TY - CHAP A1 - Altherr, Lena A1 - Leise, Philipp A1 - Pfetsch, Marc E. A1 - Schmitt, Andreas T1 - Optimal design of resilient technical systems on the example of water supply systems T2 - Mastering Uncertainty in Mechanical Engineering Y1 - 2021 SN - 978-3-030-78356-3 N1 - Unterkapitel des Kapitels "Strategies for Mastering Uncertainty" SP - 429 EP - 433 PB - Springer CY - Cham ER - TY - CHAP A1 - Leise, Philipp A1 - Altherr, Lena T1 - Experimental evaluation of resilience metrics in a fluid system T2 - Mastering Uncertainty in Mechanical Engineering Y1 - 2021 SN - 978-3-030-78356-3 N1 - Unterkapitel des Kapitels "Strategies for Mastering Uncertainty" SP - 442 EP - 447 PB - Springer CY - Cham ER - TY - CHAP A1 - Nikolovski, Gjorgji A1 - Reke, Michael A1 - Elsen, Ingo A1 - Schiffer, Stefan T1 - Machine learning based 3D object detection for navigation in unstructured environments T2 - 2021 IEEE Intelligent Vehicles Symposium Workshops (IV Workshops) N2 - 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. KW - 3D object detection KW - LiDAR KW - autonomous driving KW - Deep learning KW - Three-dimensional displays Y1 - 2021 SN - 978-1-6654-7921-9 U6 - https://doi.org/10.1109/IVWorkshops54471.2021.9669218 N1 - 2021 IEEE Intelligent Vehicles Symposium Workshops (IV Workshops), 11-17 July 2021, Nagoya, Japan. SP - 236 EP - 242 PB - IEEE ER - TY - CHAP A1 - Ritschel, Konstantin A1 - Stenzel, Adina A1 - Czarnecki, Christian A1 - Hong, Chin-Gi ED - Gesellschaft für Informatik e.V. (GI), T1 - Realizing robotic process automation potentials: an architectural perspective on a real-life implementation case T2 - GI Edition Proceedings Band 314 "INFORMATIK 2021" Computer Science & Sustainability N2 - 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. KW - Robotic Process Automation KW - Enterprise Architecture KW - Implementation Case Y1 - 2021 SN - 9783885797081 U6 - https://doi.org/10.18420/informatik2021-108 SN - 1617-5468 N1 - INFORMATIK 2021 – 51. Jahrestagung der Gesellschaft für Informatik, 27. September – 01. Oktober 2021 / Virtuell SP - 1303 EP - 1311 PB - Köllen CY - Bonn ER - TY - CHAP A1 - Mertens, Alexander A1 - Pütz, Sebastian A1 - Brauner, Philipp A1 - Brillowski, Florian Sascha A1 - Buczak, Nadine A1 - Dammers, Hannah A1 - van Dyck, Marc A1 - Kong, Iris A1 - Königs, Peter A1 - Kortomeikel, Frauke Carole A1 - Rodemann, Niklas A1 - Schaar, Anne Kathrin A1 - Steuer-Dankert, Linda A1 - Wlecke, Shari A1 - Gries, Thomas A1 - Leicht-Scholten, Carmen A1 - Nagel, Saskia K. A1 - Piller, Frank Thomas A1 - Schuh, Günther A1 - Ziefle, Martina A1 - Nitsch, Verena T1 - Human digital shadow: Data-based modeling of users and usage in the internet of production T2 - 14th Conference Human System Interaction Conference Proceedings N2 - 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. KW - digital shadow KW - cyber physical production system KW - user & usage KW - internet of production Y1 - 2021 U6 - https://doi.org/10.1109/HSI52170.2021.9538729 N1 - 14th International Conference on Human System Interaction : 8-10 July 2021. Gdańsk, Poland SP - 1 EP - 8 PB - IEEE ER - TY - JOUR A1 - Monakhova, Yulia A1 - Diehl, Bernd W.K. T1 - Novel approach of qNMR workflow by standardization using 2H integral: Application to any intrinsic calibration standard JF - Talanta N2 - 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.). KW - qNMR KW - Deuterium NMR KW - Deuterated solvents KW - Standardization Y1 - 2021 SN - 0039-9140 U6 - https://doi.org/10.1016/j.talanta.2020.121504 VL - 222 IS - Article number: 121504 PB - Elsevier ER - TY - JOUR A1 - Burmistrova, Natalia A. A1 - Soboleva, Polina M. A1 - Monakhova, Yulia T1 - Is infrared spectroscopy combined with multivariate analysis a promising tool for heparin authentication? JF - Journal of Pharmaceutical and Biomedical Analysis N2 - 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. KW - IR spectroscopy KW - Heparin KW - Authenticity KW - Principal component analysis KW - Soft independent modeling of class analogy Y1 - 2021 SN - 0731-7085 U6 - https://doi.org/10.1016/j.jpba.2020.113811 VL - 194 IS - Article number: 113811 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Monakhova, Yulia A1 - Diehl, Bernd W. K. T1 - Simplification of NMR Workflows by Standardization Using 2H Integral of Deuterated Solvent as Applied to Aloe vera Preparations JF - Applied Magnetic Resonance N2 - In this study, a recently proposed NMR standardization approach by 2H integral of deuterated solvent for quantitative multicomponent analysis of complex mixtures is presented. As a proof of principle, the existing NMR routine for the analysis of Aloe vera products was modified. Instead of using absolute integrals of targeted compounds and internal standard (nicotinamide) from 1H-NMR spectra, quantification was performed based on the ratio of a particular 1H-NMR compound integral and 2H-NMR signal of deuterated solvent D2O. Validation characteristics (linearity, repeatability, accuracy) were evaluated and the results showed that the method has the same precision as internal standardization in case of multicomponent screening. Moreover, a dehydration process by freeze drying is not necessary for the new routine. Now, our NMR profiling of A. vera products needs only limited sample preparation and data processing. The new standardization methodology provides an appealing alternative for multicomponent NMR screening. In general, this novel approach, using standardization by 2H integral, benefits from reduced sample preparation steps and uncertainties, and is recommended in different application areas (purity determination, forensics, pharmaceutical analysis, etc.). Y1 - 2021 U6 - https://doi.org/10.1007/s00723-021-01393-4 SN - 1613-7507 VL - 52 IS - 11 SP - 1591 EP - 1600 PB - Springer CY - Cham ER - TY - JOUR A1 - Burger, René A1 - Rumpf, Jessica A1 - Do, Xuan Tung A1 - Monakhova, Yulia A1 - Diehl, Bernd W. K. A1 - Rehahn, Matthias A1 - Schulze, Margit T1 - Is NMR combined with multivariate regression applicable for the molecular weight determination of randomly cross-linked polymers such as lignin? JF - ACS Omega N2 - The molecular weight properties of lignins are one of the key elements that need to be analyzed for a successful industrial application of these promising biopolymers. In this study, the use of 1H NMR as well as diffusion-ordered spectroscopy (DOSY NMR), combined with multivariate regression methods, was investigated for the determination of the molecular weight (Mw and Mn) and the polydispersity of organosolv lignins (n = 53, Miscanthus x giganteus, Paulownia tomentosa, and Silphium perfoliatum). The suitability of the models was demonstrated by cross validation (CV) as well as by an independent validation set of samples from different biomass origins (beech wood and wheat straw). CV errors of ca. 7–9 and 14–16% were achieved for all parameters with the models from the 1H NMR spectra and the DOSY NMR data, respectively. The prediction errors for the validation samples were in a similar range for the partial least squares model from the 1H NMR data and for a multiple linear regression using the DOSY NMR data. The results indicate the usefulness of NMR measurements combined with multivariate regression methods as a potential alternative to more time-consuming methods such as gel permeation chromatography. Y1 - 2021 U6 - https://doi.org/10.1021/acsomega.1c03574 SN - 2470-1343 VL - 6 IS - 44 SP - 29516 EP - 29524 PB - ACS Publications CY - Washington, DC ER - TY - CHAP A1 - Czarnecki, Christian A1 - Hong, Chin-Gi A1 - Schmitz, Manfred A1 - Dietze, Christian ED - Urbach, Nils ED - Röglinger, Maximilian ED - Kautz, Karlheinz ED - Alias, Rose Alinda ED - Saunders, Carol ED - Wiener, Martin T1 - Enabling digital transformation through cognitive robotic process automation at Deutsche Telekom Services Europe T2 - Digitalization Cases Vol. 2 : Mastering digital transformation for global business N2 - Subject of this case is Deutsche Telekom Services Europe (DTSE), a service center for administrative processes. Due to the high volume of repetitive tasks (e.g., 100k manual uploads of offer documents into SAP per year), automation was identified as an important strategic target with a high management attention and commitment. DTSE has to work with various backend application systems without any possibility to change those systems. Furthermore, the complexity of administrative processes differed. When it comes to the transfer of unstructured data (e.g., offer documents) to structured data (e.g., MS Excel files), further cognitive technologies were needed. Y1 - 2021 SN - 978-3-030-80002-4 (Print) SN - 978-3-030-80003-1 (Online) U6 - https://doi.org/10.1007/978-3-030-80003-1 SP - 123 EP - 138 PB - Springer CY - Cham ER -