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Forschen und Forschung in Kontexten des Alter(n)s mit Ausblicken für die Soziale Arbeit: eine Hinführung
Organisation der Altenhilfe nach § 71 SGB XII und die Bedeutung der Sozialen Arbeit: Erkenntnisse aus einem gerontologischen Gutachten mit dem Fokus auf Einzelleistungen
Development and Evaluation of an Immersive Virtual Reality Application for Road Crossing Training in Older Adults
Background/Objectives: Aging is often accompanied by physical and cognitive decline, affecting older adults’ mobility. Virtual reality (VR) offers innovative opportunities to safely practice everyday tasks, such as street crossing. This study was designed as a feasibility and pilot study to explore acceptance, usability, and preliminary effects of a VR-based road-crossing intervention for older adults. It investigates the use of virtual reality (VR) as an innovative training tool to support senior citizens in safely navigating everyday challenges such as crossing roads. By providing an immersive environment with realistic traffic scenarios, VR enables participants to practice in a safe and controlled setting, minimizing the risks associated with real-world road traffic. Methods: A VR training application called “Wegfest” was developed to facilitate targeted road-crossing practice. The application simulates various scenarios commonly encountered by older adults, such as crossing busy streets or waiting at traffic lights. The study applied a single-group pre-post design. Outcomes included the Timed Up and Go test (TUG), Falls Efficacy Scale-International (FES-I), and Montreal Cognitive Assessment (MoCA). Results: The development process of “Wegfest” demonstrates how a highly realistic street environment can be created for VR-based road-crossing training. Significant improvements were found in the Timed Up and Go test (p = 0.002, d = 0.784) and fall-related self-efficacy (FES-I, p = 0.005). No change was observed in cognitive function (MoCA, p = 0.56). Participants reported increased subjective safety (p < 0.001). Discussion: The development of the VR training application “Wegfest” highlights the feasibility of creating realistic virtual environments for skill development. By leveraging immersive technology, both physical and cognitive skills required for road-crossing can be effectively trained. The findings suggest that “Wegfest” has the potential to enhance the mobility and safety of older adults in road traffic through immersive experiences and targeted training interventions. Conclusions: As an innovative training tool, the VR application not only provides an engaging and enjoyable learning environment but also fosters self-confidence and independence among older adults in traffic settings. Regular training within the virtual world enables senior citizens to continuously refine their skills, ultimately improving their quality of life
Qualität in Ganztagsgrundschulen – neue empirische Erkenntnisse
Die vorliegende Studie untersucht den Einfluss und die Effekte der pädagogische Prozessqualität im Ganztag (Autonomie, Interesse und Beziehungsqualität) auf das schulische Wohlbefinden von 800 Drittklässler*innen an 31 Düsseldorfer Grundschulen im Rahmen des Projekts „Zukunft des Ganztags an Düsseldorfer Grundschulen“. Ergebnisse zeigen, dass die sozialräumliche Verortung der Schulen (gemessen über den Sozialindex NRW) keinen Einfluss auf die Prozessqualität im Ganztag (gemessen über Autonomie, das Interesse an Ganztagsangeboten und der Beziehung zu Betreuungspersonen) hat. Vertiefende Mehrebenenanalysen zeigen, dass insbesondere das Interesse an den Ganztagsangeboten und die Beziehungsqualität signifikant zum schulischen Wohlbefinden beitragen, während die Autonomie keinen signifikanten Einfluss aufweist. Mädchen zeigten ein höheres Interesse an Ganztagsangeboten als Jungen. Ein höherer Sozialindex ist mit geringerem Wohlbefinden assoziiert. Diese Ergebnisse unterstreichen die zentrale Bedeutung des Sozialraums und der Prozessqualität für das Wohlbefinden der Schüler*innen im Ganztag
Automated leaders and followers selection in Stackelberg games for modular manufacturing systems
We propose an automated data-driven mechanism to evaluate each actuator’s influence on modular manufacturing system objectives. This mechanism enables automated leader and follower selection in Stackelberg games, which have gained traction in engineering. While leaders typically hold greater priority or influence, systematic methods for assigning leaders and followers remain limited, especially in large-scale applications. As a result, many rely on empirical analysis to assign leaders and followers, without confirming if the selected setup is optimal. Therefore, in this paper, we develop an automated mechanism to evaluate the influence of each player on the global objectives of modular manufacturing systems, applicable to both single- and multi-objective scenarios. We validate the proposed approach within an industrial control scenario, using a modular Bulk Good System and its larger-scale arrangement with sequential and serial-parallel processes. We focus on three objectives, including production flow disruption prevention, power consumption reduction, and production demand fulfilment. Finally, we implement a self-learning algorithm utilizing Modular State-based Stackelberg Games, where leaders and followers are selected using our approach, which leads to encouraging results