13 Zentrale Universitätseinrichtungen

Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/14

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Institute: search.filters.UBSInstitut.Fakultätsübergreifend / Sonstige EinrichtungSubject: search.filters.subject.004Start date: 2025End date: 2025

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Now showing 1 - 5 of 5
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    Governance of high-risk AI systems in healthcare and credit scoring
    (2025) Bartsch, Sebastian; Behn, Oliver; Benlian, Alexander; Brownsword, Roger; Bücker, Sebastian; Düwell, Marcus; Formánek, Nico; Jungtäubl, Marc; Leyer, Michael; Richter, Alexander; Schmidt, Jan-Hendrik; Will-Zocholl, Mascha
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    Editorial - visualizing big culture and history data
    (2025) Windhager, Florian; Koch, Steffen; Münster, Sander; Mayr, Eva
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    Fourth-order paired-explicit Runge-Kutta methods
    (2025) Doehring, Daniel; Christmann, Lars; Schlottke-Lakemper, Michael; Gassner, Gregor; Torrilhon, Manuel
    In this paper, we extend the Paired-Explicit Runge-Kutta (P-ERK) schemes by Vermeire et al. (J Comput Phys 393:465-483, 2019) and Nasab and Vermeire (J Comput Phys 468:111470, 2022) to fourth-order of consistency. Based on the order conditions for partitioned Runge-Kutta methods we motivate a specific form of the Butcher arrays which leads to a family of fourth-order accurate methods. The employed form of the Butcher arrays results in a special structure of the stability polynomials, which needs to be adhered to for an efficient optimization of the domain of absolute stability. We demonstrate that the constructed fourth-order P-ERK methods satisfy linear stability, internal consistency, designed order of convergence, and conservation of linear invariants. At the same time, these schemes are seamlessly coupled for codes employing a method-of-lines approach, in particular without any modifications of the spatial discretization. We demonstrate speedup for single-threaded program executions, shared-memory parallelism, i.e., multi-threaded executions and distributed-memory parallelism with MPI. We apply the multirate P-ERK schemes to inviscid and viscous problems with locally varying wave speeds, which may be induced by non-uniform grids or multiscale properties of the governing partial differential equation. Compared to state-of-the-art optimized standalone methods, the multirate P-ERK schemes allow significant reductions in right-hand-side evaluations and wall-clock time, ranging from up to factors greater than four. A reproducibility repository is provided which enables the reader to examine all results presented in this work.
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    A knowledge-based approach for guided development of infrastructure as code
    (2025) Vasileiou, Zoe; Kumara, Indika; Meditskos, Georgios; Tokmakov, Kamil; Radolović, Dragan; Cruz, Jesús Gorroñogoitia; Di Nitto, Elisabetta; Tamburri, Damian Andrew; Heuvel, Jan-Willem van den ; Vrochidis, Stefanos
    Infrastructure as Code (IaC) uses versionable software code to define, deploy, and configure physical computational resources, software execution platforms, and applications. As a result, IaC enables the scalable management of complex computing environments while preventing environment drift. IaC frameworks typically offer specific languages such as the industrial Terraform, Ansible, Chef, or TOSCA-standing for Topology and Orchestration Specification for Cloud Applications-the OASIS (Organization for the Advancement of Structured Information Standards) open standard approach to IaC. Developing high-quality IaC for deploying and managing applications demands expertise and knowledge in specific IaC languages, infrastructure resources, resource providers, quality issues in IaC scripts, and so on. While several model-driven engineering (MDE) approaches have been proposed to simplify IaC development, they cannot capture and use expert knowledge to assist with modeling tasks and MDE processes by providing interactive recommendations. This paper presents a knowledge-based framework for guiding the model-driven development of IaC. We use TOSCA as the target IaC language as it is an open standard. We enable IaC and resource experts to share their IaC and resource-related knowledge with application operational experts to help simplify the development of application deployment models. We use an ontology to record the relevant deployment knowledge and ontology reasoning to implement modeling guidance capabilities such as TOSCA model auto-completion, code smell and error detection, and model element matchmaking. We show the flexibility of our methodology by applying it to three industrial applications, covering cloud, edge, and HPC (High-Performance Computing) domains. Moreover, we also assess the use acceptance of our approach and framework by conducting controlled experiments with expert and non-expert IaC users. The results indicate that our method can simplify IaC development by providing appropriate recommendations.
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    Desktop versus VR for collaborative sensemaking
    (2025) Yang, Ying; Dwyer, Tim; Swiecki, Zachari; Lee, Benjamin; Wybrow, Michael; Cordeil, Maxime; Wulandari, Teresa; Thomas, Bruce H.; Billinghurst, Mark
    Immersive environments enable people to share a workspace in a more spatial and embodied manner than traditional desktop collaboration platforms. However, it remains unclear whether such differences support collaborators in sharing information to build mutual understanding during sensemaking. To investigate this, we conducted a user study with groups of four participants - each given exclusive starting information - using mind maps as a medium for information sharing and collaborative sensemaking. Participants used both the VR and desktop systems we developed to complete sensemaking tasks. Our results reveal that the primary focuses of mind-mapping activities differed between VR and desktop: participants in VR engaged more in problem solving, whereas on desktop they concentrated more on mind map organisation. We synthesise our results from post hoc analysis, observations and subjective feedback, and attribute the discrepancies to the fundamental distinctions between the affordances of traditional desktop tools and embodied presence and interactions in VR. We therefore suggest additional features that facilitate mind map authoring and organisation such as automatic mechanisms be considered essential in future immersive mind-mapping systems.