Software Technologie und Anwendungen Research Center Hagenberg
Publikationen
Supporting Teamwork in Industrial Virtual Reality Applications
J. Wolfartsberger, J. Zenisek, N. Wild - Supporting Teamwork in Industrial Virtual Reality Applications - Procedia Manufacturing, 2020, pp. 2-7
Virtual Reality (VR) systems allow for novel modes of visualization and interaction to support engineering design reviews. However, there are still research…
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Urheberrechtliche Relevanz von KI-generierten sowie verschlüsselten Inhalten
P. Burgstaller, E. Hermann - Urheberrechtliche Relevanz von KI-generierten sowie verschlüsselten Inhalten - Österreichsiche Blätter für gewerblichen Rechtsschutz und Urheberrecht, 2020
Der Einsatz von künstlich intelligenten (KI) Systemen tangiert beinahe alle Rechtsbereiche – vom Arbeits- und Datenschutzrecht über das Gesundheits- und Pflege…
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Pre- and Post-processing Strategies for Generic Slice-wise Segmentation of Tomographic 3D datasets Utilizing U-Net Deep Learning Models Trained for Specific Diagnostic Domains
G. Zwettler, D. Holmes III, W. Backfrieder - Pre- and Post-processing Strategies for Generic Slice-wise Segmentation of Tomographic 3D datasets Utilizing U-Net Deep Learning Models Trained for Specific Diagnostic Domains - Proceedings of the VISAPP 2020, Valetta, Malta, 2020, pp. 66-78
MS Annika: A New Search Tool for the Identification of Cross-Linked Peptides from Tandem Mass Spectrometry Data
G. J. Pirklbauer, C. Stieger, S. M. Winkler, K. Mechtler, V. Dorfer - MS Annika: A New Search Tool for the Identification of Cross-Linked Peptides from Tandem Mass Spectrometry Data - Proceedings of the 9th Symposium on Structural Proteomics (SSP2019), Göttingen, Deutschland, 2019
Numerous chemical cross-linkers linkers have been developed over the last years, each with their own physical and chemical properties [1]. The development of…
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Parameter identification for symbolic regression using nonlinear least squares
M. Kommenda, B. Burlacu, G. K. Kronberger, M. Affenzeller - Parameter identification for symbolic regression using nonlinear least squares - Genetic Programming and Evolvable Machines, 2019, pp. 471-501
In this paper we analyze the effects of using nonlinear least squares for parameter identification of symbolic regression models and integrate it as local…
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Using Ontologies to Express Prior Knowledge for Genetic Programming
S. Prieschl, D. Girardi, G. K. Kronberger - Using Ontologies to Express Prior Knowledge for Genetic Programming - Machine Learning and Knowledge Extraction. CD-MAKE 2019., Canterbury, Vereinigtes Königreich von Großbritannien und Nordirland, 2019, pp. 362-376
Ontologies are useful for modeling domains and can be used to capture expert knowledge about a system. Genetic programming can be used to identify statistical…
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A Cost Optimized Data Acquisition System For Predictive Maintenance
E. Strumpf, F. Holzinger, F. Eibensteiner, J. Langer - A Cost Optimized Data Acquisition System For Predictive Maintenance - 6. Tagung Innovation Messtechnik, Linz, Österreich, 2019, pp. 104-108
Preprocessing and Modeling of Radial Fan Data for Health State Prediction
F. Holzinger, M. Kommenda - Preprocessing and Modeling of Radial Fan Data for Health State Prediction - Computer Aided Systems Theory – EUROCAST 2019, Las Palmas, Gran Canaria, Spanien, 2019
Extended Regression Models for Predicting the Pumping Capability and Viscous Dissipation of Two-Dimensional Flows in Single-Screw Extrusion
W. Roland, M. Kommenda, C. Marschik, J. Miethlinger - Extended Regression Models for Predicting the Pumping Capability and Viscous Dissipation of Two-Dimensional Flows in Single-Screw Extrusion - Polymers, Vol. 11, No. 2, 2019
Generally, numerical methods are required to model the non-Newtonian flow of polymer melts in single-screw extruders. Existing approximation equations for…
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New Approaches for Equalizing the Granulate Size and Bulk Density in Mechanical Recycling Using Heuristic Approaches Based on Specific Data Analyses
M. Aigner, L. Kammerer, F. Schieder, G. K. Kronberger - New Approaches for Equalizing the Granulate Size and Bulk Density in Mechanical Recycling Using Heuristic Approaches Based on Specific Data Analyses - Proceedings of SPE ANTEC 2019, Detroit, Vereinigte Staaten von Amerika, 2019, pp. 1-7
Exactly defined and constant granulates become more and more important in recycling business. The material is very often mixed with virgin granulate, sold on…
