TY - JOUR A1 - Grajewski, Matthias A1 - Kleefeld, Andreas T1 - Detecting and approximating decision boundaries in low-dimensional spaces JF - Numerical Algorithms N2 - A method for detecting and approximating fault lines or surfaces, respectively, or decision curves in two and three dimensions with guaranteed accuracy is presented. Reformulated as a classification problem, our method starts from a set of scattered points along with the corresponding classification algorithm to construct a representation of a decision curve by points with prescribed maximal distance to the true decision curve. Hereby, our algorithm ensures that the representing point set covers the decision curve in its entire extent and features local refinement based on the geometric properties of the decision curve. We demonstrate applications of our method to problems related to the detection of faults, to multi-criteria decision aid and, in combination with Kirsch’s factorization method, to solving an inverse acoustic scattering problem. In all applications we considered in this work, our method requires significantly less pointwise classifications than previously employed algorithms. KW - MCDA KW - Inverse scattering problem KW - Fault approximation KW - Fault detection Y1 - 2023 SN - 1572-9265 N1 - Corresponding author: Matthias Grajewski VL - 93 IS - 4 PB - Springer Science+Business Media CY - Dordrecht 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 - Achtsnicht, Stefan A1 - Tödter, Julia A1 - Niehues, Julia A1 - Telöken, Matthias A1 - Offenhäusser, Andreas A1 - Krause, Hans-Joachim A1 - Schröper, Florian T1 - 3D printed modular immunofiltration columns for frequency mixing-based multiplex magnetic immunodetection JF - Sensors N2 - For performing point-of-care molecular diagnostics, magnetic immunoassays constitute a promising alternative to established enzyme-linked immunosorbent assays (ELISA) because they are fast, robust and sensitive. Simultaneous detection of multiple biomolecular targets from one body fluid sample is desired. The aim of this work is to show that multiplex magnetic immunodetection based on magnetic frequency mixing by means of modular immunofiltration columns prepared for different targets is feasible. By calculations of the magnetic response signal, the required spacing between the modules was determined. Immunofiltration columns were manufactured by 3D printing and antibody immobilization was performed in a batch approach. It was shown experimentally that two different target molecules in a sample solution could be individually detected in a single assaying step with magnetic measurements of the corresponding immobilization filters. The arrangement order of the filters and of a negative control did not influence the results. Thus, a simple and reliable approach to multi-target magnetic immunodetection was demonstrated. Y1 - 2019 U6 - https://doi.org/10.3390/s19010148 SN - 1424-8220 VL - 19 IS - 1 PB - MDPI CY - Basel ER - TY - CHAP A1 - Baier, Ralph A1 - Brauner, Philipp A1 - Brillowski, Florian A1 - Dammers, Hannah A1 - Liehner, Luca A1 - Pütz, Sebastian A1 - Schneider, Sebastian A1 - Schollemann, Alexander A1 - Steuer-Dankert, Linda A1 - Vervier, Luisa A1 - Gries, Thomas A1 - Leicht-Scholten, Carmen A1 - Mertens, Alexander A1 - Nagel, Saskia K. A1 - Schuh, Günther A1 - Ziefle, Martina A1 - Nitsch, Verena ED - Brecher, Christian ED - Schuh, Günther ED - van der Alst, Wil ED - Jarke, Matthias ED - Piller, Frank T. ED - Padberg, Melanie T1 - Human-centered work design for the internet of production T2 - Internet of production - fundamentals, applications and proceedings N2 - Like all preceding transformations of the manufacturing industry, the large-scale usage of production data will reshape the role of humans within the sociotechnical production ecosystem. To ensure that this transformation creates work systems in which employees are empowered, productive, healthy, and motivated, the transformation must be guided by principles of and research on human-centered work design. Specifically, measures must be taken at all levels of work design, ranging from (1) the work tasks to (2) the working conditions to (3) the organizational level and (4) the supra-organizational level. We present selected research across all four levels that showcase the opportunities and requirements that surface when striving for human-centered work design for the Internet of Production (IoP). (1) On the