The HAM10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions

Training of neural networks for automated diagnosis of pigmented skin lesions is hampered by the small size and lack of diversity of available datasets of dermatoscopic images. We tackle this problem by releasing the HAM10000 ("Human Against Machine with 10000 training images") dataset. We collected dermatoscopic images from different populations acquired and stored by different modalities. Given this diversity we had to apply different acquisition and cleaning methods and developed semi-automatic workflows utilizing specifically trained neural networks. The final dataset consists of 10015 dermatoscopic images which are released as a training set for academic machine learning purposes and are publicly available through the ISIC archive. This benchmark dataset can be used for machine learning and for comparisons with human experts. Cases include a representative collection of all important diagnostic categories in the realm of pigmented lesions. More than 50% of lesions have been confirmed by pathology, while the ground truth for the rest of the cases was either follow-up, expert consensus, or confirmation by in-vivo confocal microscopy

From bulk to structural failure: fracture of hyperelastic materials

This thesis investigates the fracture of nearly incompressible hyperelastic media. It covers the different characteristics of bulk material failure under dilatational or distortional loads and develops a unified description of the corresponding failure surface. It proposes a coupled strain and energy failure criterion for the assessment of notch-induced crack nucleation and presents a weak interface model that allows for efficient stress, strain and failure analyses of hyperelastic adhesive lap joints. Theoretical concepts for the measurement of fracture properties of nonlinear elastic materials are provided. The methodology is developed using two exemplary hyperelastic silicones, DOWSIL 993 Structural Glazing Sealant and DOWSIL Transparent Structural Silicone Adhesive, and is validated using large sets of experiments of different loading conditions

360° videos in education – A systematic literature review on application areas and future potentials

As a teaching and learning medium, 360° videos offer new teaching-learning experiences. Through the possibility of immersion, individual 360° panoramic images, multi-perspective viewing options and interaction possibilities, they extend the advantages of conventional video technology. To understand the potential of using 360° video technology for educational processes, a systematic literature review analyzed previous scientific articles (N = 44) about the interdisciplinary use of 360° videos according to PRISMA guidelines. In the systematic literature selection, particular emphasis was placed on the conceptual distinction between virtual reality and 360° videos. By the authors, 360° videos are understood as a specific video format that has characteristics of virtual reality but is to be distinguished from virtual reality by the necessary real recording situation without programmed virtual environments. The results show a use of 360° videos mainly for three teaching-learning purposes: presentation and observation of teaching–learning content, immersive and interactive theory–practice mediation, and external and self-reflection. Combined with the added value of conventional video technology and other immersive technology such as virtual reality, five added value categories for its use as a teaching–learning medium were identified: To increase learning motivation and interest, to learn in authentic and realistic learning scenarios, for immersive and interactive learning experiences, for multi-perspective observation opportunities and for individual learning. These consisted primarily of positive motivational effects for authentic or immersive learning experiences

360-Videotechnologie im Sport – ein systematisches Review zu Einsatzbereichen und Potenzialen als Lehr-Lernmedium

360°-Videos erweitern die Vorteile herkömmlicher Videos mit Interaktions-spiel-räumen, mehrperspektivischen Reflexionsmöglichkeiten und Immersi-on. Um deren Potenziale für Lehr-Lernprozesse im Sport zu nutzen, wurden in einer systematischen Übersicht bisherige wissenschaftliche Beiträge (n = 18) zum Einsatz von 360°-Videos im Sport aufgearbeitet, um daraus Chan-cen zur Implementierung als Lehr-Lernmedium im Sport abzuleiten. 360°-Videos werden hauptsächlich für kognitive, mentale, technische und reflekti-ve Trainingsprozesse verwendet. Aus den eingeschlossenen Beiträgen ergaben sich induktiv sechs Mehrwertkategorien zur Verwendung als Lehr-Lernmedium, vor allem motivationale Effekte, authentische und immersive Lernerfahrungen

360°-Videos für beobachtendes und nachahmendes Kata-Training im Karate

Seit der Corona-Pandemie werden Sportlehrkräfte sowie Trainerinnen und Trainer vor neue Herausforderungen gestellt, Sport- und Trainingsangebote weiterhin zu gewährleisten. Digitale Trainingsmöglichkeiten, z. B. mit Videoeinsatz, wurden entsprechend erprobt. Einen neuen Ansatz bietet die 360°-Videotechnologie. In 360°-Videos können Betrachtende ihre Blickperspektive um die Kamera herum selbst wählen. Mit einfachen Schritten lässt sich diese Möglichkeit für beobachtende Trainingsprozesse nutzen, etwa um sich eine Bewegungsabfolge anzueignen. Im vorliegenden Beitrag wird ein einfach gestaltbares methodisch-didaktisches Konzept vorgestellt, welches bereits im Karate-Kata-Training exemplarisch erprobt wird und sich auch auf andere Sportbereiche übertragen lässt

Application of a reduced basis method for an efficient treatment of structural mechanics problems

For numerous problems in structural mechanics, a repeated solution of partial differential equations (PDEs), varying certain input parameters, is necessary. Solving the PDE for a large number of different input parameter sets using a full‐dimensional finite element method, requires repeated solving of large systems of equations and, thus, leads to a high computational effort. The aim of model order reduction techniques is to reduce the computational complexity in such calculations. In order to achieve this, the idea of the reduced basis method [1–3] is to replace the high‐dimensional model with a lower dimensional model, which is realized by forming a basis of solutions of the full problem for selected parameter sets. Key to determining suitable parameter sets is an appropriate error estimator