Browsing by Author "Amann, Marco"

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Open Access
Efficient splitter for data parallel complex event processing
(2018) Amann, Marco
Complex Event Processing systems are a promising approach to detect patterns on ever growing amounts of event streams. Since a single server might not be able to run an operator at a sufficiently high rate, Data Parallel Complex Event Processing aims to distribute the load of one operator onto multiple nodes. In this work we analyze the splitter of an existing CEP framework, detail on its drawbacks and propose optimizations to cope with them. This yields the newly developed SPACE framework, which is evaluated and compared with an industry-proven CEP framework, Apache Flink. We show that the new splitter has greatly improved performance and is able to support more instances at a higher rate. In comparison with Apache Flink, the SPACE framework is able to process events at higher rates in our benchmarks but is less stable if overloaded.
Open Access
Visualization of differences in perception caused by vision deficiency
(2021) Amann, Marco
Simulation of visual impairments may be used to counter design exclusion and improve the accessibility of products. Whilst first-hand experience of the simulated scene is important, having to manually look for differences caused by vision deficiencies, let alone judge their severity, is time-consuming and error-prone. In this work, we develop an error metric that tracks errors and uncertainty throughout the stages of a simulator for visual impairments. This allows us to visualize errors and uncertainty independently in all tracked dimensions. We add more advanced view modes to the simulator to enable visualization of our error metric in combination with the input and output images. We further extend the simulator to include simulations for strabismus, astigmatism and retinal ganglion cells. By simulating several combinations of vision deficiency, we found that a visualization of the proposed metric can be used to identify problematic areas in a scene. Depending on the use case, one may need to select different combination functions generating scalar values, e.g. the aggregated standard deviation of the RGBXY vector. With a comparison of our metric to SSIM, we found that our metric can cope better with displaced features of an image but may produce blurred visualizations. We conclude that although our metric imposes considerable performance penalties on the simulator, it has advantages compared to approaches based exclusively on input and output images.