work task level, we illustrate the user-centered design of human-robot collaboration (HRC) and process planning in the composite industry as well as user-centered design factors for cognitive assistance systems. (2) On the working conditions level, we present a newly developed framework for the classification of HRC workplaces. (3) Moving to the organizational level, we show how corporate data can be used to facilitate best practice sharing in production networks, and we discuss the implications of the IoP for new leadership models. Finally, (4) on the supra-organizational level, we examine overarching ethical dimensions, investigating, e.g., how the new work contexts affect our understanding of responsibility and normative values such as autonomy and privacy. Overall, these interdisciplinary research perspectives highlight the importance and necessary scope of considering the human factor in the IoP. KW - Responsibility KW - Privacy KW - Digital leadership KW - Best practice sharing KW - Cognitive assistance system KW - Human-robot collaboration KW - Human-centered work design Y1 - 2023 SN - 978-3-030-98062-7 U6 - https://doi.org/10.1007/978-3-030-98062-7_19-1 N1 - Part of the book series: Interdisciplinary Excellence Accelerator Series (IDEAS) SP - 1 EP - 23 PB - Springer CY - Cham ER - TY - JOUR A1 - Achtsnicht, Stefan A1 - Schönenborn, Kristina A1 - Offenhäusser, Andreas A1 - Krause, Hans-Joachim T1 - Measurement of the magnetophoretic velocity of different superparamagnetic beads JF - Journal of Magnetism and Magnetic Materials N2 - The movement of magnetic beads due to a magnetic field gradient is of great interest in different application fields. In this report we present a technique based on a magnetic tweezers setup to measure the velocity factor of magnetically actuated individual superparamagnetic beads in a fluidic environment. Several beads can be tracked simultaneously in order to gain and improve statistics. Furthermore we show our results for different beads with hydrodynamic diameters between 200 and 1000 nm from diverse manufacturers. These measurement data can, for example, be used to determine design parameters for a magnetic separation system, like maximum flow rate and minimum separation time, or to select suitable beads for fixed experimental requirements. KW - magnetophoretic velocity KW - superparamagnetic bead KW - magnetic tweezers KW - magnetic separation KW - magnetic actuation Y1 - 2019 U6 - https://doi.org/10.1016/j.jmmm.2018.10.066 SN - 0304-8853 VL - 477 IS - 1 SP - 244 EP - 248 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Digel, Ilya A1 - Akimbekov, Nuraly S. A1 - Rogachev, Evgeniy A1 - Pogorelova, Natalia T1 - Bacterial cellulose produced by Medusomyces gisevii on glucose and sucrose: biosynthesis and structural properties JF - Cellulose N2 - In this work, the effects of carbon sources and culture media on the production and structural properties of bacterial cellulose (BC) synthesized by Medusomyces gisevii have been studied. The culture medium was composed of different initial concentrations of glucose or sucrose dissolved in 0.4% extract of plain green tea. Parameters of the culture media (titratable acidity, substrate conversion degree etc.) were monitored daily for 20 days of cultivation. The BC pellicles produced on different carbon sources were characterized in terms of biomass yield, crystallinity and morphology by field emission scanning electron microscopy (FE-SEM), atomic force microscopy and X-ray diffraction. Our results showed that Medusomyces gisevii had higher BC yields in media with sugar concentrations close to 10 g L−1 after a 18–20 days incubation period. Glucose in general lead to a higher BC yield (173 g L−1) compared to sucrose (163.5 g L−1). The BC crystallinity degree and surface roughness were higher in the samples synthetized from sucrose. Obtained FE-SEM micrographs show that the BC pellicles synthesized in the sucrose media contained densely packed tangles of cellulose fibrils whereas the BC produced in the glucose media displayed rather linear geometry of the BC fibrils without noticeable aggregates. KW - Bacterial cellulose KW - Medusomyces gisevi KW - Carbon sources KW - Culture media KW - Cellulose nanostructure Y1 - 2023 U6 - https://doi.org/10.1007/s10570-023-05592-z SN - 1572-882X (Online) SN - 0969-0239 (Print) N1 - Corresponding author: Ilya Digel PB - Springer Science + Business Media CY - Dordrecht ER -