Refine
Year of publication
Document Type
- Master's Thesis (484)
- Article (483)
- Conference Proceeding (424)
- Part of a Book (233)
- Book (107)
- Report (29)
- Other (18)
- Doctoral Thesis (14)
- Working Paper (10)
- Preprint (5)
Institute
- Wirtschaft (358)
- Forschungszentrum Mikrotechnik (265)
- Technik | Engineering & Technology (197)
- Forschungszentrum Business Informatics (176)
- Department of Computer Science (Ende 2021 aufgelöst; Integration in die übergeordnete OE Technik) (164)
- Soziales & Gesundheit (151)
- Forschungsgruppe Empirische Sozialwissenschaften (120)
- Forschungszentrum Human Centred Technologies (107)
- Forschungszentrum Energie (96)
- Didaktik (mit 31.03.2021 aufgelöst; Integration ins TELL Center) (68)
Keywords
- Social Work (18)
- Organizational Studies, Economic Sociology (17)
- Social Structure, Social Inequality (17)
- Soziale Arbeit (16)
- Digitalisierung (14)
- arrayed waveguide gratings (13)
- Controlling (11)
- Laser ablation (11)
- Y-branch splitter (11)
- +KDC 122 (9)
This paper investigates restart strategies for algorithms whose success depends on an algorithmic parameter λ. It is assumed that there exists a unique unknown optimal λ. After each restart λ is increased. The main question is whether there is an optimal strategy for choosing λ after each restart. To this end, possible restart strategies are classified into parameter-dependent strategy types. A loss function is introduced, that measures the wasted computational costs compared to the optimal strategy. One criterion that a viable restart strategy must satisfy is that the loss relative to the optimal λ is bounded. Experimental evidence demonstrates that this is not the case for all strategy types. However, for a specific strategy type, where the parameter λ is increased multiplicatively with an increasing constant ρ, the relative loss function has an upper bound. It will be shown, that for this strategy type there is an optimal choice for the parameter ρ that is independent of the optimal λ.
The role of leaders in the age of digital transformation is characterized by complexity and ambiguity. Consequently, leadership finds itself at a crossroads where hierarchy no longer seems to be the path to success. On the one hand, employees desire more autonomy and participation. On the other hand, leaders are compelled to relinquish and distribute power. Therefore, new directions and contemporary concepts are necessary, ones that enable non-hierarchical organizational and leadership models that go beyond the traditional Great Man Theory, which focuses on a single leader. In this vein, shared leadership emerges as an alternative to hierarchical leadership, emphasizing not the individual leader but the skills and expertise of all team members. Therefore, this approach relieves the formal leader and allows for the distribution of responsibilities. Indeed, this raises the question of the relevance of the formal leader in a team with shared leadership. Which role does the formal leader play in a shared leadership team? Drawing on a qualitative study this paper identifies personality, leadership mindset, and leadership tasks as main leadership categories, and uncovers the four leadership types enabler, connector, ambassador, and organizer. Adding to the leadership-as-practice literature (Alvehus, 2019; Raelin, 2018), our findings contribute to the development of shared leadership programs.
Machines and other driving components like compressors or fans usually generate vibrations which frequently lead to acoustic noise. Flexible structures equipped with acoustic black holes minimise acoustic radiation by confining structural vibrations locally. One main restriction of its usage in the broad engineering field is its limited effectiveness at low frequencies. Recent investigations shifted the frequency range of attenuation successfully down to 1500 Hz. Moving the existing designs towards an even lower frequency demands a large structure. However, in general, sufficient space is often not available in machines and facilities. We propose a new design that enables a geometrically compact and simultaneously broadband vibration attenuation in the low-frequency below to 100 Hz: stacked wedges. The proposed design is calculated and optimised numerically by combining CAD and finite element calculations. The influence of geometrical parameters on the effectiveness of vibration attenuation is analysed with the help of transfer functions and dispersion curves. Successful designs of multi-stacked wedges at different lengths confirm their effectiveness at low frequency.
Introduction: Acoustic black holes (ABH) are capable to mitigate structural vibrations efficiently above a certain cut-on frequency. The most commonly used geometry for a flexible beam is a simple wedge following a power-law curve. A simple wedge demands large dimensions for achieving mitigation in the low-frequency range below 1000 Hz. It was shown recently by experiments and numerical simulation that a multi-wedge configuration is beneficial for realizing a compact design and still showing good performance at low frequencies.
