@incollection{EngemannDuKallweitetal.2020,
  author    = {Engemann, Heiko and Du, Shengzhi and Kallweit, Stephan and Ning, Chuanfang and Anwar, Saqib},
  title     = {AutoSynPose: Automatic Generation of Synthetic Datasets for 6D Object Pose Estimation},
  series = {Machine Learning and Artificial Intelligence. Proceedings of MLIS 2020},
  booktitle = {Machine Learning and Artificial Intelligence. Proceedings of MLIS 2020},
  publisher = {IOS Press},
  address   = {Amsterdam},
  isbn      = {978-1-64368-137-5},
  doi       = {10.3233/FAIA200770},
  pages     = {89 -- 97},
  year      = {2020},
  abstract  = {We present an automated pipeline for the generation of synthetic datasets for six-dimension (6D) object pose estimation. Therefore, a completely automated generation process based on predefined settings is developed, which enables the user to create large datasets with a minimum of interaction and which is feasible for applications with a high object variance. The pipeline is based on the Unreal 4 (UE4) game engine and provides a high variation for domain randomization, such as object appearance, ambient lighting, camera-object transformation and distractor density. In addition to the object pose and bounding box, the metadata includes all randomization parameters, which enables further studies on randomization parameter tuning. The developed workflow is adaptable to other 3D objects and UE4 environments. An exemplary dataset is provided including five objects of the Yale-CMU-Berkeley (YCB) object set. The datasets consist of 6 million subsegments using 97 rendering locations in 12 different UE4 environments. Each dataset subsegment includes one RGB image, one depth image and one class segmentation image at pixel-level.},
  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{DuemmlerOetringerGoettsche2020,
  author    = {D{\"u}mmler, Andreas and Oetringer, Kerstin and G{\"o}ttsche, Joachim},
  title     = {Auslegungstool zur energieeffizienten K{\"u}hlung von Geb{\"a}uden},
  series = {DKV-Tagung 2020, AA IV},
  booktitle = {DKV-Tagung 2020, AA IV},
  pages     = {1109},
  year      = {2020},
  abstract  = {Thematisch widmet sich das Projekt Coolplan- AIR der Fortentwicklung und Feldvalidierung eines Berechnungs- und Auslegungstools zur energieeffizienten K{\"u}hlung von Geb{\"a}uden mit luftgest{\"u}tzten Systemen. Neben dem Aufbau und der Weiterentwicklung von Simulationsmodellen erfolgen Vermessungen der Gesamtsysteme anhand von Praxisanlagen im Feld. Der Schwerpunkt des Projekts liegt auf der Vermessung, Simulation und Integration rein luftgest{\"u}tzter K{\"u}hltechnologien. Im Bereich der K{\"a}lteerzeugung wurden Luft- Luft- W{\"a}rmepumpen, Anlagen zur adiabaten K{\"u}hlung bzw. offene K{\"u}hlt{\"u}rme und VRF- Multisplit- Systeme (Variable Refrigerant Flow) im Feld bzw. auf dem Teststand der HSD vermessen. Die Komponentenmodelle werden in die Matlab/Simulink- Toolbox CARNOT integriert und anschließend auf Basis der zuvor erhaltenen Messdaten validiert. Einerseits erlauben die Messungen das Betriebsverhalten von Anlagenkomponenten zu analysieren. Andererseits soll mit der Vermessung im Feld gepr{\"u}ft werden, inwieweit die Simulationsmodelle, welche im Vorg{\"a}ngerprojekt aus Pr{\"u}fstandmessungen entwickelt wurden, auch f{\"u}r gr{\"o}ßere Ger{\"a}teleistungen G{\"u}ltigkeit besitzen. Die entwickelten und implementierten Systeme, bestehend aus verschiedensten Anlagenmodellen und Regelungskomponenten, werden gepr{\"u}ft und dahingehend qualifiziert, dass sie in Standard- Auslegungstools zuverl{\"a}ssig verwendet werden k{\"o}nnen. Zus{\"a}tzlich wird ein energetisches Monitoring eines H{\"o}rsaalgeb{\"a}udes am Campus J{\"u}lich durchgef{\"u}hrt, das u. a. zur Validierung der K{\"u}hllastberechnungen in g{\"a}ngigen Simulationsmodelle genutzt werden kann.},
  language  = {de}
}
@article{MarinkovicButenweg2020,
  author    = {Marinkovic, Marko and Butenweg, Christoph},
  title     = {Ausfachungen aus Ziegelmauerwerk in Stahlbetonrahmentragwerken unter Erdbebenbeanspruchung},