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Analyzing the potential of Virtual Reality for engineering design review
J. Wolfartsberger - Analyzing the potential of Virtual Reality for engineering design review - Automation in Construction, 2019, pp. 27-37
Integration of Physical Knowledge in Empirical Models - A New Approach to Regression Analysis
G. K. Kronberger, S. Scheidel, C. Haider, M. Kommenda, M. Kordon - Integration of Physical Knowledge in Empirical Models - A New Approach to Regression Analysis - 8th International Symposium on Development Methodology, Wiesbaden, Deutschland, 2019, pp. 1-9
Design of experiments, empirical modelling and model-based optimization is a widely known and approved approach for high-dimensional optimization problems in…
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Extracting High-Level System Specifications from Source Code via Abstract State Machines
F. Ferrarotti, J. Pichler, M. Moser, G. Buchgeher - Extracting High-Level System Specifications from Source Code via Abstract State Machines - International Conference on Model and Data Engineering, Tuolouse, France, Frankreich, 2019, pp. 267-283
Understanding and Preparing Data of Industrial Processes for Machine Learning Applications
P. Fleck, M. Kügel, M. Kommenda - Understanding and Preparing Data of Industrial Processes for Machine Learning Applications - Computer Aided Systems Theory – EUROCAST 2019, Las Palmas, Gran Canaria, Spanien, 2019
Lost in Translation: Machine Translation and Text-To-Speech in Industry 4.0
J. D. Hallewell Haslwanter, M. Heiml, J. Wolfartsberger - Lost in Translation: Machine Translation and Text-To-Speech in Industry 4.0 - Proceedings of the 12th PErvasive Technologies Related to Assistive Environments Conference, Rhodos, Griechenland, 2019, pp. 10
Small lot sizes are becoming more common in modern manufacturing. Rather than automate every possible product variant, companies may rely on manual assembly to…
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Management von lernfähigen Vorhersage-Modellen für Industrie-Anwendungen
F. Bachinger, G. K. Kronberger - Management von lernfähigen Vorhersage-Modellen für Industrie-Anwendungen - Coming Soon - Tagungsband - 2019, Linz, Österreich, 2019, pp. 253-259
Local Optimization and Complexity Control for Symbolic Regression
M. Kommenda - Local Optimization and Complexity Control for Symbolic Regression - Phd Thesis, Johannes Kepler Universität, Österreich, 2018, pp. 1-157
Symbolische Regression ist ein datenbasiertes, maschinelles Lernverfahren bei dem Vorhersagemodelle in Form mathematischer Ausdrücke ohne vorgegebener…
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Using robust generalized fuzzy modeling and enhanced symbolic regression to model tribological systems
G. K. Kronberger, M. Kommenda, E. Lughofer, S. Saminger-Platz, A. Promberger, F. Nickel, S. M. Winkler, M. Affenzeller - Using robust generalized fuzzy modeling and enhanced symbolic regression to model tribological systems - Applied Soft Computing, 2018, pp. 610-624
Tribological systems are mechanical systems that rely on friction to transmit forces. The design and dimensioning of such systems requires prediction of…
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Schema Analysis in Tree-based Genetic Programming
B. Burlacu, M. Affenzeller, M. Kommenda, G. K. Kronberger, S. M. Winkler - Schema Analysis in Tree-based Genetic Programming in Genetic Programming in Theory and Practice XV (Contributions to Book: Part/Chapter/Section 2), - Springer International Publishing, 2018, pp. 17-37
In this chapter we adopt the concept of schemata from schema theory and use it to analyze population dynamics in genetic programming for symbolic regression.…
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Schema-based Diversification in Genetic Programming
B. Burlacu, M. Affenzeller - Schema-based Diversification in Genetic Programming - GECCO '18: Proceedings of the Genetic and Evolutionary Computation Conference, Kyoto, Japan, Japan, 2018, pp. 1111-1118
In genetic programming (GP), population diversity represents a key aspect of evolutionary search and a major factor in algorithm performance. In this paper we…
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Novel Robustness Measures for Engineering Design Optimisation
P. Fleck, M. Kommenda, T. Prante, M. Affenzeller - Novel Robustness Measures for Engineering Design Optimisation - International Journal of Simulation and Process Modelling, Vol. 13, No. 4, 2018
This paper presents novel robustness measures to analyse and compare the robustness of solutions for constrained optimisation problems in the field of…
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