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This document presents an algorithm for a non-obtrusive recognition of Sleep/Wake states using signals derived from ECG, respiration, and body movement captured while lying in a bed. As a core mathematical base of system data analytics, multinomial logistic regression techniques were chosen. Derived parameters of the three signals are used as the input for the proposed method. The overall achieved accuracy rate is 84% for Wake/Sleep stages, with Cohen’s kappa value 0.46. The presented algorithm should support experts in analyzing sleep quality in more detail. The results confirm the potential of this method and disclose several ways for its improvement.
Im vorliegenden Aufsatz werden die rechnerischen Rissbreiten bei frühem und bei spätem Zwang verglichen. Insbesondere wird der Fall betrachtet, dass nach einer frühen Rissbildung infolge Abfließens der Hydratationswärme im fortgeschrittenen Betonalter Zwängungen durch Schwinden und/oder Temperatureinflüsse entstehen. Es wird gezeigt, dass die im jungen Betonalter entstandenen Risse zunächst breiter werden, bevor neue Risse infolge späten Zwangs entstehen können, und dass die resultierende Rissbreite dann größer ist, als wenn die Risse ausschließlich durch späten Zwang entstehen. Für die rechnerische Behandlung dieser Problematik wird ein einfaches Rechenverfahren aufgezeigt. Des Weiteren wird auf die Konzentration von zwangsbedingten Rissen in Schwachstellen, z. B. bei Bodenplatten und Decken mit großen Aussparungen, eingegangen und es wird dargestellt, wie für solche Bauteilgeometrien die rechnerische Begrenzung der Rissbreite erfolgen kann.
One way of reducing carbon emissions is to reduce carbon emissions from consumption. Quantitative information about these emissions helps to better understand the reduction potential. This article aims to provide carbon footprint data for students of the University of Applied Science in Konstanz, Germany. The study includes almost 10% of the University’s students. Data on emission patterns was collected via questionnaires and calculated by a web-based carbon calculator. The study analyses personal carbon footprints and, more detailed, carbon emissions from consumption categories heating, electricity, mobility (land travel and aviation) and food. The findings show average students’ annual carbon footprint to be10.9t CO2eq and in the same order of magnitude as the German average. While students cause less emissions through heating because of smaller living space per person, they cause significantly more emissions by aviation. Female students tend to have higher emissions from aviation, instead male students have higher emissions from food (due to more meat in their diet). Business students have higher emissions than others, mainly because they are tending to fly more. The student carbon footprint is far above climate protection goals formulated for 2050.
The evolution of strain induced martensite in austenitic stainless steel AISI 304 was investigated in a rolling contact on a two-discs-tribometer. The effects of surface roughness, slip and normal force as well as the number of load cycles were examined. In comparison to the investigations of martensitic phase transformation during cold rolling, the applied stresses are considerably lower. The formation of strain induced martensite was detected in-situ by means of a FERITSCOPE MP30 and ex-situ by optical microscopy after etching with Kane etchant. Both number of load cycles and magnitude of normal force appeared to be the main influencing factors regarding strain induced martensitic evolution in low stress rolling contacts.