@inproceedings{KunfermannDrumm2005,
  author    = {Kunfermann, Philipp and Drumm, Christian},
  title     = {Lifting XML schemas to ontologies - the concept finder algorithm},
  series = {MEDIATE 2005 First International Workshop on Mediation in Semantic Web Services Proceedings of the First International Workshop on Mediation in Semantic Web Services (MEDIATE 2005)},
  booktitle = {MEDIATE 2005 First International Workshop on Mediation in Semantic Web Services Proceedings of the First International Workshop on Mediation in Semantic Web Services (MEDIATE 2005)},
  pages     = {113 -- 122},
  year      = {2005},
  language  = {en}
}
@inproceedings{WiesenEngemannLimpertetal.2018,
  author    = {Wiesen, Patrick and Engemann, Heiko and Limpert, Nicolas and Kallweit, Stephan},
  title     = {Learning by Doing - Mobile Robotics in the FH Aachen ROS Summer School},
  series = {European Robotics Forum 2018, TRROS18 Workshop},
  booktitle = {European Robotics Forum 2018, TRROS18 Workshop},
  pages     = {47 -- 58},
  year      = {2018},
  language  = {en}
}
@inproceedings{SerrorHenzeHacketal.2018,
  author    = {Serror, Martin and Henze, Martin and Hack, Sacha and Schuba, Marko and Wehrle, Klaus},
  title     = {Towards in-network security for smart homes},
  series = {13th International Conference on Availability, Reliability and Security, ARES 2018; Hamburg; Germany; 27 August 2018 through 30 August 2018},
  booktitle = {13th International Conference on Availability, Reliability and Security, ARES 2018; Hamburg; Germany; 27 August 2018 through 30 August 2018},
  isbn      = {978-145036448-5},
  doi       = {10.1145/3230833.3232802},
  pages     = {Article numer 3232802},
  year      = {2018},
  language  = {en}
}
@inproceedings{KromeSander2018,
  author    = {Krome, Cornelia and Sander, Volker},
  title     = {Time series analysis with apache spark and its applications to energy informatics},
  series = {Proceedings of the 7th DACH+ Conference on Energy Informatics},
  booktitle = {Proceedings of the 7th DACH+ Conference on Energy Informatics},
  doi       = {10.1186/s42162-018-0043-1},
  year      = {2018},
  abstract  = {In energy economy forecasts of different time series are rudimentary. In this study, a prediction for the German day-ahead spot market is created with Apache Spark and R. It is just an example for many different applications in virtual power plant environments. Other examples of use as intraday price processes, load processes of machines or electric vehicles, real time energy loads of photovoltaic systems and many more time series need to be analysed and predicted. This work gives a short introduction into the project where this study is settled. It describes the time series methods that are used in energy industry for forecasts shortly. As programming technique Apache Spark, which is a strong cluster computing technology, is utilised. Today, single time series can be predicted. The focus of this work is on developing a method to parallel forecasting, to process multiple time series simultaneously with R and Apache Spark.},
  language  = {en}
}
@inproceedings{Matcha2016,
  author    = {Matcha, Heike},
  title     = {From Designing Buildings from Systems to Designing Systems for Buildings},
  series = {Complexity \& Simplicity - Proceedings of the 34th eCAADe Conference - Volume 1},
  booktitle = {Complexity \& Simplicity - Proceedings of the 34th eCAADe Conference - Volume 1},
  editor    = {Herneoja, Aulikki and {\"O}sterlund, Toni and Markkanen, Piia},
  publisher = {ECAADe},
  address   = {Oulu, Finland},
  doi       = {10.52842/conf.ecaade.2016.1.237},
  pages     = {237 -- 240},
  year      = {2016},
  abstract  = {We study the novel possibilities computer aided design and production open up for the design of building systems. Such systems today can, via individualized mass production, consist of a larger number and more complex parts than previously and therefore be assembled into more complex wholes. This opens up the possibility of designing specialized systems specifically for single buildings. The common order of starting with a building system and designing a building using this system can be reversed to designing a building first and then developing a system specifically for that building. We present and discuss research that incorporates students design projects into research work and fosters links between research and teaching.},
  language  = {en}
}
@inproceedings{Huening2019,
  author    = {H{\"u}ning, Felix},
  title     = {Complexity for heterogeneous classes: teaching embedded systems using an open project approach},
  series = {Varietas delectat: Complexity is the new normality - 47th Annual Conference, Budapest, Hungary16th - 20th September 2019. SEFI 47th Annual Conference Proceedings},
  booktitle = {Varietas delectat: Complexity is the new normality - 47th Annual Conference, Budapest, Hungary16th - 20th September 2019. SEFI 47th Annual Conference Proceedings},
  isbn      = {978-2-87352-018-2},
  pages     = {540 -- 549},
  year      = {2019},
  language  = {en}
}
@inproceedings{WiesenSchleser2019,
  author    = {Wiesen, Andreas and Schleser, Markus},
  title     = {Entwicklung einer Qualit{\"a}tssicherung f{\"u}r das Laserstrahlschweißen im Vakuum mittels Bildverarbeitung},
  series = {Große Schweißtechnische Tagung},
  booktitle = {Große Schweißtechnische Tagung},
  publisher = {DVS-Media},
  address   = {D{\"u}sseldorf},
  isbn      = {978-3-96144-066-5},
  pages     = {1 -- 6},
  year      = {2019},
  language  = {de}
}
@inproceedings{OttenGerhardsSchleseretal.2019,
  author    = {Otten, Christian and Gerhards, Benjamin and Schleser, Markus and Schwarz, A. and Gebhardt, Andreas},
  title     = {Innovative Laserschweißtechnologie f{\"u}r additiv gefertigte Bauteile},
  series = {Große Schweißtechnische Tagung},
  booktitle = {Große Schweißtechnische Tagung},
  publisher = {DVS-Media},
  address   = {D{\"u}sseldorf},
  isbn      = {978-3-96144-066-5},
  pages     = {150 -- 157},
  year      = {2019},
  language  = {de}
}
@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{DinghoferHartung2020,
  author    = {Dinghofer, Kai and Hartung, Frank},
  title     = {Analysis of Criteria for the Selection of Machine Learning Frameworks},
  series = {2020 International Conference on Computing, Networking and Communications (ICNC)},
  booktitle = {2020 International Conference on Computing, Networking and Communications (ICNC)},
  publisher = {IEEE},
  address   = {New York, NY},
  doi       = {10.1109/ICNC47757.2020.9049650},
  pages     = {373 -- 377},
  year      = {2020},
  abstract  = {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.},
  language  = {en}
}