aircraft T2 - Deutscher Luft- und Raumfahrtkongress 2019, 30.9.-2.10.2019, Darmstadt N2 - In this paper, an approach to propulsion system modelling for hybrid-electric general aviation aircraft is presented. Because the focus is on general aviation aircraft, only combinations of electric motors and reciprocating combustion engines are explored. Gas turbine hybrids will not be considered. The level of the component's models is appropriate for the conceptual design stage. They are simple and adaptable, so that a wide range of designs with morphologically different propulsive system architectures can be quickly compared. Modelling strategies for both mass and efficiency of each part of the propulsion system (engine, motor, battery and propeller) will be presented. Y1 - 2019 ER - TY - CHAP A1 - Sadeghfam, Arash A1 - Sadeghi-Ahangar, A. A1 - Elgamal, Abdelrahman A1 - Heuermann, Holger T1 - Design and Development of a Novel Self-Igniting Microwave Plasma Jet for Industrial Applications T2 - IEEE MTT-S International Microwave Symposium Digest Y1 - 2019 SN - 978-172811309-8 SP - 63 EP - 66 ER - TY - CHAP A1 - Alhwarin, Faraj A1 - Ferrein, Alexander A1 - Scholl, Ingrid T1 - An Efficient Hashing Algorithm for NN Problem in HD Spaces T2 - Lecture Notes in Computer Science Y1 - 2019 SN - 978-303005498-4 U6 - https://doi.org/10.1007/978-3-030-05499-1_6 N1 - 7th International Conference on Pattern Recognition Applications and Methods, ICPRAM 2018; Funchal; Portugal; 16 January 2018 through 18 January 2018; Code 222779 SP - 101 EP - 115 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 - Ferrein, Alexander A1 - Bharatheesha, Mukunda A1 - Schiffer, Stefan A1 - Corbato, Carlos Hernandez T1 - TRROS 2018 : Teaching Robotics with ROS Workshop at ERF 2018; Proceedings of the Workshop on Teaching Robotics with ROS (held at ERF 2018), co-located with European Robotics Forum 2018 (ERF 2018), Tampere, Finland, March 15th, 2018 T2 - CEUR Workshop Proceedings Y1 - 2019 SN - 1613-0073 IS - Vol-2329 ER - TY - CHAP A1 - Ferrein, Alexander A1 - Scholl, Ingrid A1 - Neumann, Tobias A1 - Krückel, Kai A1 - Schiffer, Stefan T1 - A system for continuous underground site mapping and exploration Y1 - 2019 U6 - https://doi.org/10.5772/intechopen.85859 ER - TY - JOUR A1 - Claer, Mario A1 - Ferrein, Alexander A1 - Schiffer, Stefan T1 - Calibration of a Rotating or Revolving Platform with a LiDAR Sensor JF - Applied Sciences Y1 - 2019 U6 - https://doi.org/10.3390/app9112238 SN - 2076-3417 VL - Volume 9 IS - issue 11, 2238 PB - MDPI CY - Basel 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, Ashraf 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 - https://doi.org/10.1371/journal.pone.0222452 ER - TY - CHAP A1 - Kirsch, Maximilian A1 - Mataré, Victor A1 - Ferrein, Alexander A1 - Schiffer, Stefan T1 - Integrating golog++ and ROS for Practical and Portable High-level Control T2 - Proceedings of the 12th International Conference on Agents and Artificial Intelligence - Volume 2 N2 - The field of Cognitive Robotics aims at intelligent decision making of autonomous robots. It has matured over the last 25 or so years quite a bit. That is, a number of high-level control languages and architectures have emerged from the field. One concern in this regard is the action language GOLOG. GOLOG has been used in a rather large number of applications as a high-level control language ranging from intelligent service robots to soccer robots. For the lower level robot software, the Robot Operating System (ROS) has been around for more than a decade now and it has developed into the standard middleware for robot applications. ROS provides a large number of packages for standard tasks in robotics like localisation, navigation, and object recognition. Interestingly enough, only little work within ROS has gone into the high-level control of robots. In this paper, we describe our approach to marry the GOLOG action language with ROS. In particular, we present our architecture on inte grating golog++, which is based on the GOLOG dialect Readylog, with the Robot Operating System. With an example application on the Pepper service robot, we show how primitive actions can be easily mapped to the ROS ActionLib framework and present our control architecture in detail. Y1 - 2020 U6 - https://doi.org/10.5220/0008984406920699 N1 - Proceedings of the 12th International Conference on Agents and Artificial