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Advances in eye-tracking control for assistive robotic arms provide intuitive interaction opportunities for people with physical disabilities. Shared control has gained interest in recent years by improving user satisfaction through partial automation of robot control. We present an eye-tracking-guided shared control design based on insights from state-of-the-art literature. A Wizard of Oz setup was used in which automation was simulated by an experimenter to evaluate the concept without requiring full implementation. This approach allowed for rapid exploration of user needs and expectations to inform future iterations. Two studies were conducted to assess user experience, identify design challenges, and find improvements to ensure usability and accessibility. The first study involved people with disabilities by providing a survey, and the second study used the Wizard of Oz design in person to gain technical insights, leading to a comprehensive picture of findings.
A failure model for SFRP for FEM simulations is developed to describe the strain rate dependency, the influence of the local fiber orientation and of the stress state on the failure behavior. The material is considered as a continuum while internally calculating the micro-mechanics analytically. The described micro-mechanics are based on experimental observations and on analyzation with numerical studies. In particular the strain rate dependent delamination of fibers and matrix is incorporated in the model. The distortion energy density is defined as the driving value for failure and estimated by the model. This is achieved with the analytic solution by Eshelby for the stress field in the matrix and by introducing an additional phase for the plasticly deformed volume. The validation on characterization specimens as well as component test demonstrates that the influence of strain rate, fiber orientation, and stress state on the failure behavior can be described with only one material parameter, the critical distortion energy density.
For predicting the strain rate dependent failure of short fiber reinforced plastics (SFRP) a two-phase simulation model is developed using the finite element method and comparing the results to microscopic specimen tests for uniaxial tension under quasi-static (0.007/s) and dynamic loads (250/s). Experimentally the failure behavior of SFRP is observed to be strain rate dependent. The global strain at failure and the absorbed energy increase with strain rate. Moreover, locally an influence of the strain rate on the amount of material involved in the deformation can be observed. The suggested model can represent these effects accurately. Also, the present micro-mechanical effects and their influence on the strain distribution are investigated by unit cell simulations. Thereby the material model of the fibers, the matrix, and the boundary layer are varied respectively. These reveal the important role of strain rate dependent decohesion leading to a correct representation of the plastically deformed volume. Consequently, the distortion energy density is evaluated and is found to be constant at failure for all strain rates.
The mechanical properties of fibre‐reinforced thermoplastics and their dependencies on the manufacturing process, fibre properties, fibre concentration and strain rate have been researched intensively for years in order to predict their macroscopic behaviour by numerical simulations as precisely as possible. Including the microstructure in both real and virtual experiments has improved prediction precision for injection‐moulded glass fibre‐reinforced thermoplastics significantly. In this work, we apply three established methods for characterisation and modelling to an injection‐moulded and to a 3D printed material. The geometric properties of the fibre component as fibre orientation, fibre length and fibre diameter distributions are identified by analysing reconstructed tomographic images. For comparing the fibre lengths, a recently suggested new method is applied. Based on segmentations of the tomographic images, we calculate the elastic stiffness of both composites numerically on the microscale. Finally, the mechanical behaviour of both materials is experimentally characterised by micro tensile tests. The simulation results agree well with the measured stiffness in case of the injection‐moulded material. However, for the 3D printed material, measurement and simulation differ strongly. The prediction from the simulation agrees with the values expected from the image analytic findings on the microstructure. Therefore, the differences in the measured behaviour have to be contributed to the matrix material. This proves demand for further research for 3D printed materials for predictable prototypes, preproduction series and possible serial application.
Im Rahmen der vorliegenden Bachelorarbeit werden verschiedene API- und Rendering-Technologien verglichen, um darauf aufbauend ein Konzept für eine Schnittstelle für das CMS "EDITH" der Web Commerce GmbH zu entwerfen.
Auf Basis dieses Konzepts soll dann ein Prototyp entwickelt werden. Ziel ist es, die derzeit serverseitig gerenderten Pflegemasken des CMS langfristig clientseitig zu generieren und so die Benutzerfreundlichkeit des CMS zu erhöhen und die Serverlast zu reduzieren.
