@inproceedings{PohleFroehlichDalitzRichteretal.2020, author = {Pohle-Fr{\"o}hlich, Regina and Dalitz, Christoph and Richter, Charlotte and Hahnen, Tobias and St{\"a}udle, Benjamin and Albracht, Kirsten}, title = {Estimation of muscle fascicle orientation in ultrasonic images}, series = {Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5}, booktitle = {Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5}, publisher = {SciTePress}, address = {Set{\´u}bal, Portugal}, isbn = {978-989-758-402-2}, doi = {10.5220/0008933900790086}, pages = {79 -- 86}, year = {2020}, abstract = {We compare four different algorithms for automatically estimating the muscle fascicle angle from ultrasonic images: the vesselness filter, the Radon transform, the projection profile method and the gray level cooccurence matrix (GLCM). The algorithm results are compared to ground truth data generated by three different experts on 425 image frames from two videos recorded during different types of motion. The best agreement with the ground truth data was achieved by a combination of pre-processing with a vesselness filter and measuring the angle with the projection profile method. The robustness of the estimation is increased by applying the algorithms to subregions with high gradients and performing a LOESS fit through these estimates.}, language = {en} } @inproceedings{RekePeterSchulteTiggesetal.2020, author = {Reke, Michael and Peter, Daniel and Schulte-Tigges, Joschua and Schiffer, Stefan and Ferrein, Alexander and Walter, Thomas and Matheis, Dominik}, title = {A Self-Driving Car Architecture in ROS2}, series = {2020 International SAUPEC/RobMech/PRASA Conference, Cape Town, South Africa}, booktitle = {2020 International SAUPEC/RobMech/PRASA Conference, Cape Town, South Africa}, publisher = {IEEE}, address = {New York, NY}, isbn = {978-1-7281-4162-6}, doi = {10.1109/SAUPEC/RobMech/PRASA48453.2020.9041020}, pages = {1 -- 6}, year = {2020}, abstract = {In this paper we report on an architecture for a self-driving car that is based on ROS2. Self-driving cars have to take decisions based on their sensory input in real-time, providing high reliability with a strong demand in functional safety. In principle, self-driving cars are robots. However, typical robot software, in general, and the previous version of the Robot Operating System (ROS), in particular, does not always meet these requirements. With the successor ROS2 the situation has changed and it might be considered as a solution for automated and autonomous driving. Existing robotic software based on ROS was not ready for safety critical applications like self-driving cars. We propose an architecture for using ROS2 for a self-driving car that enables safe and reliable real-time behaviour, but keeping the advantages of ROS such as a distributed architecture and standardised message types. First experiments with an automated real passenger car at lower and higher speed-levels show that our approach seems feasible for autonomous driving under the necessary real-time conditions.}, language = {en} } @inproceedings{RendonSchwagerGhiasietal.2020, author = {Rendon, Carlos and Schwager, Christian and Ghiasi, Mona and Schmitz, Pascal and Bohang, Fakhri and Chico Caminos, Ricardo Alexander and Teixeira Boura, Cristiano Jos{\´e} and Herrmann, Ulf}, title = {Modeling and upscaling of a pilot bayonettube reactor for indirect solar mixed methane reforming}, series = {AIP Conference Proceedings}, booktitle = {AIP Conference Proceedings}, number = {2303}, doi = {10.1063/5.0029974}, pages = {170012-1 -- 170012-9}, year = {2020}, abstract = {A 16.77 kW thermal power bayonet-tube reactor for the mixed reforming of methane using solar energy has been designed and modeled. A test bench for the experimental tests has been installed at the Synlight facility in Juelich, Germany and has just been commissioned. This paper presents the solar-heated reactor design for a combined steam and dry reforming as well as a scaled-up process simulation of a solar reforming plant for methanol production. Solar power towers are capable of providing large amounts of heat to drive high-endothermic reactions, and their integration with thermochemical processes shows a promising future. In the designed bayonet-tube reactor, the conventional burner arrangement for the combustion of natural gas has been substituted by a continuous 930 °C hot air stream, provided by means of a solar heated air receiver, a ceramic thermal storage and an auxiliary firing system. Inside the solar-heated reactor, the heat is transferred by means of convective mechanism mainly; instead of radiation mechanism as typically prevailing in fossil-based industrial reforming processes. A scaled-up solar reforming plant of 50.5 MWth was designed and simulated in Dymola® and AspenPlus®. In comparison to a fossil-based industrial reforming process of the same thermal capacity, a solar reforming plant with thermal storage promises a reduction up to 57 \% of annual natural gas consumption in regions with annual DNI-value of 2349 kWh/m2. The benchmark solar reforming plant contributes to a CO2 avoidance of approx. 79 kilotons per year. This facility can produce a nominal output of 734.4 t of synthesis gas and out of this 530 t of methanol a day.