IRF: Institutional Repository FHNW (Hochschule für Wirtschaft FHNW)
Not a member yet
31163 research outputs found
Sort by
Large Language Model support in drafting a Business Process
No full textAccording to the 2018 survey, BPM has been very high on most companies’ list of priorities since the survey started back in 2003. Paul Harmon’s (2018) survey indicates that organisations go through cycles of interest in the Business Process Management work. Each of the
peaks of interest are preceded by some novel concept, new technological development or economical cycle, even if the overall interest keeps growing (Harmon, 2018) With the advent of relatively cheap and readily available LLMs, we are on the potential verge of the new BPM hype cycle. Researchers and companies alike are exploring all possible applications of the LLMs in the daily operations to gain efficiencies, improve profits and simply gain a competitive advantage over the competition. Business process modelling is the key capability in any BPM initiative. It helps to ensure the quality of the communication between the various stakeholders, structures the common business understanding and streamlines the ease of understanding between different domains such as business and IT. No BPM initiative could be successful without the modelling capabilities, as is a crucial part in every step of the Dumas et al., 2018 BPM lifecycle
Fachlichkeit fachfremd Sport unterrichtender Grundschullehrkräfte
No full textDer Beitrag fokussiert auf die Mindestkompetenzen fachfremd unterrichtende Primarlehrpersonen für das Schulfach Bewegung und Sport
Webbasierte Automatsierung des Inkubator-Fragebogens
No full textInkubatoren fördern Innovation und wirtschaftliches Wachstum, daher möchte das FHNW
ImpactLab ihre Effektivität mit einer präzisen Selbstanalyse ihrer Stärken und Schwächen
unterstützen. Derzeit basiert die Auswertung kritischer Erfolgsfaktoren auf einem ineffizienten,
manuell gesteuerten Prozess, der Google Forms und ein R-Skript nutzt. Dieser Prozess ist
ineffizient und schwer zugänglich. Um die Bewertung zu optimieren und diesen manuellen
Prozess abzulösen, benötigt das FHNW ImpactLab eine online zugängliche und automatisierte
Lösung
Focal molography allows for affinity and concentration measurements of proteins in complex matrices with high accuracy
No full textCharacterizing biomolecular receptor–ligand interactions is critical for research and development. However, performing analyses in complex, biologically relevant matrices, such as serum, remains challenging due to non-specific binding that often impairs measurements. Here, we evaluated Focal Molography (FM) for determining KD and kinetic constants in comparison to gold-standard methods using single-domain heavy-chain antibodies in various systems. FM provided kinetic constants highly comparable to SPR and BLI in standard buffers containing blocking proteins, with KDs of soluble CD4 (sCD4) interactions within a 2.4-fold range across technologies. In buffers lacking blocking proteins, FM demonstrated greater robustness against non-specific binding and rebinding effects. In serum, FM exhibited stable baseline signals, unlike SPR and BLI, and yielded KDs of sCD4 interaction in 50% Bovine Serum within a 1.8-fold range of those obtained in standard buffers. For challenging molecules prone to non-specific binding (Granzyme B), FM successfully determined kinetic constants without external referencing. Finally, FM enabled direct analyte quantification in complex matrices. sCD4 quantification in cell culture media and 50% FBS showed recovery rates of 97.8–100.3% with an inter-assay CV below 1.3%. This study demonstrates the high potential of FM for kinetic affinity determination and biomarker quantification in complex matrices, enabling reliable measurements under biologically relevant conditions
The universal robot of the 21st century
No full textDevelopments in several areas of computer science, robotics, and social robotics make it seem likely that a universal robot will be available in the foreseeable future. Large language models for communication, perception, and control play a central role in this. This article briefly outlines the developments in the various areas and uses them to create the overall image of the universal robot. It then discusses the associated challenges from an ethical and social science perspective. It can be said that the universal robot will bring with it new possibilities and will perhaps be one of the most powerful human tools in physical space. At the same time, numerous problems are foreseeable, individual, social, and ecological.https://cas.au.dk/en/robophilosophy/conferences/rpc202
Bildung in einer diversen und komplexen Welt. Digitale Bildung und Bildung für eine Nachhaltige Entwicklung als Herausforderungen und Chancen für die Lehrer*innenbildung
No full textQUBO formulations and characterization of penalty parameters for the multi-knapsack problem
No full textThe Multi-Knapsack Problem (MKP) is a fundamental challenge in operations research and combinatorial optimization. Quantum computing introduces new possibilities for solving MKP using Quadratic Unconstrained Binary Optimization (QUBO) models. However, a key challenge in QUBO formulations is the selection of penalty parameters, which directly influence solution feasibility and algorithm performance. In this work, we develop QUBO formulations for two MKP variants—the Multidimensional Knapsack Problem (MDKP) and the Multiple Knapsack Problem (MUKP)—and provide an algebraic characterization of their penalty parameters. We systematically evaluate their impact through quantum simulation experiments and compare the performance of the two leading quantum optimization approaches: Quantum Approximate Optimization Algorithm (QAOA) and quantum annealing, alongside a state-of-the-art classical solver. Our results indicate that while classical solvers remain superior, careful tuning of penalty parameters significantly affects quantum optimization outcomes. QAOA is highly sensitive to parameter choices, whereas quantum annealing produces more stable results on small to mid-sized instances. Finally, we outline directions for future research in solvingMKP, including adaptive penalty parameter tuning, hybrid quantum-classical approaches, and practical optimization strategies for QAOA, as well as real-hardware evaluations