@book{Pieper2021, author = {Pieper, Martin}, title = {Quantum mechanics: Introduction to mathematical formulation}, publisher = {Springer}, address = {Wiesbaden}, isbn = {978-3-658-32644-9}, doi = {10.1007/978-3-658-32645-6}, pages = {XIII, 33}, year = {2021}, abstract = {Anyone who has always wanted to understand the hieroglyphs on Sheldon's blackboard in the TV series The Big Bang Theory or who wanted to know exactly what the fate of Schr{\"o}dinger's cat is all about will find a short, descriptive introduction to the world of quantum mechanics in this essential. The text particularly focuses on the mathematical description in the Hilbert space. The content goes beyond popular scientific presentations, but is nevertheless suitable for readers without special prior knowledge thanks to the clear examples.}, language = {en} } @inproceedings{EnglhardWeberArent2021, author = {Englhard, Markus and Weber, Tobias and Arent, Jan-Christoph}, title = {Efficiency enhancement for CFRP-Prepregautoclave manufacturing by means of simulation-assisted loading optimization}, series = {Proceedings of SAMPE Europe Conference 2021}, booktitle = {Proceedings of SAMPE Europe Conference 2021}, pages = {8 Seiten}, year = {2021}, abstract = {A new method for improved autoclave loading within the restrictive framework of helicopter manufacturing is proposed. It is derived from experimental and numerical studies of the curing process and aims at optimizing tooling positions in the autoclave for fast and homogeneous heat-up. The mold positioning is based on two sets of information. The thermal properties of the molds, which can be determined via semi-empirical thermal simulation. The second information is a previously determined distribution of heat transfer coefficients inside the autoclave. Finally, an experimental proof of concept is performed to show a cycle time reduction of up to 31\% using the proposed methodology.}, language = {en} } @incollection{AltherrLeise2021, author = {Altherr, Lena and Leise, Philipp}, title = {Resilience as a concept for mastering uncertainty}, series = {Mastering Uncertainty in Mechanical Engineering}, booktitle = {Mastering Uncertainty in Mechanical Engineering}, publisher = {Springer}, address = {Cham}, isbn = {978-3-030-78353-2}, doi = {10.1007/978-3-030-78354-9}, pages = {412 -- 417}, year = {2021}, language = {en} } @incollection{AltherrLeisePfetschetal.2021, author = {Altherr, Lena and Leise, Philipp and Pfetsch, Marc E. and Schmitt, Andreas}, title = {Optimal design of resilient technical systems on the example of water supply systems}, series = {Mastering Uncertainty in Mechanical Engineering}, booktitle = {Mastering Uncertainty in Mechanical Engineering}, publisher = {Springer}, address = {Cham}, isbn = {978-3-030-78356-3}, pages = {429 -- 433}, year = {2021}, language = {en} } @incollection{LeiseAltherr2021, author = {Leise, Philipp and Altherr, Lena}, title = {Experimental evaluation of resilience metrics in a fluid system}, series = {Mastering Uncertainty in Mechanical Engineering}, booktitle = {Mastering Uncertainty in Mechanical Engineering}, publisher = {Springer}, address = {Cham}, isbn = {978-3-030-78356-3}, pages = {442 -- 447}, year = {2021}, language = {en} } @inproceedings{NikolovskiRekeElsenetal.2021, author = {Nikolovski, Gjorgji and Reke, Michael and Elsen, Ingo and Schiffer, Stefan}, title = {Machine learning based 3D object detection for navigation in unstructured environments}, series = {2021 IEEE Intelligent Vehicles Symposium Workshops (IV Workshops)}, booktitle = {2021 IEEE Intelligent Vehicles Symposium Workshops (IV Workshops)}, publisher = {IEEE}, isbn = {978-1-6654-7921-9}, doi = {10.1109/IVWorkshops54471.2021.9669218}, pages = {236 -- 242}, year = {2021}, abstract = {In this paper we investigate the use of deep neural networks for 3D object detection in uncommon, unstructured environments such as in an open-pit mine. While neural nets are frequently used for object detection in regular autonomous driving applications, more unusual driving scenarios aside street traffic pose additional challenges. For one, the collection of appropriate data sets to train the networks is an issue. For another, testing the performance of trained networks often requires tailored integration with the particular domain as well. While there exist different solutions for these problems in regular autonomous driving, there are only very few approaches that work for special domains just as well. We address both the challenges above in this work. First, we discuss two possible ways of acquiring data for training and evaluation. That is, we evaluate a semi-automated annotation of recorded LIDAR data and we examine synthetic data generation. Using these datasets we train and test different deep neural network for the task of object detection. Second, we propose a possible integration of a ROS2 detector module for an autonomous driving platform. Finally, we present the performance of three state-of-the-art deep neural networks in the domain of 3D object detection on a synthetic dataset and a smaller one containing a characteristic object from an open-pit mine.}, language = {en} } @inproceedings{RitschelStenzelCzarneckietal.2021, author = {Ritschel, Konstantin and Stenzel, Adina and Czarnecki, Christian and Hong, Chin-Gi}, title = {Realizing robotic process automation potentials: an architectural perspective on a real-life implementation case}, series = {GI Edition Proceedings Band 314 "INFORMATIK 2021" Computer Science \& Sustainability}, booktitle = {GI Edition Proceedings Band 314 "INFORMATIK 2021" Computer Science \& Sustainability}, editor = {Gesellschaft f{\"u}r Informatik e.V. (GI),}, publisher = {K{\"o}llen}, address = {Bonn}, isbn = {9783885797081}, issn = {1617-5468}, doi = {10.18420/informatik2021-108}, pages = {1303 -- 1311}, year = {2021}, abstract = {The initial idea of Robotic Process Automation (RPA) is the automation of business processes through a simple emulation of user input and output by software robots. Hence, it can be assumed that no changes of the used software systems and existing Enterprise Architecture (EA) is required. In this short, practical paper we discuss this assumption based on a real-life implementation project. We show that a successful RPA implementation might require architectural work during analysis, implementation, and migration. As practical paper we focus on exemplary lessons-learned and new questions related to RPA and EA.