Due to recent advances in data science and Big Data the importance of data is increasing.
Although service choreographies provide means to specify complex conversations between …

This paper studies the joint learning of action recognition and temporal localization in long,
untrimmed videos. We employ a multi-task learning framework that performs the three highly …

The increasing amount of gathered sensor data in Industry 4.0 allows comprehensive data
analysis software that creates value-adding opportunities. As companies often cannot …

Current systems for enacting scientific experiments, and simulation workflows in particular,
do not support multi-scale and multi-field problems if they are not coupled on the level of the …

Computer-aided engineering (CAE) applications support the digital transformation of the
manufacturing industry. They facilitate virtual product development and product testing via …

In recent years scientific workflows have been used for conducting data-intensive and long
running simulations. Such simulation workflows have processed and produced different …

Simulations are characterized by long running calculations and complex data handling tasks
accompanied by non-trivial data dependencies. The workflow technology helps to automate …

Managing data exchange in scientific workflow simulations is a challenge for which existing
solutions have only limited success. Basing on a data-model approach we developed a …

The approach of ProHTA (Prospective Health Technology Assessment) is to understand the
impact of medical processes and technologies as early as possible. Therefore, simulation …

Current systems for enacting scientific experiments, and in particular simulation workflows,
do not support multi-scale and multi-field problems if they are not coupled on the level of the …