  series = {Mauerwerk},
  volume    = {24},
  journal   = {Mauerwerk},
  number    = {4},
  publisher = {Wiley},
  address   = {Weinheim},
  issn      = {1437-1022},
  doi       = {10.1002/dama.202000011},
  pages     = {194 -- 205},
  year      = {2020},
  abstract  = {Stahlbetonrahmentragwerke mit Ausfachungen aus Mauerwerk weisen nach Erdbeben h{\"a}ufig schwere Sch{\"a}den auf. Gr{\"u}nde hierf{\"u}r sind die Beanspruchungen der Ausfachungsw{\"a}nde durch die aufgezwungenen Rahmenverformungen in Wandebene und die gleichzeitig auftretenden Tr{\"a}gheitskr{\"a}fte senkrecht zur Wandebene in Kombination mit der konstruktiven Ausf{\"u}hrung des Ausfachungsmauerwerks. Die Ausfachung wird in der Regel knirsch gegen die Rahmenst{\"u}tzen gemauert, wobei der Verschluss der oberen Fuge mit M{\"o}rtel oder Montageschaum erfolgt. Dadurch kommt es im Erdbebenfall zu lokalen Interaktionen zwischen Ausfachung und Rahmen, die in der Folge zu einem Versagen einzelner Ausfachungsw{\"a}nde oder zu einem sukzessiven Versagen des Gesamtgeb{\"a}udes f{\"u}hren k{\"o}nnen. Die beobachteten Sch{\"a}den waren die Motivation daf{\"u}r, in dem europ{\"a}ischen Forschungsprojekt INSYSME f{\"u}r Stahlbetonrahmentragwerke mit Ausfachungen aus hochw{\"a}rmed{\"a}mmenden Ziegelmauerwerk innovative L{\"o}sungen zur Verbesserung des seismischen Verhaltens zu entwickeln. Der vorliegende Beitrag stellt die im Rahmen des Projekts von den deutschen Projektpartnern (Universit{\"a}t Kassel, SDA-engineering GmbH) entwickelten L{\"o}sungen vor und vergleicht deren seismisches Verhalten mit der traditionellen Ausf{\"u}hrung der Ausfachungsw{\"a}nde. Grundlage f{\"u}r den Vergleich sind statisch-zyklische Wandversuche und Simulationen auf Wandebene. Aus den Ergebnissen werden Empfehlungen f{\"u}r die erdbebensichere Auslegung von Stahlbetonrahmentragwerken mit Ausfachungen aus Ziegelmauerwerk abgeleitet.},
  language  = {de}
}
@inproceedings{LorenzAltherrPelz2020,
  author    = {Lorenz, Imke-Sophie and Altherr, Lena and Pelz, Peter F.},
  title     = {Assessing and Optimizing the Resilience of Water Distribution Systems Using Graph-Theoretical Metrics},
  series = {Operations Research Proceedings 2019},
  booktitle = {Operations Research Proceedings 2019},
  editor    = {Neufeld, Janis S. and Buscher, Udo and Lasch, Rainer and M{\"o}st, Dominik and Sch{\"o}nberger, J{\"o}rn},
  publisher = {Springer},
  address   = {Cham},
  isbn      = {978-3-030-48439-2},
  doi       = {10.1007/978-3-030-48439-2_63},
  pages     = {521 -- 527},
  year      = {2020},
  abstract  = {Water distribution systems are an essential supply infrastructure for cities. Given that climatic and demographic influences will pose further challenges for these infrastructures in the future, the resilience of water supply systems, i.e. their ability to withstand and recover from disruptions, has recently become a subject of research. To assess the resilience of a WDS, different graph-theoretical approaches exist. Next to general metrics characterizing the network topology, also hydraulic and technical restrictions have to be taken into account. In this work, the resilience of an exemplary water distribution network of a major German city is assessed, and a Mixed-Integer Program is presented which allows to assess the impact of capacity adaptations on its resilience.},
  language  = {en}
}
@inproceedings{ChavezBermudezWollert2020,
  author    = {Chavez Bermudez, Victor Francisco and Wollert, J{\"o}rg},
  title     = {Arduino based Framework for Rapid Application Development of a Generic IO-Link interface},
  series = {Kommunikation und Bildverarbeitung in der Automation. Ausgew{\"a}hlte Beitr{\"a}ge der Jahreskolloquien KommA und BVAu 2018},
  booktitle = {Kommunikation und Bildverarbeitung in der Automation. Ausgew{\"a}hlte Beitr{\"a}ge der Jahreskolloquien KommA und BVAu 2018},
  publisher = {Springer Vieweg},
  address   = {Berlin},
  isbn      = {978-3-662-59895-5},
  doi       = {10.1007/978-3-662-59895-5_2},