}, language = {en} } @inproceedings{MertensPuetzBrauneretal.2021, author = {Mertens, Alexander and P{\"u}tz, Sebastian and Brauner, Philipp and Brillowski, Florian Sascha and Buczak, Nadine and Dammers, Hannah and van Dyck, Marc and Kong, Iris and K{\"o}nigs, Peter and Kortomeikel, Frauke Carole and Rodemann, Niklas and Schaar, Anne Kathrin and Steuer-Dankert, Linda and Wlecke, Shari and Gries, Thomas and Leicht-Scholten, Carmen and Nagel, Saskia K. and Piller, Frank Thomas and Schuh, G{\"u}nther and Ziefle, Martina and Nitsch, Verena}, title = {Human digital shadow: Data-based modeling of users and usage in the internet of production}, series = {14th Conference Human System Interaction Conference Proceedings}, booktitle = {14th Conference Human System Interaction Conference Proceedings}, publisher = {IEEE}, doi = {10.1109/HSI52170.2021.9538729}, pages = {1 -- 8}, year = {2021}, abstract = {Digital Shadows as the aggregation, linkage and abstraction of data relating to physical objects are a central vision for the future of production. However, the majority of current research takes a technocentric approach, in which the human actors in production play a minor role. Here, the authors present an alternative anthropocentric perspective that highlights the potential and main challenges of extending the concept of Digital Shadows to humans. Following future research methodology, three prospections that illustrate use cases for Human Digital Shadows across organizational and hierarchical levels are developed: human-robot collaboration for manual work, decision support and work organization, as well as human resource management. Potentials and challenges are identified using separate SWOT analyses for the three prospections and common themes are emphasized in a concluding discussion.}, language = {en} } @article{MonakhovaDiehl2021, author = {Monakhova, Yulia and Diehl, Bernd W.K.}, title = {Novel approach of qNMR workflow by standardization using 2H integral: Application to any intrinsic calibration standard}, series = {Talanta}, volume = {222}, journal = {Talanta}, number = {Article number: 121504}, publisher = {Elsevier}, isbn = {0039-9140}, doi = {10.1016/j.talanta.2020.121504}, year = {2021}, abstract = {Quantitative nuclear magnetic resonance (qNMR) is routinely performed by the internal or external standardization. The manuscript describes a simple alternative to these common workflows by using NMR signal of another active nuclei of calibration compound. For example, for any arbitrary compound quantification by NMR can be based on the use of an indirect concentration referencing that relies on a solvent having both 1H and 2H signals. To perform high-quality quantification, the deuteration level of the utilized deuterated solvent has to be estimated. In this contribution the new method was applied to the determination of deuteration levels in different deuterated solvents (MeOD, ACN, CDCl3, acetone, benzene, DMSO-d6). Isopropanol-d6, which contains a defined number of deuterons and protons, was used for standardization. Validation characteristics (precision, accuracy, robustness) were calculated and the results showed that the method can be used in routine practice. Uncertainty budget was also evaluated. In general, this novel approach, using standardization by 2H integral, benefits from reduced sample preparation steps and uncertainties, and can be applied in different application areas (purity determination, forensics, pharmaceutical analysis, etc.).}, language = {en} } @article{BurmistrovaSobolevaMonakhova2021, author = {Burmistrova, Natalia A. and Soboleva, Polina M. and Monakhova, Yulia}, title = {Is infrared spectroscopy combined with multivariate analysis a promising tool for heparin authentication?}, series = {Journal of Pharmaceutical and Biomedical Analysis}, volume = {194}, journal = {Journal of Pharmaceutical and Biomedical Analysis}, number = {Article number: 113811}, publisher = {Elsevier}, address = {Amsterdam}, isbn = {0731-7085}, doi = {10.1016/j.jpba.2020.113811}, year = {2021}, abstract = {The investigation of the possibility to determine various characteristics of powder heparin (n = 115) was carried out with infrared spectroscopy. The evaluation of heparin samples included several parameters such as purity grade, distributing company, animal source as well as heparin species (i.e. Na-heparin, Ca-heparin, and heparinoids). Multivariate analysis using principal component analysis (PCA), soft independent modelling of class analogy (SIMCA), and partial least squares - discriminant analysis (PLS-DA) were applied for the modelling of spectral data. Different pre-processing methods were applied to IR spectral data; multiplicative scatter correction (MSC) was chosen as the most relevant. Obtained results were confirmed by nuclear magnetic resonance (NMR) spectroscopy. Good predictive ability of this approach demonstrates the potential of IR spectroscopy and chemometrics for screening of heparin quality. This approach, however, is designed as a screening tool and is not considered as a replacement for either of the methods required by USP and FDA.}, language = {en} }