TY - CHAP A1 - Chavez Bermudez, Victor Francisco A1 - Cruz Castanon, Victor Fernando A1 - Ruchay, Marco A1 - Wollert, Jörg ED - Leipzig, Hochschule für Technik, Wirtschaft und Kultur T1 - Rapid prototyping framework for automation applications based on IO-Link T2 - Tagungsband AALE 2022: Wissenstransfer im Spannungsfeld von Autonomisierung und Fachkräftemangel N2 - The development of protype applications with sensors and actuators in the automation industry requires tools that are independent of manufacturer, and are flexible enough to be modified or extended for any specific requirements. Currently, developing prototypes with industrial sensors and actuators is not straightforward. First of all, the exchange of information depends on the industrial protocol that these devices have. Second, a specific configuration and installation is done based on the hardware that is used, such as automation controllers or industrial gateways. This means that the development for a specific industrial protocol, highly depends on the hardware and the software that vendors provide. In this work we propose a rapid-prototyping framework based on Arduino to solve this problem. For this project we have focused to work with the IO-Link protocol. The framework consists of an Arduino shield that acts as the physical layer, and a software that implements the IO-Link Master protocol. The main advantage of such framework is that an application with industrial devices can be rapid-prototyped with ease as its vendor independent, open-source and can be ported easily to other Arduino compatible boards. In comparison, a typical approach requires proprietary hardware, is not easy to port to another system and is closed-source. KW - Rapid-prototyping KW - Arduino KW - IO-Link KW - Industrial Communication Y1 - 2022 SN - 978-3-910103-00-9 U6 - https://doi.org/10.33968/2022.28 N1 - 18. AALE-Konferenz. Pforzheim, 09.03.-11.03.2022 CY - Leipzig ER - TY - CHAP A1 - Ulmer, Jessica A1 - Mostafa, Youssef A1 - Wollert, Jörg T1 - Digital Twin Academy: From Zero to Hero through individual learning experiences T2 - Tagungsband AALE 2022: Wissenstransfer im Spannungsfeld von Autonomisierung und Fachkräftemangel N2 - Digital twins are seen as one of the key technologies of Industry 4.0. Although many research groups focus on digital twins and create meaningful outputs, the technology has not yet reached a broad application in the industry. The main reasons for this imbalance are the complexity of the topic, the lack of specialists, and the unawareness of the twin opportunities. The project "Digital Twin Academy" aims to overcome these barriers by focusing on three actions: Building a digital twin community for discussion and exchange, offering multi-stage training for various knowledge levels, and implementing realworld use cases for deeper insights and guidance. In this work, we focus on creating a flexible learning platform that allows the user to select a training path adjusted to personal knowledge and needs. Therefore, a mix of basic and advanced modules is created and expanded by individual feedback options. The usage of personas supports the selection of the appropriate modules. KW - Digital Twins KW - Knowledge Transfer KW - Training Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bsz:l189-qucosa2-776097 SN - 978-3-910103-00-9 N1 - 18. AALE-Konferenz. Pforzheim, 09.03.-11.03.2022 SP - 1 EP - 9 ER - TY - CHAP A1 - Ulmer, Jessica A1 - Braun, Sebastian A1 - Wollert, Jörg T1 - Adaptive VR-Produktionsumgebungen für Evaluations- und Schulungstätigkeiten T1 - Adaptive VR production environments for evaluation and training purposes T2 - Automation 2021: Navigating towards resilient Production N2 - Industrie 4.0 stellt viele Herausforderungen an produzierende Unternehmen und ihre Beschäf-tigten. Innovative und effektive Trainingsstrategien sind erforderlich, um mit den sich schnell verändernden Produktionsumgebungen und neuen Fertigungstechnologien Schritt halten zu können. Virtual Reality (VR) bietet neue Möglichkeiten für On-the-Job, On-Demand- und Off-Premise-Schulungen. Diese Arbeit stellt ein neues VR Schulungssystem vor, welches sich flexible an unterschiedliche Trainingsobjekte auf Grundlage von Rezepten und CAD Modellen anpassen lässt. Das Konzept basiert auf gerichteten azyklischen Graphen und einem Level-system. Es ermöglicht eine benutzerindividuelle Lerngeschwindigkeit mittels visueller Ele-mente. Das Konzept wurde für einen mechanischen Anwendungsfall mit Industriekomponen-ten implementiert und in der Industrie 4.0-Modellfabrik der FH Aachen umgesetzt. N2 - Industry 4.0 poses many challenges for manufacturing companies