000 Informatik, Informationswissenschaft, allgemeine Werke
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Even though in most cases time is a good metric to measure costs of algorithms, there are cases where theoretical worst-case time and experimental running time do not match. Since modern CPUs feature an innate memory hierarchy, the location of data is another factor to consider. When most operations of an algorithm are executed on data which is already in the CPU cache, the running time is significantly faster than algorithms where most operations have to load the data from the memory. The topic of this thesis is a new metric to measure costs of algorithms called memory distance—which can be seen as an abstraction of the just mentioned aspect. We will show that there are simple algorithms which show a discrepancy between measured running time and theoretical time but not between measured time and memory distance. Moreover we will show that in some cases it is sufficient to optimize the input of an algorithm with regard to memory distance (while treating the algorithm as a black box) to improve running times. Further we show the relation between worst-case time, memory distance and space and sketch how to define "the usual" memory distance complexity classes.
Similarity-based retrieval of semantic graphs is a core task of Process-Oriented Case-Based Reasoning (POCBR) with applications in real-world scenarios, e.g., in smart manufacturing. The involved similarity computation is usually complex and time-consuming, as it requires some kind of inexact graph matching. To tackle these problems, we present an approach to modeling similarity measures based on embedding semantic graphs via Graph Neural Networks (GNNs). Therefore, we first examine how arbitrary semantic graphs, including node and edge types and their knowledge-rich semantic annotations, can be encoded in a numeric format that is usable by GNNs. Given this, the architecture of two generic graph embedding models from the literature is adapted to enable their usage as a similarity measure for similarity-based retrieval. Thereby, one of the two models is more optimized towards fast similarity prediction, while the other model is optimized towards knowledge-intensive, more expressive predictions. The evaluation examines the quality and performance of these models in preselecting retrieval candidates and in approximating the ground-truth similarities of a graph-matching-based similarity measure for two semantic graph domains. The results show the great potential of the approach for use in a retrieval scenario, either as a preselection model or as an approximation of a graph similarity measure.
Designing a Randomized Trial with an Age Simulation Suit—Representing People with Health Impairments
(2020)
Due to demographic change, there is an increasing demand for professional care services, whereby this demand cannot be met by available caregivers. To enable adequate care by relieving informal and formal care, the independence of people with chronic diseases has to be preserved for as long as possible. Assistance approaches can be used that support promoting physical activity, which is a main predictor of independence. One challenge is to design and test such approaches without affecting the people in focus. In this paper, we propose a design for a randomized trial to enable the use of an age simulation suit to generate reference data of people with health impairments with young and healthy participants. Therefore, we focus on situations of increased physical activity.
Der vorliegende Bericht basiert auf einer universitätsweiten Online-Umfrage zum Status quo des Forschungsdatenma-nagements an der Universität Trier. Er ist ein erster Schritt, um den aktuellen und zukünftigen Bedarf an zentralen Dienstleistungen zu identifizieren. Neue Handlungsfelder sollen frühzeitig erkannt werden, auch um der Strategie-entwicklung eine Richtung zu weisen.rnDie Befragten befürworten generell die Initiative zur Entwicklung zentraler IT- und Beratungsangebote. Sie sind bereit, die eigenen Forschungsdaten anderen zur Nachnutzung zur Verfügung zu stellen, sofern die geeigneten Instrumente vorhanden, sind die eine solche Arbeitsweise unterstützen. Allerdings wird eine unkommentierte Bereit-stellung von Rohdaten eher kritisch beurteilt. Der Dokumentationsaufwand einer öffentlichen Bereitstellung von Daten wird in einem ungünstigen Kosten-Nutzenverhältnis gesehen. Es fällt auf, dass die Datenarchivierung größ-tenteils in proprietären Formaten erfolgt.