@article{KubingerSommer, author = {Kubinger, Wilfried and Sommer, Roland}, title = {Industrie 4.0 - Auswirkungen von Digitalisierung und Internet auf den Industriestandort}, series = {e\&i Elektrotechnik und Informationstechnik}, volume = {133}, journal = {e\&i Elektrotechnik und Informationstechnik}, number = {7}, pages = {330 -- 333}, subject = {Industry 4.0}, language = {de} } @article{OtrebskiRauerEngelhardtNowitzkietal., author = {Otrebski, Richard and Rauer, Johannes and Engelhardt-Nowitzki, Corinna and Kryvinska, Natalia and Aburaia, Mohamed and Pospisil, Dominik}, title = {Flexibility Enhancements in Digital Manufacturing by means of Ontological Data Modeling}, series = {International Journal of Ubiquitous Systems and Pervasive Networks (JUSPN)}, journal = {International Journal of Ubiquitous Systems and Pervasive Networks (JUSPN)}, number = {Volume 12, Issue 2}, subject = {Communication Modeling}, language = {en} } @article{HuFengZhangetal., author = {Hu, Qingxi and Feng, Di and Zhang, Haiguang and Yao, Yuan and Aburaia, Mohamed and Lammer, Herfried}, title = {Oriented to Multi-Branched Structure Unsupported 3D Printing Method Research}, series = {Materials, vol. 13, no. 9, p. 2023, Apr. 2020}, journal = {Materials, vol. 13, no. 9, p. 2023, Apr. 2020}, subject = {Structure}, language = {en} } @article{EngelhardtNowitzkiAburaiaRauer, author = {Engelhardt-Nowitzki, Corinna and Aburaia, Mohamed and Rauer, Johannes}, title = {Research-based teaching in digital manufacturing and robotics - the Digital Factory at the UAS Technikum Wien as an exemplary case}, series = {CLF2020 TU Graz}, journal = {CLF2020 TU Graz}, subject = {Digital Manufacturing}, language = {en} } @article{AburaiaStujaMarkl, author = {Aburaia, Mohamed and Stuja, Kemajl and Markl, Erich}, title = {Design and control of 4 axis additive manufactured robot using software tools}, series = {Procedia Engineering 100}, journal = {Procedia Engineering 100}, subject = {Robotics}, language = {en} } @article{Aburaia, author = {Aburaia, Mohamed}, title = {Digitale Fabrik}, series = {So funktioniert Wirtschaft. Ein Sachbuch f{\"u}r Jugendliche}, journal = {So funktioniert Wirtschaft. Ein Sachbuch f{\"u}r Jugendliche}, subject = {Digital Factory}, language = {de} } @article{DelucaBermejoMoratinosGruenbichleretal., author = {Deluca, Marco and Bermejo Moratinos, Ra{\´u}l and Gr{\"u}nbichler, Hannes and Pressler, Volker and Danzer, Robert and Nickel, Klaus G.}, title = {Raman spectroscopy for the investigation of indentation-induced domain texturing in lead zirconate titanate piezoceramics}, series = {Scripta materialia}, journal = {Scripta materialia}, number = {63(2)}, pages = {343 -- 346}, subject = {Materials}, language = {en} } @article{GruenbichlerKreithBermejoMoratinosetal., author = {Gr{\"u}nbichler, Hannes and Kreith, Josef and Bermejo Moratinos, Ra{\´u}l and Supancic, Peter and Danzer, Robert}, title = {Modelling of the ferroic material behaviour of piezoelectrics: Characterisation of temperature-sensitive functional properties}, series = {Journal of the European Ceramic Society}, journal = {Journal of the European Ceramic Society}, number = {30}, pages = {249 -- 254}, subject = {Materials}, language = {en} } @article{BermejoMoratinosGruenbichlerKreithetal., author = {Bermejo Moratinos, Ra{\´u}l and Gr{\"u}nbichler, Hannes and Kreith, Josef and Auer, Christoph}, title = {Fracture resistance of a doped PZT ceramic for multilayer piezoelectric actuators: Effect of mechanical load and temperature}, series = {Journal of the European Ceramic Society}, journal = {Journal of the European Ceramic Society}, number = {30}, pages = {705 -- 712}, subject = {Materials}, language = {en} } @article{SchwaabGruenbichlerSupancicetal., author = {Schwaab, Holger and Gr{\"u}nbichler, Hannes and Supancic, Peter and Kamlah, Marc}, title = {Macroscopical non-linear material model for ferroelectric materials inside a hybrid finite element formulation}, series = {International Journal of Solids and Structures}, journal = {International Journal of Solids and Structures}, number = {49}, pages = {457 -- 469}, subject = {Ferroelectricity}, language = {en} } @article{BermejoMoratinosGruenbichlerLubeetal., author = {Bermejo Moratinos, Raul and Gr{\"u}nbichler, Hannes and Lube, Tanja and Supancic, Peter and Danzer, Robert and Sestakova, Lucie}, title = {Fracture Mechanisms of Structural and Functional Multilayer Ceramic Structures}, series = {Key engineering materials}, volume = {2011}, journal = {Key engineering materials}, number = {Vol. 465}, pages = {41 -- 46}, subject = {Materials}, language = {en} } @article{GruenbichlerKreithBermejoMoratinosetal., author = {Gr{\"u}nbichler, Hannes and Kreith, Josef and Bermejo Moratinos, Ra{\´u}l and Krautgasser, Clemens and Supancic, Peter}, title = {Influence of the Load Dependent Material Properties on the Performance of Multilayer Piezoelectric Actuators}, series = {IUTAM Bookseries (24), Springer}, volume = {2011}, journal = {IUTAM Bookseries (24), Springer}, number = {24}, pages = {243 -- 253}, subject = {Materials}, language = {en} } @article{KubingerPeschakWoeberetal., author = {Kubinger, Wilfried and Peschak, Bernhard and W{\"o}ber, Wilfried and Sulz, Clemens}, title = {Bildgebende Sensorsystems f{\"u}r robotische Systeme in der Agrar- und Landtechnik}, series = {e\&i Elektrotechnik und Informationstechnik}, volume = {134}, journal = {e\&i Elektrotechnik und Informationstechnik}, number = {6}, pages = {316 -- 322}, subject = {Sensor}, language = {de} } @article{WoeberRauerPapaetal., author = {W{\"o}ber, Wilfried and Rauer, Johannes and Papa, Maximilian and Aburaia, Ali and Schwaiger, Simon and Novotny, Georg and Aburaia, Mohamed and Kubinger, Wilfried}, title = {Evaluierung von Navigationsmethoden f{\"u}r mobile Roboter}, series = {e \& i Elektrotechnik und Informationstechnik}, journal = {e \& i Elektrotechnik und Informationstechnik}, subject = {Robotics}, language = {de} } @article{StadlerBloeschlVogletal., author = {Stadler, Philipp and Bl{\"o}schl, G{\"u}nter and Vogl, Wolfgang and Koschelnik, Juri and Epp, Markus, and Lackner, Maximilian and Oism{\"u}ller, Markus and Kumpan, Monika and Nemeth, Lukas, and Strauss, Peter and Sommer, Regina and Ryzinska-Paier, Gabriela and Farnleitner, Andras and Zessner, Matthias}, title = {Real-time monitoring of beta-D-glucuronidase activity in sediment laden streams: A comparison of prototypes}, series = {Real-time monitoring of beta-D-glucuronidase activity in sediment laden streams}, journal = {Real-time monitoring of beta-D-glucuronidase activity in sediment laden streams}, subject = {Enzymes}, language = {en} } @article{EngelhardtNowitzkiAburaiaOtrebskietal., author = {Engelhardt-Nowitzki, Corinna and Aburaia, Mohamed and Otrebski, Richard and Rauer, Johannes and Orsolits, Horst}, title = {Research-based teaching in Digital Manufacturing and Robotics - the Digital Factory at the UAS Technikum Wien as a Case Example}, series = {Procedia Manufacturing}, journal = {Procedia Manufacturing}, number = {Volume 45}, pages = {164 -- 170}, subject = {Digital Factory}, language = {en} } @article{RauerAburaiaWoeber, author = {Rauer, Johannes and Aburaia, Mohamed and W{\"o}ber, Wilfried}, title = {Semi-Automatic Generation of Training Data for Neural Networks for 6D Pose Estimation and Robotic Graspin}, series = {Proceedings of Joint Austrian Computer Vision and Robotics Workshop 2020}, journal = {Proceedings of Joint Austrian Computer Vision and Robotics Workshop 2020}, pages = {2 -- 3}, subject = {Robotics}, language = {en} } @article{EngelhardtNowitzkiAburaiaOtrebskietal., author = {Engelhardt-Nowitzki, Corinna and Aburaia, Mohamed and Otrebski, Richard and Rauer, Johannes and Orsolits, Horst}, title = {Research-based teaching in Digital Manufacturing and Robotics - the Digital Factory at the UAS Technikum Wien as a Case Example}, series = {Procedia Manuf}, journal = {Procedia Manuf}, subject = {Teaching}, language = {en} } @article{AburaiaLacknerBucheretal., author = {Aburaia, Mohamed and Lackner, Maximilian and Bucher, Michael and Gonzalez-Gutierrez, Joamin and Zhang, Haiguang and Lammer, Herfried}, title = {A Production Method for Standardized Continuous Fiber Reinforced FFF