http://dl.gi.de/handle/20.500.12116/40229 Tue, 21 Jul 2026 13:26:50 GMT 2026-07-21T13:26:50Z http://dl.gi.de:80/bitstream/id/ef4f00d6-ba17-42f3-9037-4cf056b6433e/ http://dl.gi.de/handle/20.500.12116/40229 http://dl.gi.de/handle/20.500.12116/40243 The problem of packing modification-disjoint P3 – an overview and an improved heuristic approach Dirks, Jona; Gerhard, Enna Gesellschaft für Informatik e.V. The problem of packing modification-disjoint P₃ – an overview and an improved heuristic approach We consider the problem of packing modification-disjoint induced P₃. This has not been fully researched so far. Induced P₃ are especially relevant to solve the cluster editing problem. We provide an overview and new insights for locating modification-disjoint P₃ packing within the complexity hierarchy. Accordingly, we further look into conflict graphs. In response to our theoretical results, we create a significantly improved heuristic based on the approach of Spinner (2019). We then analyze its efficiency empirically on a selection of generated and public datasets. Our results show that it is either better than existing heuristics when comparing solution size and running time. Sat, 01 Jan 2022 00:00:00 GMT http://dl.gi.de/handle/20.500.12116/40243 2022-01-01T00:00:00Z http://dl.gi.de/handle/20.500.12116/40242 Identifying Alternatives and Deciding Factors for a Data Mesh Architecture Voß, Clara Gesellschaft für Informatik e.V. The data mesh was introduced in 2019 as a new type of data architecture. It promises a more democratic and scalable way of data production and consumption, while also solving data engineering problems of siloed and hyper-specialized data engineering knowledge, a growing number of dependencies within data pipelines, and the rigidness of centralized monoliths. This paper used expert interviews to identify the most significant current alternatives to the data mesh and abstract factors, with which companies can evaluate whether a data mesh can further their move to a data-driven, democratized future. The results show that the motivation, company culture, company structure, IT history and IT structure should be evaluated before implementing a data mesh. This paper is based on a bachelor thesis. Sat, 01 Jan 2022 00:00:00 GMT http://dl.gi.de/handle/20.500.12116/40242 2022-01-01T00:00:00Z http://dl.gi.de/handle/20.500.12116/40241 TD-Browser – A Beginner-friendly Web-Client for the Web of Things Hanoun, Osama Gesellschaft für Informatik e.V. In this paper, I introduce the TD-Browser which enables visual interactions with Web Things by generating user interface elements from Thing Descriptions. The target group are beginners who did not yet understand the concept of the Web of Things. Currently, most available tools focus on scientific purposes with a lack of documentation which makes it hard for newcomers to gain practical experience. For evaluation, I conducted a study using the Concurrent Think-aloud method with one subject to uncover first design flaws. Although TD-Browser cannot be used for teaching beginners the concepts of the Web of Things for now, its clean user interface enables users to work and interact effortlessly with Web Things. Sat, 01 Jan 2022 00:00:00 GMT http://dl.gi.de/handle/20.500.12116/40241 2022-01-01T00:00:00Z http://dl.gi.de/handle/20.500.12116/40240 Methode für Vorhersagen über die Fortführung von Handbewegungen Rall, Philipp; Bender, Nicolas Gesellschaft für Informatik e.V. Die vorliegende Arbeit befasst sich mit der Entwicklung einer Methode zur Echtzeit-Vorhersage von Trajektorien seitlicher Greifbewegungen zur Kollisionsvermeidung in der kollaborativen Robotik. Ein Neuronales Netz sagt hierfür anhand des Verlaufs der Anfangsbewegung in einem Regressionsansatz die Endposition und Dauer des gesamten Greifvorgangs voraus. Durch das Minimum Jerk Model für gekrümmte Punkt-zu-Punkt-Bewegungen lässt sich daraufhin der weitere Verlauf der Trajektorie präzise berechnen. Die Arbeit legt besonderen Fokus auf die Entwicklung einer automatisierten Pipeline zur Datenvorverarbeitung, die aufgenommene Rohdaten von natürlichen Greifbewegungen in mehreren modularen Verarbeitungsphasen zur qualitativ hochwertigen und vereinheitlichten Trainingsdaten transformiert sowie fehlerbehaftete Messdaten aussortiert. Sat, 01 Jan 2022 00:00:00 GMT http://dl.gi.de/handle/20.500.12116/40240 2022-01-01T00:00:00Z