The integration of a digital twin into inspection planning enables a novel procedure that reduces avoidable inspection times and costs. This paper shows a method for component-specific adaption of inspection plans by feeding ...

Bystander programs contribute to crime prevention by motivating people to intervene in violent situations. Social media allow addressing very specific target groups, and provide valuable information for program evaluation. ...

In this study, the thermal conductivity ( κ ) of Al-Cu eutectics were investigated by experimental and computational methods to shed light on the role of these compounds in thermal properties of Al-Cu connections in compound ...

Density functional theory calculations are robust tools to explore the mechanical properties of pristine structures at their ground state but become exceedingly expensive for large systems at finite temperatures. Classical ...

Most machine learning algorithms are configured by a set of hyperparameters whose values must be carefully chosen and which often considerably impact performance. To avoid a time-consuming and irreproducible manual process ...

With the growing interest in the field of artificial materials, more advanced and sophisticated functionalities are required from phononic crystals and acoustic metamaterials. This implies a high computational effort and ...

This study draws on machine learning as a means to causal inference for econometric investigation. We utilize the concept of transfer entropy to examine the relationship between the US National Association of Home Builders ...

As a pilot study, we present 1)a database that includes 30 daily-life table-top tasks, which were selected within the SoftPro project, and 2)a novel autoencoder-based muscle synergy identification method, whose results ...

The possibility of acquiring data in production and manufacturing processes is almost limitless. But especially small and medium-sized enterprises (SMEs) lack the knowledge to successfully integrate digital tools and use ...

The recent advent and evolution of deep learning models and pre-trained embedding techniques have created a breakthrough in supervised learning. Typically, we expect that adding more labeled data improves the predictive ...