Materials and Methods: The WKB approximation is extended for a single-wedge design. Expressions for the reflection coefficient and cut-on frequency are discussed for an arbitrary number of wedges—the suggested multi-wedge ABH.
Results: The main benefit of the stacked multi-wedge ABH is a great improvement in performance in the low-frequency range. A numerical example highlights the successful vibration mitigation. It is shown how a multi-wedge ABH is tuned towards low-frequency in terms of cut-on frequency and reflections’ coefficient. The improved performance of a multi-wedge ABH is benchmarked against the well-established simple ABH.
Noise from machine vibrations and oscillations is a growing problem in today’s society. The use of acoustic black holes (ABH) in the area of passive vibration damping as an absorbing metamaterial is an active research field. Previous work has been successful mainly in the higher frequency range above 1500 Hz. This work aims at vibration damping in the lower frequency range below 1500 Hz. Here, additively manufactured multi-wedge ABH with two, three, four and ten wedges were welded to a beam structure and measured to estimate which number of wedges produces the best damping for a specific frequency range. The manufactured wedges largely absorbed a vast amount of the vibration energy induced into the structure and showed promising results. It was found that the more wedges were welded to the beam, the more natural frequencies occurred in the low frequency range. In the case of the ABH with ten wedges, ten eigenmodes were detected in this range, all of which absorbed the induced vibration energy effectively in the low frequency range.
Organizations are increasingly opting to use decision-making systems based on artificial intelligence (AI) to increase decision quality and speed and free up resources. However, delegating decisions to AI is challenging, especially in contexts that go beyond classical optimization problems. Current research has so far largely neglected to include the viewpoints of the decision-affected and of surrogate decision-makers in the discussion. To address these gaps, in this study we rely on two experimental designs and complement our findings with qualitative interview data to shed light on both sides: the perspective of those affected by the decision and that of the decision maker in surrogate and ethically complex decision contexts. Findings reveal that the individual decision-making perspective may lead to opposing perceptions. Whereas the willingness to delegate an ethically challenging decision to AI in a surrogate decision context is lower than that in a non-surrogate context (decision-maker perspective), people affected by the decision do not generally prefer humans to AI (decision-affected perspective). By these findings, we contribute to the literature on AI-enabled decision-making and decision delegation to non-human entities.
Hintergrund: Menschen mit Migrationsbiografie bzw. mit besonderen sozio-kulturellen Bedürfnissen finden erschwert den Zugang zu Gesundheitsdienstleistungen bzw. sind von einer Über-, Unter- oder Fehlversorgung betroffen. Durch Community Nursing (CN) kann die Gesundheitskompetenz gestärkt werden. Ein solches Angebot wurde im Jahr 2022 in einer Gemeinde in Österreich implementiert. Ziel: Das Ziel war eine Analyse des Bedarfs und der aktuellen Akzeptanz von CN durch Menschen mit Migrationsbiografie sowie die Identifikation von adäquaten Maßnahmen zur Förderung der Inanspruchnahme. Methodik: Im März 2023 wurden in einer österreichischen Gemeinde in Vorarlberg im Rahmen einer Bedarfs- und Akzeptanzanalyse zwei Fokusgruppeninterviews mit Stakeholdern sowie Adressat_innen betreffend der Nutzung des CN-Angebots durchgeführt, inhaltsanalytisch ausgewertet und in Workshops validiert. Ergebnisse: Vielfältige Barrieren (fehlende Sprachkompetenz, Unwissenheit bzgl. Versicherungsschutz, fehlende Informationen zu CN, gefühlsbezogene hemmende Faktoren wie Angst, Scham und Vorbehalte gegenüber Pflegeangeboten) konnten identifiziert werden. Die gemeinsam erarbeiteten Lösungsansätze für ein niederschwelliges Angebot reichen vom Einsatz von Schlüsselpersonen über Gesundheitsberatung in Begegnungscafés bis hin zu einer gezielten Informationsstrategie. Schlussfolgerungen: Ein erfolgreiches CN-Angebot erfordert eine umfassende Implementierungsstrategie und bedarfsgerechte Maßnahmen. Die sichtbar gewordenen Barrieren, Ängste und Vorbehalte sollten berücksichtigt werden, um den Zugang zum CN für Menschen mit Migrationsbiografie zu erleichtern.
