FH Upper AustriaResearch & Development

Software Technology and Applications Research Center Hagenberg Campus

Publications

An integrated approach for power transformer modeling and manufacturing

C. Lettner, M. Moser, J. Pichler - An integrated approach for power transformer modeling and manufacturing - International Conference on Industry 4.0 and Smart Manufacturing, Linz, Austria, 2020, pp. 351-355
Essential characteristics of smart factories, such as flexibility and resource efficiency, can be leveraged and improved by the power of machine learning and…   mehr
  • Proceedings
  • Software Technology and Applications

Stepwise abstraction of high-level system specifications from source code

F. Ferrarotti, M. Moser, J. Pichler - Stepwise abstraction of high-level system specifications from source code - Journal of Computer Languages, 2020
We are interested in specifications which provide a consistent high-level view of systems. They should abstract irrelevant details and provide a precise and…   mehr
  • Journal
  • Software Technology and Applications

Strategies for Training Deep Learning Models in Medical Domains with Small Reference Datasets

G. Zwettler, D. Holmes III, W. Backfrieder - Strategies for Training Deep Learning Models in Medical Domains with Small Reference Datasets - Proceedings of the WSCG 2020, Pilsen, Czech Republic, 2020, pp. 10
  • Proceedings
  • Software Technology and Applications

Hybrid Approach for Orientation-Estimation of Rotating Humans in Video Frames Acquired by Stationary Monocular Camera

D. Baumgartner, C. Praschl, T. Zucali, G. Zwettler - Hybrid Approach for Orientation-Estimation of Rotating Humans in Video Frames Acquired by Stationary Monocular Camera - Proceedings of the WSCG 2020, Pilsen, Czech Republic, 2020, pp. 9
The precise orientation-estimation of humans relative to the POSE of a monocular camera system is a challenging task due to the general aspects of camera…   mehr
  • Proceedings
  • Software Technology and Applications

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…   mehr
  • Journal
  • Software Technology and Applications
  • Materials and Production Engineering

Effects of Arrival Uncertainty on Solver Performance in Dynamic Stacking Problems

S. Raggl, A. Beham, S. Wagner, M. Affenzeller - Effects of Arrival Uncertainty on Solver Performance in Dynamic Stacking Problems - Proceedings of the 32nd European Modeling & Simulation Symposium (EMSS 2020), Online, Greece, 2020, pp. 193-200
In this paper, we present a dynamic stacking problem with uncertainty. We developed a simulation environment, an optimizer for solving it, and performance…   mehr
  • Proceedings
  • Production and Operations Management
  • Software Technology and Applications

Copyright relevance of AI-generated and encrypted Content

P. Burgstaller, E. Hermann - Copyright relevance of AI-generated and encrypted Content - Journal for IP and Copyright, 2020
The use of artificially intelligent (AI) systems affects almost all areas of law - from employment law and data protection law to health and care to "classic"…   mehr
  • Journal
  • Software Technology and Applications

Using Deep Learning for Depth Estimation and 3D Reconstruction of Humans

A. Freller, G. Zwettler - Using Deep Learning for Depth Estimation and 3D Reconstruction of Humans - Proceedings of the 32th EUROPEAN MODELING AND SIMULATION SYMPOSIUM, Athen, Greece, 2020, pp. 6
  • Proceedings
  • Software Technology and Applications

Characterizing Energy Consumption of Third-Party API Libraries using API Utilization Profiles

A. Schuler, G. Anderst-Kotsis - Characterizing Energy Consumption of Third-Party API Libraries using API Utilization Profiles - 2020 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM), Bari, Italy, 2020
Background: Third-party software libraries often serve as fundamental building blocks for developing applications. However, depending on such libraries for…   mehr
  • Proceedings
  • Software Technology and Applications

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
  • Proceedings
  • Software Technology and Applications

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, Germany, 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…   mehr
  • Proceedings
  • Software Technology and Applications
  • Food Technology and Biotechnology

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…   mehr
  • Journal
  • Software Technology and Applications

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, United Kingdom of Great Britain and Northern Ireland, 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…   mehr
  • Proceedings
  • Software Technology and Applications

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, Austria, 2019, pp. 104-108
In this paper, we focus on the development and application of a cost optimized sensor platform for predictive maintenance of industrial fans. Typically,…   mehr
  • Proceedings
  • Software Technology and Applications

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, Spain, 2019
Monitoring critical components of systems is a crucial step towards failure safety. Affordable sensors are available and the industry is in the process of…   mehr
  • Proceedings
  • Software Technology and Applications

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…   mehr
  • Journal
  • Software Technology and Applications

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, United States of America, 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…   mehr
  • Proceedings
  • Software Technology and Applications

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
Virtual Reality (VR) technology still needs to evolve, but as the pace of innovations accelerates, systems allow for more novel modes of visualization and…   mehr
  • Journal
  • Production and Operations Management
  • Software Technology and Applications

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, Germany, 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…   mehr
  • Proceedings
  • Software Technology and Applications

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, France, 2019, pp. 267-283
  • Proceedings
  • Software Technology and Applications

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, Spain, 2019
Industrial applications of machine learning face unique challenges due to the nature of raw industry data. Preprocessing and preparing raw industrial data…   mehr
  • Proceedings
  • Software Technology and Applications

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