27 research outputs found

    Hardware Ports - Getting Rid of Sandboxed Modelled Software

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    Way of Working for Embedded Control Software using Model-Driven Development Techniques

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    The relative importance of plant-soil feedbacks for plant-species performance increases with decreasing intensity of herbivory

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    Under natural conditions, aboveground herbivory and plant-soil feedbacks (PSFs) are omnipresent interactions strongly affecting individual plant performance. While recent research revealed that aboveground insect herbivory generally impacts the outcome of PSFs, no study tested to what extent the intensity of herbivory affects the outcome. This, however, is essential to estimate the contribution of PSFs to plant performance under natural conditions in the field. Here, we tested PSF effects both with and without exposure to aboveground herbivory for four common grass species in nine grasslands that formed a gradient of aboveground invertebrate herbivory. Without aboveground herbivores, PSFs for each of the four grass species were similar in each of the nine grasslands—both in direction and in magnitude. In the presence of herbivores, however, the PSFs differed from those measured under herbivory exclusion, and depended on the intensity of herbivory. At low levels of herbivory, PSFs were similar in the presence and absence of herbivores, but differed at high herbivory levels. While PSFs without herbivores remained similar along the gradient of herbivory intensity, increasing herbivory intensity mostly resulted in neutral PSFs in the presence of herbivores. This suggests that the relative importance of PSFs for plant-species performance in grassland communities decreases with increasing intensity of herbivory. Hence, PSFs might be more important for plant performance in ecosystems with low herbivore pressure than in ecosystems with large impacts of insect herbivores.Plant science

    Connecting ROS to a real-time control framework for embedded computing

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    Modern robotic systems tend to get more complex sensors at their disposal, resulting in complex algorithms to process their data. For example, camera images are being used map their environment and plan their route. On the other hand, the robotic systems are becoming mobile more often and need to be as energy-efficient as possible; quadcopters are an example of this. These two trends interfere with each other: Data-intensive, complex algorithms require a lot of processing power, which is in general not energy-friendly nor mobile-friendly.\ud \ud In this paper, we describe how to move the complex algorithms to a computing platform that is not part of the mobile part of the setup, i.e. to offload the processing part to a base station. We use the ROS framework for this, as ROS provides a lot of existing computation solutions. On the mobile part of the system, our hard real-time execution framework, called LUNA, is used, to make it possible to run the loop controllers on it.\ud \ud The design of a ‘bridge node’ is explained, which is used to connect the LUNA framework to ROS. The main issue to tackle is to subscribe to an arbitrary ROS topic at run-time, instead of defining the ROS topics at compile-time. Furthermore, it is shown that this principle is working and the requirements of network bandwidth are discussed
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