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 - 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 - JOUR A1 - Özsoylu, Dua A1 - Aliazizi, Fereshteh A1 - Wagner, Patrick A1 - Schöning, Michael Josef T1 - Template bacteria-free fabrication of surface imprinted polymer-based biosensor for E. coli detection using photolithographic mimics: Hacking bacterial adhesion JF - Biosensors and Bioelectronics N2 - As one class of molecular imprinted polymers (MIPs), surface imprinted polymer (SIP)-based biosensors show great potential in direct whole-bacteria detection. Micro-contact imprinting, that involves stamping the template bacteria immobilized on a substrate into a pre-polymerized polymer matrix, is the most straightforward and prominent method to obtain SIP-based biosensors. However, the major drawbacks of the method arise from the requirement for fresh template bacteria and often non-reproducible bacteria distribution on the stamp substrate. Herein, we developed a positive master stamp containing photolithographic mimics of the template bacteria (E. coli) enabling reproducible fabrication of biomimetic SIP-based biosensors without the need for the “real” bacteria cells. By using atomic force and scanning electron microscopy imaging techniques, respectively, the E. coli-capturing ability of the SIP samples was tested, and compared with non-imprinted polymer (NIP)-based samples and control SIP samples, in which the cavity geometry does not match with E. coli cells. It was revealed that the presence of the biomimetic E. coli imprints with a specifically designed geometry increases the sensor E. coli-capturing ability by an “imprinting factor” of about 3. These findings show the importance of geometry-guided physical recognition in bacterial detection using SIP-based biosensors. In addition, this imprinting strategy was employed to interdigitated electrodes and QCM (quartz crystal microbalance) chips. E. coli detection performance of the sensors was demonstrated with electrochemical impedance spectroscopy (EIS) and QCM measurements with dissipation monitoring technique (QCM-D). KW - Surface imprinted polymer KW - E. coli detection KW - Photolithographic mimics KW - Master stamp KW - Quartz crystal microbalance Y1 - 2024 U6 - https://doi.org/10.1016/j.bios.2024.116491 SN - 1873-4235 (eISSN) SN - 0956-5663 N1 - Corresponding author: Michael J. Schöning VL - 261 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Ketelhut, Maike A1 - Brügge, G. M. A1 - Göll, Fabian A1 - Braunstein, Bjoern A1 - Albracht, Kirsten A1 - Abel, Dirk T1 - Adaptive iterative learning control of an industrial robot during neuromuscular training JF - IFAC PapersOnLine N2 - To prevent the reduction of muscle mass and loss of strength coming along with the human aging process, regular training with e.g. a leg press is suitable. However, the risk of training-induced injuries requires the continuous monitoring and controlling of the forces applied to the musculoskeletal system as well as the velocity along the motion trajectory and the range of motion. In this paper, an adaptive norm-optimal iterative learning control algorithm to minimize the knee joint loadings during the leg extension training with an industrial robot is proposed. The response of the algorithm is tested in simulation for patients with varus, normal and valgus alignment of the knee and compared to the results of a higher-order iterative learning control algorithm, a robust iterative learning control and a recently proposed conventional norm-optimal iterative learning control algorithm. Although significant improvements in performance are made compared to the conventional norm-optimal iterative learning control algorithm with a small learning factor, for the developed approach as well as the robust iterative learning control algorithm small steady state errors occur. KW - Iterative learning control KW - Robotic rehabilitation KW - Adaptive control Y1 - 2020 U6 - https://doi.org/10.1016/j.ifacol.2020.12.741 SN - 2405-8963 VL - 53 IS - 2 SP - 16468 EP - 16475 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Ketelhut, Maike A1 - Kolditz, Melanie A1 - Göll, Fabian A1 - Braunstein, Bjoern A1 - Albracht, Kirsten A1 - Abel, Dirk T1 - Admittance control of an industrial robot during resistance training JF - IFAC-PapersOnLine N2 - Neuromuscular strength training of the leg extensor muscles plays an important role in the rehabilitation and prevention of age and wealth related diseases. In this paper, we focus on the design and implementation of a Cartesian admittance control scheme for isotonic training, i.e. leg extension and flexion against a predefined weight. For preliminary testing and validation of the designed algorithm an experimental research and development platform consisting of an industrial robot and a force plate mounted at its end-effector has been used. Linear, diagonal and arbitrary two-dimensional motion trajectories with different weights for the leg extension and flexion part are applied. The proposed algorithm is easily adaptable to trajectories consisting of arbitrary six-dimensional poses and allows the implementation of individualized trajectories. KW - Assistive technology KW - Rehabilitation engineering KW - Human-Computer interaction KW - Automatic control Y1 - 2019 U6 - https://doi.org/10.1016/j.ifacol.2019.12.102 SN - 2405-8963 N1 - 14th IFAC Symposium on Analysis, Design, and Evaluation of Human Machine Systems HMS 2019 Tallinn, Estonia, 16–91 September 2019 VL - 52 IS - 19 SP - 223 EP - 228 PB - Elsevier CY - Amsterdam ER -