Intelligence: ICAART 2020, Valletta, Malta SP - 692 EP - 699 PB - SciTePress CY - Setúbal, Portugal ER - TY - JOUR A1 - Fiedler, Thomas M. A1 - Ladd, Mark E. A1 - Clemens, Markus A1 - Bitz, Andreas T1 - Safety of subjects during radiofrequency exposure in ultra-high-field magnetic resonance imaging JF - IEEE Letters on Electromagnetic Compatibility Practice and Applications N2 - Magnetic resonance imaging (MRI) is one of the most important medical imaging techniques. Since the introduction of MRI in the mid-1980s, there has been a continuous trend toward higher static magnetic fields to obtain i.a. a higher signal-to-noise ratio. The step toward ultra-high-field (UHF) MRI at 7 Tesla and higher, however, creates several challenges regarding the homogeneity of the spin excitation RF transmit field and the RF exposure of the subject. In UHF MRI systems, the wavelength of the RF field is in the range of the diameter of the human body, which can result in inhomogeneous spin excitation and local SAR hotspots. To optimize the homogeneity in a region of interest, UHF MRI systems use parallel transmit systems with multiple transmit antennas and time-dependent modulation of the RF signal in the individual transmit channels. Furthermore, SAR increases with increasing field strength, while the SAR limits remain unchanged. Two different approaches to generate the RF transmit field in UHF systems using antenna arrays close and remote to the body are investigated in this letter. Achievable imaging performance is evaluated compared to typical clinical RF transmit systems at lower field strength. The evaluation has been performed under consideration of RF exposure based on local SAR and tissue temperature. Furthermore, results for thermal dose as an alternative RF exposure metric are presented. Y1 - 2020 SN - 2637-6423 U6 - https://doi.org/10.1109/LEMCPA.2020.3029747 VL - 2 IS - 3 SP - 1 EP - 8 PB - IEEE CY - New York, NY ER - TY - JOUR A1 - Hüning, Felix A1 - Backes, Andreas T1 - Direct observation of large Barkhausen jump in thin Vicalloy wires JF - IEEE Magnetics Letters Y1 - 2020 SN - 1949-307X U6 - https://doi.org/10.1109/LMAG.2020.3046411 VL - 11 IS - Art. 2506504 SP - 1 EP - 4 PB - IEEE CY - New York, NY ER - TY - CHAP A1 - Dinghofer, Kai A1 - Hartung, Frank T1 - Analysis of Criteria for the Selection of Machine Learning Frameworks T2 - 2020 International Conference on Computing, Networking and Communications (ICNC) N2 - With the many achievements of Machine Learning in the past years, it is likely that the sub-area of Deep Learning will continue to deliver major technological breakthroughs [1]. In order to achieve best results, it is important to know the various different Deep Learning frameworks and their respective properties. This paper provides a comparative overview of some of the most popular frameworks. First, the comparison methods and criteria are introduced and described with a focus on computer vision applications: Features and Uses are examined by evaluating papers and articles, Adoption and Popularity is determined by analyzing a data science study. Then, the frameworks TensorFlow, Keras, PyTorch and Caffe are compared based on the previously described criteria to highlight properties and differences. Advantages and disadvantages are compared, enabling researchers and developers to choose a framework according to their specific needs. Y1 - 2020 U6 - https://doi.org/10.1109/ICNC47757.2020.9049650 N1 - 2020 International Conference on Computing, Networking and Communications (ICNC), 17-20 February 2020, Big Island, HI, USA SP - 373 EP - 377 PB - IEEE CY - New York, NY ER - TY - JOUR A1 - Köhler, Klemens T1 - A conflict theory perspective of IT attacks – consequences for IT security education N2 - Cyberspace is "the environment formed by physical and non-physical components to store, modify, and exchange data using computer networks" (NATO CCDCOE). Beyond that, it is an environment where people interact. IT attacks are hostile, non-cooperative interactions that can be described with conflict theory. Applying conflict theory to IT security leads to different objectives for end-user education, requiring different formats like agency-based competence developing games. Y1 - 2020 IS - Preprint ER - TY - CHAP A1 - Leise, Philipp A1 - Breuer, Tim A1 - Altherr, Lena A1 - Pelz, Peter F. T1 - Development, validation and assessment of a resilient