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Die Arbeit beschreibt die Entwicklung eines Open-Source Plugins für die 3D-Modellierungssoftware FreeCAD, mit welchem es möglich ist, Roboterpfade anhand von 3D-Modellen zu erstellen. Die Pfade sind in einem geeigneten Format exportierbar und können beispielsweise zur Steuerung eines Roboters durch eine speicherprogrammierbare Steuerung verwendet werden. Im ersten Teil der Arbeit wird der geplante Arbeitsablauf der Pfadgenerierung beschrieben und genauer erläutert, welche Vorteile und Pflichten die Erstellung von Open-Source-Software nach sich zieht. Anschließend wird anhand der Systeme „Robot Studio“ von ABB und „MotoSim EG VRC“ von Yaskawa analysiert, wie proprietäre Systeme die Programmierung von Roboterpfaden realisieren. Nach einem Überblick über den aktuellen Stand der Technik in der Roboterprogrammierung, wird die Implementierung des Plugins für FreeCAD beschrieben. Dazu wird anhand des Sourcecodes erläutert, wie neue Arbeitsbereiche erstellt werden können. Es werden verschiedene Funktionen implementiert, welche essenziell für die Erstellung von Roboterpfaden sind. Dazu zählen die Möglichkeit zur Definition von Koordinatensystemen, Roboterposen und das Beschreiben des Roboterpfades durch Pfadsegmente mit verschiedenen Parametern, wie Bewegungsart, Geschwindigkeit und Wegpunkte. Das Plugin wurde getestet indem eine einfache Pick & Place Anwendung erstellt wurde. Anschließend sind mögliche Erweiterungen des Plugins, wie zum Beispiel die Möglichkeit des Duplizierens von Pfadsegmenten am Ende der Arbeit beschrieben.
A concept for a recommender system for the information portal swissmom is designed in this work. The challenges posed by the cold start problem and the pregnancy-related temporal interest changes need to be considered in the concept. A state-of-the-art research on recommender systems is conducted to evaluate suitable models for solving both challenges. The explorative data analysis shows that the article's month of pregnancy is an important indicator of how relevant an article is to a user. Neither collaborative filtering, content-based filtering, hybrid models, nor context-aware recommender systems are applicable because the user's pregnancy phase is unknown in the available data. Therefore, the proposed recommender system concept is a case-based model that recommends articles which belong to the same gestation phase as the currently viewed article.
This recommender system requires that the month of pregnancy, in which an article is relevant, is known for each article. However, this information is only available for 31% of all articles about pregnancy. Consequently, this work looks for an approach to predict the month of gestation based on the article text. The challenges with this are that only few training data are available, and the article texts of the various months of pregnancy often contain the same terms, considering all articles are about pregnancy. A keyword-based approach using the TF-IDF model is compared with a context-based approach using the BERT model. The results show that the context-based approach outperforms the keyword-based approach.
With Cloud Computing and multi-core CPUs parallel computing resources are becoming more and more affordable and commonly available. Parallel programming should as well be easily accessible for everyone. Unfortunately, existing frameworks and systems are powerful but often very complex to use for anyone who lacks the knowledge about underlying concepts. This paper introduces a software framework and execution environment whose objective is to provide a system which should be easily usable for everyone who could benefit from parallel computing. Some real-world examples are presented with an explanation of all the steps that are necessary for computing in a parallel and distributed manner.
The increasing digitalisation of daily routines confronts people with frequent privacy decisions. However, obscure data processing often leads to tedious decision-making and results in unreflective choices that unduly compromise privacy. Serious Games could be applied to encourage teenagers and young adults to make more thoughtful privacy decisions. Creating a Serious Game (SG) that promotes privacy awareness while maintaining an engaging gameplay requires, however, a carefully balanced game concept. This study explores the benefits of an online role-playing boardgame as a co-designing activity for creating SGs about privacy. In a between-subjects trial, student groups and educator/researcher groups were taking the roles of player, teacher, researcher and designer to co-design a balanced privacy SG concept. Using predefined design proposal cards or creating their own, students and educators played the online boardgame during a video conference session to generate game ideas, resolve potential conflicts and balance the different SG aspects. The comparative results of the present study indicate that students and educators alike perceive support from role-playing when ideating and balancing SG concepts and are happy with their playfully co-designed game concepts. Implications for supporting SG design with role-playing in remote collaboration scenarios are conclusively synthesised.