}, language = {en} } @inproceedings{SattlerChicoCaminosAttietal.2020, author = {Sattler, Johannes Christoph and Chico Caminos, Ricardo Alexander and Atti, Vikrama Naga Babu and {\"U}rlings, Nicolas and Dutta, Siddharth and Ruiz, Victor and Kalogirou, Soteris and Ktistis, Panayiotis and Agathokleous, Rafaela and Alexopoulos, Spiros and Teixeira Boura, Cristiano Jos{\´e} and Herrmann, Ulf}, title = {Dynamic simulation tool for a performance evaluation and sensitivity study of a parabolic trough collector system with concrete thermal energy storage}, series = {AIP Conference Proceedings 2303}, booktitle = {AIP Conference Proceedings 2303}, publisher = {American Institute of Physics}, address = {Melville, NY}, issn = {0094-243X}, doi = {10.1063/5.0029277}, pages = {160004}, year = {2020}, language = {de} } @inproceedings{SattlerChicoCaminosUerlingsetal.2020, author = {Sattler, Johannes Christoph and Chico Caminos, Ricardo Alexander and {\"U}rlings, Nicolas and Dutta, Siddharth and Ruiz, Victor and Kalogirou, Soteris and Ktistis, Panayiotis and Agathokleous, Rafaela and Jung, Christian and Alexopoulos, Spiros and Atti, Vikrama Naga Babu and Teixeira Boura, Cristiano Jos{\´e} and Herrmann, Ulf}, title = {Operational experience and behaviour of a parabolic trough collector system with concrete thermal energy storage for process steam generation in Cyprus}, series = {AIP Conference Proceedings}, booktitle = {AIP Conference Proceedings}, number = {2303}, doi = {10.1063/5.0029278}, pages = {140004-1 -- 140004-10}, year = {2020}, abstract = {As part of the transnational research project EDITOR, a parabolic trough collector system (PTC) with concrete thermal energy storage (C-TES) was installed and commissioned in Limassol, Cyprus. The system is located on the premises of the beverage manufacturer KEAN Soft Drinks Ltd. and its function is to supply process steam for the factory's pasteurisation process [1]. Depending on the factory's seasonally varying capacity for beverage production, the solar system delivers between 5 and 25 \% of the total steam demand. In combination with the C-TES, the solar plant can supply process steam on demand before sunrise or after sunset. Furthermore, the C-TES compensates the PTC during the day in fluctuating weather conditions. The parabolic trough collector as well as the control and oil handling unit is designed and manufactured by Protarget AG, Germany. The C-TES is designed and produced by CADE Soluciones de Ingenier{\´i}a, S.L., Spain. In the focus of this paper is the description of the operational experience with the PTC, C-TES and boiler during the commissioning and operation phase. Additionally, innovative optimisation measures are presented.}, language = {en} } @inproceedings{SchmidtsKraftWinkensetal.2020, author = {Schmidts, Oliver and Kraft, Bodo and Winkens, Marvin and Z{\"u}ndorf, Albert}, title = {Catalog integration of low-quality product data by attribute label ranking}, series = {Proceedings of the 9th International Conference on Data Science, Technology and Applications DATA - Volume 1}, booktitle = {Proceedings of the 9th International Conference on Data Science, Technology and Applications DATA - Volume 1}, publisher = {SciTePress}, address = {Set{\´u}bal, Portugal}, isbn = {978-989-758-440-4}, doi = {10.5220/0009831000900101}, pages = {90 -- 101}, year = {2020}, abstract = {The integration of product data from heterogeneous sources and manufacturers into a single catalog is often still a laborious, manual task. Especially small- and medium-sized enterprises face the challenge of timely integrating the data their business relies on to have an up-to-date product catalog, due to format specifications, low quality of data and the requirement of expert knowledge. Additionally, modern approaches to simplify catalog integration demand experience in machine learning, word vectorization, or semantic similarity that such enterprises do not have. Furthermore, most approaches struggle with low-quality data. We propose Attribute Label Ranking (ALR), an easy to understand and simple to adapt learning approach. ALR leverages a model trained on real-world integration data to identify the best possible schema mapping of previously unknown, proprietary, tabular format into a standardized catalog schema. Our approach predicts multiple labels for every attribute of an inpu t column. The whole column is taken into consideration to rank among these labels. We evaluate ALR regarding the correctness of predictions and compare the results on real-world data to state-of-the-art approaches. Additionally, we report findings during experiments and limitations of our approach.