3D-Druck einer Kesselpauke
(2025)
Diese Bachelorarbeit verfolgt das Ziel, die Machbarkeit der Herstellung eines Paukenkessels mittels 3D-Druck nachzuweisen.
Ein weiterer Aspekt dieser Arbeit ist die Untersuchung der Klangeigenschaften einer Kesselpauke mit einem 3D gedruckten Paukenkessel im Vergleich zu einer traditionell hergestellten Kesselpauke.
Diese Arbeit untersucht die Erfolgsfaktoren für die KI-Implementierung in KMUs der ländlich-industriell geprägten Region Schwarzwald-Baar-Heuberg (SBH). Trotz hohem Innovationspotenzial und Herausforderungen wie Fachkräftemangel nutzen KMUs KI-Chancen zur Effizienzsteigerung und Automatisierung nur zögerlich. Die zentrale Leitfrage lautet:
„Welche Erfolgsdeterminanten und deren Wechselwirkungen sind für die KI-Implementation in KMUs ländlicher Räume maßgeblich und wie lassen sich diese am Beispiel der Region Schwarzwald-Baar-Heuberg empirisch validieren?“
Basierend auf Literaturanalyse wurde das TOE-Framework um die regionale Dimension zum TOER-Framework (Technologie, Organisation, Wirtschaft, Region) erweitert. Ein Mixed-Methods-Ansatz kombinierte eine quantitative Umfrage mit qualitativen Interviews. Die geringe Stichprobengröße (trotz umfangreicher Bewerbung durch die IHK) schränkt die Repräsentativität stark ein; die Ergebnisse sind explorativ. Die niedrige Teilnahme deutet selbst auf Hürden hin (z.B. „KI-Müdigkeit“, Unsicherheit).
Wichtigste Ergebnisse (TOER):
• T: IT-Basis oft vorhanden, aber KI-spezifische Lücken (Datenmanagement, Hardware). Bedarf an passgenauen, sicheren, nutzerfreundlichen Lösungen; Kosten und Unsicherheit hemmen. Generative KI am populärsten.
• O: Führung oft unterstützend, aber Mitarbeiterakzeptanz, Kompetenzen und Change-Management sind Hauptbarrieren. Strategieanpassung langsam.
• E: Fokus auf Effizienz, kurze Amortisation (1-2 Jahre) erwartet, dennoch Investitionszurückhaltung. Systematische Erfolgsmessung fehlt meist.
• R: Fachkräftemangel kritischstes regionales Hemmnis. Unterstützungsangebote oft
unbekannt/unpassend. Netzwerke wichtig (v.a. für größere KMUs), aber wenig genutzt. Hoher Bedarf an Best Practices, individueller Beratung und Förderung. Hohe Kosten für externe Expertise als Hürde wahrgenommen.
Die Faktoren interagieren; Führung und regionale Netzwerke sind zentral, aber oft ungenutzt. Grundlegende Erfolgsfaktoren (Netzwerke, maßgeschneiderte Unterstützung, Führung) sind tendenziell auf andere Regionen übertragbar, erfordern ggf. regionale Anpassungen.
Zentrale Handlungsempfehlung:
Zur Überwindung der Hürden (v.a. Mangel an vertrauenswürdiger Expertise) wird die Initiierung eines regionalen „AI-ExpertHub SBH“ vorgeschlagen. Als Verbundprojekt (IHK, Hochschulen, Unternehmen) soll er Wissen bündeln, Unterstützung bieten, Qualität sichern, Best Practices fördern und Akteure vernetzen, um die KI-Adaption zu beschleunigen.
Social media has become an integral part of daily life for many individuals, serving as a platform for communication, information sharing, and entertainment. However, the extensive use of social media has led to issues such as information overload and social media fatigue, where users feel overwhelmed and emotionally exhausted by constant interaction and content. This paper investigates cognitive social media literacy skills—appraisal, comprehension, curation, and interaction—and their ability to mitigate perceived overload. Based on a quantitative study of 335 respondents, the results confirm that higher social media literacy reduces perceived information overload, but only the skill “appraisal” significantly lowers communication overload. The study highlights the critical role of social media literacy in reducing negative social media effects, offering practical insights for policymakers, educators, and platform developers to address social media fatigue.