TY - JOUR A1 - Kaniusas, Eugenijus A1 - Pfützner, Helmut A1 - Mehnen, Lars T1 - Optical tissue absorption sensor on the thorax: Possibilities and restrictions JF - International Journal of Applied Electromagnetics and Mechanics KW - Tissue Absorption KW - Sensor KW - Thorax Y1 - 2018 VL - 25 IS - 1-4 SP - 649 EP - 655 ER - TY - JOUR A1 - Wöber, Wilfried A1 - Mehnen, Lars A1 - Curto, Manuel A1 - Dias Tibihika, Papius A1 - Tesfaye, Genanaw A1 - Meimberg, Harald T1 - Investigating Shape Variation Using Generalized Procrustes Analysis and Machine Learning JF - Applied Sciences N2 - 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 KW - generalized procrustes analysis KW - machine learning KW - convolutional autoencoder KW - Gaussian process latent variable models Y1 - VL - 2022 IS - 12(6), 3158 ER - TY - JOUR A1 - Kaniusas, Eugenijus A1 - Pfützner, Helmut A1 - Mehnen, Lars A1 - Kosel, Jürgen A1 - Meydan, Turgut A1 - Vazquez, Manuel A1 - Rohn, Michael A1 - Merlo, Alberto Maria A1 - Marquardt, Bernd T1 - Dynamic Measuring of Inductivity Changes by Adaptive Controlling and Lock-in Technique JF - Journal of Electrical Engineering KW - Adaptive Controlling KW - Dynamic Measuring Y1 - 2019 VL - 2004 IS - 55 / 10 SP - 49 EP - 52 ER - TY - JOUR A1 - Pfützner, Helmut A1 - Kaniusas, Eugenijus A1 - Mehnen, Lars A1 - Meydan, Turgut A1 - Vazquez, Manuel A1 - Rohn, Michael A1 - Merlo, Alberto A1 - Marquardt, Bernd T1 - Magnetorestrictive bilayers for multi-functional sensor families JF - Sensors and Actuators A KW - Magnetism KW - Sensor Y1 - 2018 VL - 129 IS - 1 SP - 154 EP - 158 ER - TY - JOUR A1 - Obergruber, Julian A1 - Mehnen, Lars T1 - Development of a paraglide control system for automatic pitch JF - Proceedings of the 11th Conference of the International Sports Engineering Association (ISEA) 2016 KW - Control System Y1 - 2018 ER - TY - JOUR A1 - Kaniusas, Eugenijus A1 - Mehnen, Lars A1 - Pfützner, Helmut T1 - Magnetostrictive amorphous bilayers and trilayers for thermal sensors JF - Journal of Magnetism and Magnetic Materials KW - Magnetism KW - Sensor Y1 - IS - 254 - 255 SP - 624 EP - 626 ER - TY - JOUR A1 - Wöber, Wilfried A1 - Curto, Manuel A1 - Tibihika, Papius D. A1 - Meulenboek, Paul A1 - Alemayehu, Esayas A1 - Mehnen, Lars A1 - Meimberg, Harald A1 - Sykacek, Peter T1 - Identifying geographically differentiated features of Ethopian Nile tilapia (Oreochromis niloticus) morphology with machine learning JF - PlosONE KW - Machine Learning Y1 - VL - 16 IS - 4 ER - TY - JOUR A1 - Kaniusas, Eugenijus A1 - Pfützner, Helmut A1 - Mehnen, Lars A1 - Kosel, Jürgen A1 - Hasenzagl, Andreas T1 - Optimisation of Magnetostrictive Bilayer Sensors for Medical Applications JF - International Journal of Applied Electromagnetics and Mechanics KW - Magnetism KW - Medical Technology Y1 - 2018 VL - 28 IS - 1,2 SP - 193 EP - 199 ER - TY - JOUR A1 - Kaniusas, Eugenijus A1 - Pfützner, Helmut A1 - Mehnen, Lars A1 - Kosel, Jürgen A1 - Varoneckas, Giedrius A1 - Alonderis, Audrius A1 - Meydan, Turgut A1 - Vazquez, Manuel A1 - Rohn, Michael A1 - Merlo, Alberto A1 - Marquardt, Bernd T1 - Magnetoelastic bilayer concept for skin curvature sensor JF - Ultrasound KW - Magnetism KW - Skin Curvature KW - Sensor Y1 - 2019 VL - 52 IS - 3 SP - 42 EP - 46 ER - TY - JOUR A1 - Kaniusas, Eugenijus A1 - Pfützner, Helmut A1 - Mehnen, Lars A1 - Kosel, Jürgen A1 - Tellez-Blanco, Juan C. A1 - Varoneckas, Giedrius A1 - Alonderis, Audrius A1 - Meydan, Turgut A1 - Vazquez, Manuel A1 - Rohn, Michael A1 - Merlo, Alberto A1 - Marquardt, Bernd T1 - Method for continuous non-disturbing monitoring of blood pressure by magnetoelastic skin curvature sensor and ECG JF - IEEE Sensors Journal KW - Blood Pressure KW - Magnetism KW - Sensor KW - Curvature Y1 - 2018 VL - 6 IS - 3 SP - 819 EP - 828 ER -