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The Robot Operating System (ROS) is the current de-facto standard in robot middlewares. The steadily increasing size of the user base results in a greater demand for training as well. User groups range from students in academia to industry professionals with a broad spectrum of developers in between. To deliver high quality training and education to any of these audiences, educators need to tailor individual curricula for any such training. In this paper, we present an approach to ease compiling curricula for ROS trainings based on a taxonomy of the teaching contents. The instructor can select a set of dedicated learning units and the system will automatically compile the teaching material based on the dependencies of the units selected and a set of parameters for a particular training. We walk through an example training to illustrate our work.
Complexity for heterogeneous classes: teaching embedded systems using an open project approach
(2019)
Composite improvement of textile reinforced concrete by polymeric impregnation of the textiles
(2006)
The composition of plant biomass varies depending on the feedstock and pre-treatment conditions and influences its processing in biorefineries. In order to ensure optimal process conditions, the quantitative proportion of the main polymeric components of the pre-treated biomass has to be determined. Current standard procedures for biomass compositional analysis are complex, the measurements are afflicted with errors and therefore often not comparable. Hence, new powerful analytical methods are urgently required to characterize biomass. In this contribution, Differential Scanning Calorimetry (DSC) was applied in combination with multivariate data analysis (MVA) to detect the cellulose content of the plant biomass pretreated by Liquid Hot Water (LHW) and Organosolv processes under various conditions. Unlike conventional techniques, the developed analytic method enables the accurate quantification of monosaccharide content of the plant biomass without any previous sample preparation. It is easy to handle and avoids errors in sample preparation.
This paper presents a novel numerical procedure for computing limit and shakedown loads of structures using a node-based smoothed FEM in combination with a primal–dual algorithm. An associated primal–dual form based on the von Mises yield criterion is adopted. The primal-dual algorithm together with a Newton-like iteration are then used to solve this associated primal–dual form to determine simultaneously both approximate upper and quasi-lower bounds of the plastic collapse limit and the shakedown limit. The present formulation uses only linear approximations and its implementation into finite element programs is quite simple. Several numerical examples are given to show the reliability, accuracy, and generality of the present formulation compared with other available methods.