Teachers’ self-efficacy in managing classrooms is an important consideration when it comes to bringing educational robots to classrooms. Orchestration tools support teachers by providing awareness indicators of students’ progress as well as levers to contr ...
Detailed chemical abundances of very metal-poor (VMP; [Fe/H] < -2) stars are important for better understanding the first stars, early star formation, and chemical enrichment of galaxies. Big on-going and coming high-resolution spectroscopic surveys provid ...
Understanding how biological matter takes its shape is instrumental to biology, bioengineering, medicine, and bioinspired engineering. Gaining information on the principles of morphogenesis could enable clinicians to correct developmental abnormalities, ev ...
Every engineering calculation is an approximation of reality, with inevitable uncertainties involved. This fact implies that a reliability verification accounting for the uncertainties is a necessary step in the design and assessment of structures. Nowaday ...
Conventional formworks for concrete curved shells either are expensive, complex and wasteful or have formal restrictions. Using tile vaults (also known as timbrel, Guastavino, thin-tile or Catalan vaults) as stay-in-place formwork for concrete shells could ...
Time has always been a central factor in understanding the challenges of daily mobility. For a long time, and still today, methods of economic evaluation of transport projects have monetized time savings so that they can be included in the cost–benefit ana ...
In this paper, we consider electric vehicle charging facilities that offer various levels of service, i.e., charging rates, for varying prices such that rational users choose a level of service that minimizes the total cost to themselves including an oppor ...
ML-based edge devices may face memory and computational errors that affect applications' reliability and performance. These errors can be the result of particular working conditions (e.g., radiation areas in physical experiments or avionics) or could be th ...
K-means is one of the fundamental unsupervised data clustering and machine learning methods. It has been well studied over the years: parallelized, approximated, and optimized for different cases and applications. With increasingly higher parallelism leadi ...