and their employees. Inno-vative and effective training strategies are needed to keep pace with rapidly changing produc-tion environments and new manufacturing technologies. Virtual reality (VR) offers new oppor-tunities for on-the-job, on-demand, and off-premise training. This work presents a new VR training system that can be flexibly adapted to different training objects based on recipes and CAD models. The concept is based on directed acyclic graphs and a level system. It allows a user-individual learning speed by means of visual elements. The concept was implemented for a mechanical use case with industrial components and implemented in the industry 4.0 model factory of the FH Aachen University of Applied Sciences. Y1 - 2021 SN - 978-3-18-092392-5 U6 - https://doi.org/10.51202/9783181023921-55 SN - 0083-5560 N1 - 22. Leitkongress der Mess- und Automatisierungstechnik AUTOMATION 2021 - Navigating towards resilient Production, 29. und 30. Juni 2021 SP - 55 EP - 64 PB - VDI CY - Düsseldorf ER - TY - JOUR A1 - Kempt, Hendrik A1 - Freyer, Nils A1 - Nagel, Saskia K. T1 - Justice and the normative standards of explainability in healthcare JF - Philosophy & Technology N2 - Providing healthcare services frequently involves cognitively demanding tasks, including diagnoses and analyses as well as complex decisions about treatments and therapy. From a global perspective, ethically significant inequalities exist between regions where the expert knowledge required for these tasks is scarce or abundant. One possible strategy to diminish such inequalities and increase healthcare opportunities in expert-scarce settings is to provide healthcare solutions involving digital technologies that do not necessarily require the presence of a human expert, e.g., in the form of artificial intelligent decision-support systems (AI-DSS). Such algorithmic decision-making, however, is mostly developed in resource- and expert-abundant settings to support healthcare experts in their work. As a practical consequence, the normative standards and requirements for such algorithmic decision-making in healthcare require the technology to be at least as explainable as the decisions made by the experts themselves. The goal of providing healthcare in settings where resources and expertise are scarce might come with a normative pull to lower the normative standards of using digital technologies in order to provide at least some healthcare in the first place. We scrutinize this tendency to lower standards in particular settings from a normative perspective, distinguish between different types of absolute and relative, local and global standards of explainability, and conclude by defending an ambitious and practicable standard of local relative explainability. KW - Clinical decision support systems KW - Justice KW - Medical AI KW - Explainability KW - Normative standards Y1 - 2022 U6 - https://doi.org/10.1007/s13347-022-00598-0 VL - 35 IS - Article number: 100 SP - 1 EP - 19 PB - Springer Nature CY - Berlin ER - TY - CHAP A1 - Freyer, Nils A1 - Thewes, Dustin A1 - Meinecke, Matthias ED - Gusikhin, Oleg ED - Hammoudi, Slimane ED - Cuzzocrea, Alfredo T1 - GUIDO: a hybrid approach to guideline discovery & ordering from natural language texts T2 - Proceedings of the 12th International Conference on Data Science, Technology and Applications DATA - Volume 1 N2 - Extracting workflow nets from textual descriptions can be used to simplify guidelines or formalize textual descriptions of formal processes like business processes and algorithms. The task of manually extracting processes, however, requires domain expertise and effort. While automatic process model extraction is desirable, annotating texts with formalized process models is expensive. Therefore, there are only a few machine-learning-based extraction approaches. Rule-based approaches, in turn, require domain specificity to work well and can rarely distinguish relevant and irrelevant information in textual descriptions. In this paper, we present GUIDO, a hybrid approach to the process model extraction task that first, classifies sentences regarding their relevance to the process model, using a BERT-based sentence classifier, and second, extracts a process model from the sentences classified as relevant, using dependency parsing. The presented approach achieves significantly better resul ts than a pure rule-based approach. GUIDO achieves an average behavioral similarity score of 0.93. Still, in comparison to purely machine-learning-based approaches, the annotation costs stay low. KW - Natural Language Processing KW - Text Mining KW - Process Model Extraction KW - Business Process