  pages     = {21 -- 33},
  year      = {2020},
  abstract  = {The implementation of IO-Link in the automation industry has increased over the years. Its main advantage is it offers a digital point-to-point plugand-play interface for any type of device or application. This simplifies the communication between devices and increases productivity with its different features like self-parametrization and maintenance. However, its complete potential is not always used. The aim of this paper is to create an Arduino based framework for the development of generic IO-Link devices and increase its implementation for rapid prototyping. By generating the IO device description file (IODD) from a graphical user interface, and further customizable options for the device application, the end-user can intuitively develop generic IO-Link devices. The peculiarity of this framework relies on its simplicity and abstraction which allows to implement any sensor functionality and virtually connect any type of device to an IO-Link master. This work consists of the general overview of the framework, the technical background of its development and a proof of concept which demonstrates the workflow for its implementation.},
  language  = {en}
}
@article{UlmerGroeningerBraunetal.2020,
  author    = {Ulmer, Jessica and Gr{\"o}ninger, Marc and Braun, Sebastian and Wollert, J{\"o}rg},
  title     = {AR Arbeitspl{\"a}tze: F{\"u}r hochflexible und skalierbare Produktionsumgebungen},
  series = {atp Magazin},
  volume    = {62},
  journal   = {atp Magazin},
  number    = {10},
  publisher = {Vulkan-Verlag},
  address   = {Essen},
  issn      = {2364-3137},
  doi       = {10.17560/atp.v62i10.2495},
  year      = {2020},
  abstract  = {Trotz fortschreitender Automatisierung bleiben manuelle T{\"a}tigkeiten ein wichtiger Baustein der Fertigung kundenindividueller Produkte. Um die Mitarbeiter(innen) zu unterst{\"u}tzen und um eine effiziente Arbeit zu erm{\"o}glichen, werden zunehmend auf Augmented Reality (AR) basierende Systeme eingesetzt. Die vorgestellte Arbeit konzentriert sich auf die Entwicklung ganzheitlicher AR-Arbeitspl{\"a}tze f{\"u}r den Einsatz in kleinen und mittleren Unternehmen (KMU). Das entwickelte AR- Handarbeitskonzept beinhaltet eine Just-in-time-Darstellung der Arbeitsaufgaben auf Werkst{\"u}cken mit automatisierter Fertigungskontrolle. Als Reaktion auf kurze Produktlebenszyklen und hohe Produktvielfalten sind alle Komponenten auf maximale Flexibilit{\"a}t ausgelegt. Ein Umr{\"u}sten auf neue Produkte kann innerhalb von Minuten erfolgen.},
  language  = {de}
}
@misc{Golland2020,
  author    = {Golland, Alexander},
  title     = {Anspruch gegen einen Suchmaschinenbetreiber auf L{\"o}schung von Suchergebnissen},
  series = {ZD Zeitschrift f{\"u}r Datenschutz},
  volume    = {2020},
  journal   = {ZD Zeitschrift f{\"u}r Datenschutz},
  number    = {10},
  publisher = {Beck},
  address   = {M{\"u}nchen},
  issn      = {2192-5593},
  pages     = {531 -- 532},
  year      = {2020},
  language  = {de}
}
@inproceedings{NeesStengelMeisteretal.2020,
  author    = {Nees, Franz and Stengel, Ingo and Meister, Vera G. and Barton, Thomas and Herrmann, Frank and M{\"u}ller, Christian and Wolf, Martin},
  title     = {Angewandte Forschung in der Wirtschaftsinformatik 2020 : Tagungsband zur 33. AKWI-Jahrestagung am 14.09.2020, ausgerichtet von der Hochschule Karlsruhe - Wirtschaft und Technik / hrsg. von Franz Nees, Ingo Stengel, Vera G. Meister, Thomas Barton, Frank Herrmann, Christian M{\"u}ller, Martin R. Wolf},
  publisher = {mana-Buch},
  address   = {Heide},
  isbn      = {978-3-944330-66-2},
  doi       = {10.15771/978-3-944330-66-2},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:526-opus4-13840},
  pages     = {147 Seiten},
  year      = {2020},
  abstract  = {Tagungsbeitr{\"a}ge aus den Bereichen KI, Prozessorganisation und Plattformen f{\"u}r Gesch{\"a}ftsprozesse, Sicherheit und Datenschutz sowie Prototypen und Modelle.},
  language  = {de}
}
@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}
}