pumping system T2 - Proceedings of the Joint International Resilience Conference, JIRC2020 N2 - The development of resilient technical systems is a challenging task, as the system should adapt automatically to unknown disturbances and component failures. To evaluate different approaches for deriving resilient technical system designs, we developed a modular test rig that is based on a pumping system. On the basis of this example system, we present metrics to quantify resilience and an algorithmic approach to improve resilience. This approach enables the pumping system to automatically react on unknown disturbances and to reduce the impact of component failures. In this case, the system is able to automatically adapt its topology by activating additional valves. This enables the system to still reach a minimum performance, even in case of failures. Furthermore, timedependent disturbances are evaluated continuously, deviations from the original state are automatically detected and anticipated in the future. This allows to reduce the impact of future disturbances and leads to a more resilient system behaviour. KW - water supply system KW - fault detection KW - anticipation strategy Y1 - 2020 SN - 978-90-365-5095-6 N1 - Joint International Resilience Conference 2020. Interconnected: Resilience Innovations for Sustainable Development Goals. 23 - 27 November, 2020, Singapore SP - 97 EP - 100 ER - TY - CHAP A1 - Lorenz, Imke-Sophie A1 - Altherr, Lena A1 - Pelz, Peter F. T1 - Resilience enhancement of critical infrastructure – graph-theoretical resilience analysis of the water distribution system in the German city of Darmstadt T2 - 14th WCEAM Proceedings N2 - Water suppliers are faced with the great challenge of achieving high-quality and, at the same time, low-cost water supply. Since climatic and demographic influences will pose further challenges in the future, the resilience enhancement of water distribution systems (WDS), i.e. the enhancement of their capability to withstand and recover from disturbances, has been in particular focus recently. To assess the resilience of WDS, graph-theoretical metrics have been proposed. In this study, a promising approach is first physically derived analytically and then applied to assess the resilience of the WDS for a district in a major German City. The topology based resilience index computed for every consumer node takes into consideration the resistance of the best supply path as well as alternative supply paths. This resistance of a supply path is derived to be the dimensionless pressure loss in the pipes making up the path. The conducted analysis of a present WDS provides insight into the process of actively influencing the resilience of WDS locally and globally by adding pipes. The study shows that especially pipes added close to the reservoirs and main branching points in the WDS result in a high resilience enhancement of the overall WDS. KW - Resilient infrastructure KW - Resilience assessment KW - Resilience metric graph theory KW - Water distribution system KW - Case study Y1 - 2020 SN - 978-3-030-64228-0 SN - 978-3-030-64227-3 U6 - https://doi.org/10.1007/978-3-030-64228-0_13 N1 - 14th WCEAM Proceedings. World Congress on Engineering Asset Management, 28-31 July 2019, Singapore Part of the Lecture Notes in Mechanical Engineering book series (LNME) SP - 137 EP - 149 PB - Springer CY - Cham ER - TY - CHAP A1 - Schneider, Dominik A1 - Wisselink, Frank A1 - Nölle, Nikolai A1 - Czarnecki, Christian ED - Bruhn, Manfred ED - Hadwich, Karsten T1 - Influence of artificial intelligence on commercial interactions in the consumer market T2 - Automatisierung und Personalisierung von Dienstleistungen : Methoden – Potenziale – Einsatzfelder N2 - Recently, novel AI-based services have emerged in the consumer market. AI-based services can affect the way consumers take commercial decisions. Research on the influence of AI on commercial interactions is in its infancy. In this chapter, a framework creating a first overview of the influence of AI on commercial interactions is introduced. This framework summarizes the findings of comparing numerous customer journeys of novel AI-based services with corresponding non-AI equivalents. Y1 - 2020 SN - 978-3-658-30167-5 (Print) SN - 978-3-658-30168-2 (Online) U6 - https://doi.org/10.1007/978-3-658-30168-2_7 SP - 183 EP - 205 PB - Springer Gabler CY - Wiesbaden ER -