Intelligence Y1 - 2023 SN - 978-989-758-664-4 U6 - https://doi.org/10.5220/0012084400003541 SN - 2184-285X N1 - 12th International Conference on Data Science, Technology and Applications, July 11-13, 2023, in Rome, Italy. SP - 335 EP - 342 ER - TY - CHAP A1 - Klöser, Lars A1 - Büsgen, André A1 - Kohl, Philipp A1 - Kraft, Bodo A1 - Zündorf, Albert ED - Conte, Donatello ED - Fred, Ana ED - Gusikhin, Oleg ED - Sansone, Carlo T1 - Explaining relation classification models with semantic extents T2 - Deep Learning Theory and Applications N2 - In recent years, the development of large pretrained language models, such as BERT and GPT, significantly improved information extraction systems on various tasks, including relation classification. State-of-the-art systems are highly accurate on scientific benchmarks. A lack of explainability is currently a complicating factor in many real-world applications. Comprehensible systems are necessary to prevent biased, counterintuitive, or harmful decisions. We introduce semantic extents, a concept to analyze decision patterns for the relation classification task. Semantic extents are the most influential parts of texts concerning classification decisions. Our definition allows similar procedures to determine semantic extents for humans and models. We provide an annotation tool and a software framework to determine semantic extents for humans and models conveniently and reproducibly. Comparing both reveals that models tend to learn shortcut patterns from data. These patterns are hard to detect with current interpretability methods, such as input reductions. Our approach can help detect and eliminate spurious decision patterns during model development. Semantic extents can increase the reliability and security of natural language processing systems. Semantic extents are an essential step in enabling applications in critical areas like healthcare or finance. Moreover, our work opens new research directions for developing methods to explain deep learning models. KW - Relation classification KW - Natural language processing KW - Natural language understanding KW - Information extraction KW - Trustworthy artificial intelligence Y1 - 2023 SN - 978-3-031-39058-6 (Print) SN - 978-3-031-39059-3 (Online) U6 - https://doi.org/10.1007/978-3-031-39059-3_13 N1 - 4th International Conference, DeLTA 2023, Rome, Italy, July 13–14, 2023. SP - 189 EP - 208 PB - Springer CY - Cham ER - TY - INPR A1 - Greiner, Lasse A1 - Jeromin, Günter Erich A1 - Sithole, Patience A1 - Petersen, Soenke T1 - Preprint: Studies on the enzymatic reduction of levulinic acid using Chiralidon-R and Chiralidon-S T2 - ChemRxiv N2 - The enzymatic reduction of levulinic acid by the chiral catalysts Chiralidon-R and Chiralidon-S which are commercially available superabsorbed alcohol dehydrogenases is described. The Chiralidon®-R/S reduces the levulinic acid to the (R,S)-4-hydroxy valeric acid and the (R)- or (S)- gamma-valerolactone. KW - Levulinic acid KW - Chiralidon-R KW - Chiralidon-S KW - 4-hydroxy valeric acid KW - (R)- or (S)- gamma-valerolactone Y1 - 2023 U6 - https://doi.org/10.26434/chemrxiv-2023-jlvcv ER - TY - JOUR A1 - Cheng, Chi-Tsun A1 - Wollert, Jörg A1 - Chen, Xi A1 - Fapojuwo, Abraham O. T1 - Guest Editorial : Circuits and Systems for Industry X.0 Applications JF - IEEE Journal on Emerging and Selected Topics in Circuits and Systems Y1 - 2023 U6 - https://doi.org/10.1109/JETCAS.2023.3278843 SN - 2156-3357 (Print) SN - 2156-3365 (Online) VL - 13 SP - 457 EP - 460 PB - IEEE CY - New York ET - 2 ER - TY - RPRT A1 - Göll, Fabian A1 - Braunstein, Björn A1 - Albracht, Kirsten T1 - Lernende roboterassistierte Systeme für das neuromuskuläre Training - RoSylerNT; Teilvorhaben: Entwicklung eines neuromuskuloskelettalen Modells als Basis für die Interaktionsfähigkeiten autonomer Assistenzsysteme KW - Robotik KW - Rehabilitationsmedizin KW - Neuromuskuläres System KW - Rehabilitatives Training KW - Trainingsgerät Y1 - 2021 U6 - https://doi.org/10.2314/KXP:1855318741 N1 - Förderkennzeichen BMBF 16SV7853 Schlussbericht der Deutschen Sporthochschule Köln für das Vorhaben RoSylerNT Laufzeit: 01.08.2017-31.07.2021 PB - Deutsche Sporthochschule Köln CY - Köln ER - TY - GEN T1 - Ordnung zur Änderung der Ordnung zur Regelung der Einstellung des Bachelorstudiengangs Bauingenieurwesen – Netzingenieur (7-semestrig) und des dualen Bachelorstudiengangs Bauingenieurwesen – Netzingenieur (9-semestrig) im Fachbereich Bauingeieurwesen an der Fachhochschule Aachen T3 - FH-Mitteilungen - 79/2019 KW - Amtliche Mitteilung KW - Änderungsordnung KW - Einstellungsordnung KW - Bachelor KW - Bauingenieurwesen Y1 - 2019 ER -