Filament}, series = {A Production Method for Standardized Continuous Fiber Reinforced FFF Filament," vol. 4, no. 1, p. 12, 2020}, journal = {A Production Method for Standardized Continuous Fiber Reinforced FFF Filament," vol. 4, no. 1, p. 12, 2020}, subject = {Production}, language = {en} } @article{TomicDrenjanacLazendicetal., author = {Tomic, Dana Kathrin and Drenjanac, Domagoj and Lazendic, Goran and H{\"o}rmann, Sandra and Handler, Franz and W{\"o}ber, Wilfried and Aschauer, Christian and Auer, Wolfgang}, title = {Semantische Technologien f{\"u}r Produktionsprozessinnovationen in der Landwirtschaft}, series = {e\&i Elektrotechnik und Informationstechnik}, volume = {131}, journal = {e\&i Elektrotechnik und Informationstechnik}, number = {7}, pages = {223 -- 229}, subject = {Semantics}, language = {de} } @article{TomicDrenjanacLazendicetal., author = {Tomic, Dana Kathrin and Drenjanac, Domagoj and Lazendic, Goran and H{\"o}rmann, Sandra and Handler, Franz and W{\"o}ber, Wilfried and Aschauer, Christian and Auer, Wolfgang}, title = {Ontologies and semantic services for process optimization in agricultural production}, series = {e\&i Elektrotechnik und Informationstechnik}, journal = {e\&i Elektrotechnik und Informationstechnik}, subject = {Semantics}, language = {en} } @article{KamravamaneshPflueglNischkaueretal., author = {Kamravamanesh, Donya and Pfl{\"u}gl, Stefan and Nischkauer, Winfried and Limbeck, Andreas and Lackner, Maximilian and Herwig, Christoph}, title = {Photosynthetic poly-β-hydroxybutyrate accumulation in unicellular cyanobacterium Synechocystis sp. PCC 6714}, series = {AMB Express}, volume = {143}, journal = {AMB Express}, number = {7}, subject = {Bacteria}, language = {en} } @article{SpitzerSonnleitnerKempeLackner, author = {Spitzer-Sonnleitner, Birgit and Kempe, Andre and Lackner, Maximilian}, title = {Influence of halide solutions on collagen networks - measurements of physical properties by atomic force microscopy (AFM)}, series = {Influence of halide solutions on collagen networks}, journal = {Influence of halide solutions on collagen networks}, subject = {Collagen Networks}, language = {en} } @article{WoeberMehnenCurtoetal., author = {W{\"o}ber, Wilfried and Mehnen, Lars and Curto, Manuel and Dias Tibihika, Papius and Tesfaye, Genanaw and Meimberg, Harald}, title = {Investigating Shape Variation Using Generalized Procrustes Analysis and Machine Learning}, series = {Applied Sciences}, volume = {2022}, journal = {Applied Sciences}, number = {12(6), 3158}, pages = {26}, abstract = {Abstract: The biological investigation of a population's shape diversity using digital images is typi- cally reliant on geometrical morphometrics, which is an approach based on user-defined landmarks. In contrast to this traditional approach, the progress in deep learning has led to numerous applications ranging from specimen identification to object detection. Typically, these models tend to become black boxes, which limits the usage of recent deep learning models for biological applications. However, the progress in explainable artificial intelligence tries to overcome this limitation. This study compares the explanatory power of unsupervised machine learning models to traditional landmark-based approaches for population structure investigation. We apply convolutional autoencoders as well as Gaussian process latent variable models to two Nile tilapia datasets to investigate the latent structure using consensus clustering. The explanatory factors of the machine learning models were extracted and compared to generalized Procrustes analysis. Hypotheses based on the Bayes factor are formulated to test the unambiguity of population diversity unveiled by the machine learning models. The findings show that it is possible to obtain biologically meaningful results relying on unsupervised machine learning. Furthermore we show that the machine learning models unveil latent structures close to the true population clusters. We found that 80\% of the true population clusters relying on the convolutional autoencoder are significantly different to the remaining clusters. Similarly, 