}, language = {en} } @inproceedings{SildatkeKarwanniKraftetal.2020, author = {Sildatke, Michael and Karwanni, Hendrik and Kraft, Bodo and Schmidts, Oliver and Z{\"u}ndorf, Albert}, title = {Automated Software Quality Monitoring in Research Collaboration Projects}, series = {ICSEW'20: Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops}, booktitle = {ICSEW'20: Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops}, publisher = {IEEE}, address = {New York, NY}, doi = {10.1145/3387940.3391478}, pages = {603 -- 610}, year = {2020}, abstract = {In collaborative research projects, both researchers and practitioners work together solving business-critical challenges. These projects often deal with ETL processes, in which humans extract information from non-machine-readable documents by hand. AI-based machine learning models can help to solve this problem. Since machine learning approaches are not deterministic, their quality of output may decrease over time. This fact leads to an overall quality loss of the application which embeds machine learning models. Hence, the software qualities in development and production may differ. Machine learning models are black boxes. That makes practitioners skeptical and increases the inhibition threshold for early productive use of research prototypes. Continuous monitoring of software quality in production offers an early response capability on quality loss and encourages the use of machine learning approaches. Furthermore, experts have to ensure that they integrate possible new inputs into the model training as quickly as possible. In this paper, we introduce an architecture pattern with a reference implementation that extends the concept of Metrics Driven Research Collaboration with an automated software quality monitoring in productive use and a possibility to auto-generate new test data coming from processed documents in production. Through automated monitoring of the software quality and auto-generated test data, this approach ensures that the software quality meets and keeps requested thresholds in productive use, even during further continuous deployment and changing input data.}, language = {en} } @inproceedings{TamaldinEschTonolietal.2020, author = {Tamaldin, Noreffendy and Esch, Thomas and Tonoli, Andrea and Reisinger, Karl Heinz and Sprenger, Hanna and Razuli, Hisham}, title = {ERASMUS+ United CBHE Automotive International Collaboration from European to South East Asia}, series = {Proceedings of the 2nd African International Conference on Industrial Engineering and Operations Management}, booktitle = {Proceedings of the 2nd African International Conference on Industrial Engineering and Operations Management}, publisher = {IEOM Society International}, address = {Southfield}, isbn = {978-1-7923-6123-4}, issn = {2169-8767}, pages = {2970 -- 2972}, year = {2020}, abstract = {The industrial revolution especially in the IR4.0 era have driven many states of the art technologies to be introduced. The automotive industry as well as many other key industries have also been greatly influenced. The rapid development of automotive industries in Europe have created wide industry gap between European Union (EU) and developing countries such as in South East Asia (SEA). Indulging this situation, FH JOANNEUM, Austria together with European partners from FH Aachen, Germany and Politecnico di Torino, Italy are taking initiative to close down the gap utilizing the Erasmus+ United Capacity Building in Higher Education grant from EU. A consortium was founded to engage with automotive technology transfer using the European framework to Malaysian, Indonesian and Thailand Higher Education Institutions (HEI) as well as automotive industries in respective countries. This could be achieved by establishing Engineering Knowledge Transfer Unit (EKTU) in respective SEA institutions guided by the industry partners in their respective countries. This EKTU could offer updated, innovative and high-quality training courses to increase graduate's employability in higher education institutions and strengthen relations between HEI and the wider economic and social environment by addressing University-industry cooperation which is the regional priority for Asia. It is expected that, the Capacity Building Initiative would improve the quality of higher education and enhancing its relevance for the labor market and society in the SEA partners. The outcome of this project would greatly benefit the partners in strong and complementary partnership targeting the automotive industry and enhanced larger scale international cooperation between the European and SEA partners. It would also prepare the SEA HEI in sustainable partnership with Automotive industry in the region as a mean of income generation in the future.}, language = {en} } @inproceedings{ThomaFisherBertrandetal.2020, author = {Thoma, Andreas and Fisher, Alex and Bertrand, Olivier and Braun, Carsten}, title = {Evaluation of possible flight strategies for close object evasion from bumblebee experiments}, series = {Living Machines 2020: Biomimetic and Biohybrid Systems}, booktitle = {Living Machines 2020: Biomimetic and Biohybrid Systems}, editor = {Vouloutsi, Vasiliki and Mura, Anna and Tauber, Falk and Speck, Thomas and Prescott, Tony J. and Verschure, Paul F. M. J.}, publisher = {Springer}, address = {Cham}, isbn = {978-3-030-64312-6}, doi = {10.1007/978-3-030-64313-3_34}, pages = {354 -- 365}, year = {2020}, language = {en} } @inproceedings{ThomaFisherBraun2020, author = {Thoma, Andreas and Fisher, Alex and Braun, Carsten}, title = {Improving the px4 avoid algorithm by bio-inspired flight strategies}, series = {DLRK2020 - „Luft- und Raumfahrt - Verantwortung in allen Dimensionen"}, booktitle = {DLRK2020 - „Luft- und Raumfahrt - Verantwortung in allen Dimensionen"}, doi = {10.25967/530183}, pages = {10 Seiten}, year = {2020}, language = {en} }