TY - CHAP A1 - Hofmann, Till A1 - Mataré, Victor A1 - Schiffer, Stefan A1 - Ferrein, Alexander A1 - Lakemeyer, Gerhard T1 - Constraint-based online transformation of abstract plans into executable robot actions T2 - Proceedings of the 2018 AAAI Spring Symposium on Integrating Representation, Reasoning, Learning, and Execution for Goal Directed Autonomy Y1 - 2018 SP - 549 EP - 553 ER - TY - CHAP A1 - Ferrein, Alexander A1 - Schiffer, Stefan A1 - Kallweit, Stephan T1 - The ROSIN Education Concept - Fostering ROS Industrial-Related Robotics Education in Europe T2 - ROBOT 2017: Third Iberian Robotics Conference Y1 - 2018 SN - 978-3-319-70836-2 U6 - https://doi.org/10.1007/978-3-319-70836-2_31 N1 - Advances in Intelligent Systems and Computing, vol 694; (AISC, volume 694) SP - 370 EP - 381 PB - Springer CY - Cham ER - TY - CHAP A1 - Hofmann, Till A1 - Mataré, Victor A1 - Neumann, Tobias A1 - Schönitz, Sebastian A1 - Henke, Christoph A1 - Limpert, Nicolas A1 - Niemueller, Tim A1 - Ferrein, Alexander A1 - Jeschke, Sabina A1 - Lakemeyer, Gerhard T1 - Enhancing Software and Hardware Reliability for a Successful Participation in the RoboCup Logistics League 2017 Y1 - 2018 SN - 978-3-030-00308-1 U6 - https://doi.org/10.1007/978-3-030-00308-1_40 N1 - Lecture Notes in Computer Science, vol 11175 SP - 486 EP - 497 PB - Springer CY - Cham ER - TY - JOUR A1 - Schiffer, Stefan A1 - Ferrein, Alexander T1 - ERIKA—Early Robotics Introduction at Kindergarten Age JF - Multimodal Technologies Interact N2 - In this work, we report on our attempt to design and implement an early introduction to basic robotics principles for children at kindergarten age. One of the main challenges of this effort is to explain complex robotics contents in a way that pre-school children could follow the basic principles and ideas using examples from their world of experience. What sets apart our effort from other work is that part of the lecturing is actually done by a robot itself and that a quiz at the end of the lesson is done using robots as well. The humanoid robot Pepper from Softbank, which is a great platform for human–robot interaction experiments, was used to present a lecture on robotics by reading out the contents to the children making use of its speech synthesis capability. A quiz in a Runaround-game-show style after the lecture activated the children to recap the contents they acquired about how mobile robots work in principle. In this quiz, two LEGO Mindstorm EV3 robots were used to implement a strongly interactive scenario. Besides the thrill of being exposed to a mobile robot that would also react to the children, they were very excited and at the same time very concentrated. We got very positive feedback from the children as well as from their educators. To the best of our knowledge, this is one of only few attempts to use a robot like Pepper not as a tele-teaching tool, but as the teacher itself in order to engage pre-school children with complex robotics contents. Y1 - 2018 U6 - https://doi.org/10.3390/mti2040064 SN - 2414-4088 VL - 2 IS - 4 PB - MDPI CY - Basel ER - TY - JOUR A1 - Schwabedal, Justus T. C. A1 - Sippel, Daniel A1 - Brandt, Moritz D. A1 - Bialonski, Stephan T1 - Automated Classification of Sleep Stages and EEG Artifacts in Mice with Deep Learning N2 - Sleep scoring is a necessary and time-consuming task in sleep studies. In animal models (such as mice) or in humans, automating this tedious process promises to facilitate long-term studies and to promote sleep biology as a data-driven f ield. We introduce a deep neural network model that is able to predict different states of consciousness (Wake, Non-REM, REM) in mice from EEG and EMG recordings with excellent scoring results for out-of-sample data. Predictions are made on epochs of 4 seconds length, and epochs are classified as artifactfree or not. The model architecture draws on recent advances in deep learning and in convolutional neural networks research. In contrast to previous approaches towards automated sleep scoring, our model does not rely on manually defined features of the data but learns predictive features automatically. We expect deep learning models like ours to become widely applied in different fields, automating many repetitive cognitive tasks that were previously difficult to tackle. Y1 - 2018 U6 - https://doi.org/10.48550/arXiv.1809.08443 ER - TY - CHAP A1 - Richter, Charlotte A1 - Braunstein, Bjoern A1 - Stäudle, Benjamin A1 - Attias, Julia A1 - Suess, Alexander A1 - Weber, T. A1 - Rittweger, Joern A1 - Green, David A. A1 - Albracht, Kirsten T1 - In vivo fascicle length of the gastrocnemius muscle during walking in simulated martian gravity using two different body weight support devices T2 - 23rd Annual Congress of the European College of Sport Science, Dublin, Irland Y1 - 2018 ER - TY - JOUR A1 - Bernecker, Andreas A1 - Klier, Julia A1 - Stern, Sebastian A1 - Thiel, Lea T1 - Sustaining high performance beyond public-sector pilot projects. Y1 - 2018 IS - September 2018 ER - TY - RPRT A1 - Bernecker, Andreas A1 - Boyer, Pierre A1 - Gathmann, Christina T1 - The Role of Electoral Incentives for Policy Innovation: Evidence from the US Welfare Reform T2 - CESifo Working Paper Y1 - 2018 SN - ISSN 2364‐1428 (electronic version) IS - No. 6964 ER - TY - THES A1 - Keinz, Jan T1 - Optimization of a Dry Low NOx Micromix Combustor for an Industrial Gas Turbine Using Hydrogen-Rich Syngas Fuel Y1 - 2018 N1 - Dissertation submitted for the degree of Doctor of Engineering Sciences and Technology ; in Cooperation with Aachen university of Applied Sciences, Department Aerospace Technology; Thesis director: Prof. P. Hendrick; Thesis co-director: Prof. H. Funke PB - Université Libre de Bruxelles - Brussels School of Engineering Aero-Thermo-Mechanics CY - Brüssel ER - TY - JOUR A1 - Engel, Mareike A1 - Holtmann, Dirk A1 - Ulber, Roland A1 - Tippkötter, Nils T1 - Increased Biobutanol Production by Mediator‐Less Electro‐Fermentation JF - Biotechnology Journal N2 - A future bio-economy should not only be based on renewable raw materials but also in the raise of carbon yields of existing production routes. Microbial electrochemical technologies are gaining increased attention for this purpose. In this study, the electro-fermentative production of biobutanol with C. acetobutylicum without the use of exogenous mediators is investigated regarding the medium composition and the reactor design. It is shown that the use of an optimized synthetic culture medium allows higher product concentrations, increased biofilm formation, and higher conductivities compared to a synthetic medium supplemented with yeast extract. Moreover, the optimization of the reactor system results in a doubling of the maximum product concentrations for fermentation products. When a working electrode is polarized at −600 mV vs. Ag/AgCl, a shift from butyrate to acetone and butanol production is induced. This leads to an increased final solvent yield of Yᴀᴃᴇ = 0.202 gg⁻¹ (control 0.103 gg⁻¹), which is also reflected in a higher carbon efficiency of 37.6% compared to 23.3% (control) as well as a fourfold decrease in simplified E-factor to 0.43. The results are promising for further development of biobutanol production in bioelectrochemical systems in order to fulfil the principles of Green Chemistry. Y1 - 2018 U6 - https://doi.org/10.1002/biot.201800514 SN - 1860-7314 VL - 14 IS - 4 PB - Wiley-VCH CY - Weinheim ER -