60\% of the true population clusters relying on the Gaussian process latent variable model are significantly different. We conclude that the machine learning models outperform generalized Procrustes analysis, where 16\% of the population cluster was found to be significantly different. However, the applied machine learning models still have limited biological explainability. We recommend further in-depth investigations to unveil the explanatory factors in the used model. Keywords: generalized procrustes analysis; machine learning; convolutional autoencoder; Gaussian process latent variable models}, subject = {generalized procrustes analysis}, language = {en} } @article{WoeberCurtoTibihikaetal., author = {W{\"o}ber, Wilfried and Curto, Manuel and Tibihika, Papius D. and Meulenboek, Paul and Alemayehu, Esayas and Mehnen, Lars and Meimberg, Harald and Sykacek, Peter}, title = {Identifying geographically differentiated features of Ethopian Nile tilapia (Oreochromis niloticus) morphology with machine learning}, series = {PlosONE}, volume = {16}, journal = {PlosONE}, number = {4}, subject = {Machine Learning}, language = {en} } @article{SattingerPapaStujaetal., author = {Sattinger, Vinzenz and Papa, Maximilian and Stuja, Kemajl and Kubinger, Wilfried}, title = {Methodik zur Entwicklung sicherer kollaborativer Produktionssysteme im Rahmen von Industrie 4.0}, series = {e \& i Elektrotechnik und Informationstechnik}, journal = {e \& i Elektrotechnik und Informationstechnik}, subject = {Robotics}, language = {de} } @article{WoeberMehnenSykaceketal., author = {W{\"o}ber, Wilfried and Mehnen, Lars and Sykacek, Peter and Meimberg, Harald}, title = {Investigating Explanatory Factors of Machine Learning Models for Plant Classification}, series = {Plants}, volume = {2021}, journal = {Plants}, number = {10(12):2674}, pages = {20}, abstract = {Recent progress in machine learning and deep learning has enabled the implementation of plant and crop detection using systematic inspection of the leaf shapes and other morphological characters for identification systems for precision farming. However, the models used for this approach tend to become black-box models, in the sense that it is difficult to trace characters that are the base for the classification. The interpretability is therefore limited and the explanatory factors may not be based on reasonable visible characters. We investigate the explanatory factors of recent machine learning and deep learning models for plant classification tasks. Based on a Daucus carota and a Beta vulgaris image data set, we implement plant classification models and compare those models by their predictive performance as well as explainability. For comparison we implemented a feed forward convolutional neuronal network as a default model. To evaluate the performance, we trained an unsupervised Bayesian Gaussian process latent variable model as well as a convolutional autoencoder for feature extraction and rely on a support vector machine for classification. The explanatory factors of all models were extracted and analyzed. The experiments show, that feed forward convolutional neuronal networks (98.24\% and 96.10\% mean accuracy) outperforms the Bayesian Gaussian process latent variable pipeline (92.08\% and 94.31\% mean accuracy) as well as the convolutional autoenceoder pipeline (92.38\% and 93.28\% mean accuracy) based approaches in terms of classification accuracy, even though not significant for Beta vulgaris images. Additionally, we found that the neuronal network used biological uninterpretable image regions for the plant classification task. In contrast to that, the unsupervised learning models rely on explainable visual characters. We conclude that supervised convolutional neuronal networks must be used carefully to ensure biological interpretability. We recommend unsupervised machine learning, careful feature investigation, and statistical feature analysis for biological applications. View Full-Text Keywords: deep learning; machine learning; plant leaf morphometrics; explainable AI}, subject = {deep learning}, language = {en} }