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The variation of the contact impedance of adhesive conductive EMI shielding tapes under high temperature storage (HTS) of 110degC is investigated. The adhesive tapes under test are implemented as signal return paths in microstrip lines. Changes in the ground plane impedance by adhesive deterioration are analyzed by S-parameter measurements from 1MHz to 3GHz. A circuit model for contact impedance degradation is proposed and applied in simulation of board level shielding. Contact resistance and contact capacitance are found to increase significantly after 2400h, causing a declined magnetic field shielding effectiveness by 30 dB below 500 MHz.
We present inductive power transfer (IPT) with a half-bridge converter based on differential relaxation self-oscillation. The oscillation dynamics of the converter automatically adapts to variation in the inductive coupling link and changes in the load, respectively. Design equations based on theoretical circuit analysis reveals a high power transfer efficiency (>90%) for alteration of coupling distance in the strong coupling regime. A prototype system employing GaN-HEMTs confirms the theoretically predicted characteristics of the proposed circuit.
Non-Rest to non-Rest Reference Slews for Agile Imaging Satellites With LQ-minimized Angular Momentum
(2023)
This paper shows a full parametrization non-rest to non-rest slew maneuvers using polynomials. A new modelling formulation is developed which on one hand satisfies exactly the given boundary conditions as well as the kinematic differential equation of the rotating body exactly. The idea is to determine one part of the unknown coefficients by the kinematical boundary conditions and to use the other part as free design parameters to shape the dynamic in between the boundary conditions. In addition, a least squares problem is formulated in order to minimize the angular momentum of the slew. This approach allows optimal slew maneuvers as well as low computational need such that an onboard usage is possible.
SMEs are increasingly forced to shift to more sustainable manufacturing. Industry 4.0 can support the transformation and foster innovation. But, SMEs need solutions with a low barrier to entry in terms of investment, IT knowledge and capacities. A framework based on value and material flow analysis, low investments and user-oriented IT skills is proposed. As an example, it is implemented in the furniture industry and shows a digital twin in terms of monitoring the energy and material flows. In addition, a product-specific allocation of energy consumption, energy peak shaving and other applications are possible.
Psychological safety, the feeling of being comfortable to express one’s ideas or opinions in teams, is a key determinant of successful global virtual teams. Even though there exists considerable knowledge about its antecedents, it is unknown how team-based (e.g., clarification of deliverables and deadlines) and technology-based (e.g., digital reminder nudges/ DRN) interventions foster psychological safety given cultural variations of team members. Based on a survey involving 148 participants, our data shows that both team-based interventions (TBI) and digital nudges foster psychological safety in global virtual teams. TBI are even more effective for high-context, indirect communicators than for low-context, direct communicators. However, digital nudges were equally effective across cultures for building psychological safety. These findings contribute to the literature on psychological safety as we show that not all antecedents hold equally across cultures and to the literature of digital nudges as we show the effectiveness of technology-based interventions in a team context.
Holz ist eine der wichtigsten erneuerbaren Ressourcen und kann recycelt werden, wobei derzeit nur unbehandeltes Holz in mehreren Lebenszyklen verwendet werden kann. Allerdings werden in Altholzsortieranlagen meist behandeltes und unbehandeltes Altholz gemischt angeliefert und es gibt keine automatische Klassifizierung zur sortenreinen Sortierung. Frühere Studien zeigen, dass behandelte und unbehandelte Holzproben mit Hilfe von bildgebender Fluoreszenzabklingzeit Mikroskopie unterschieden werden können. Um den Prozess der Klassifizierung von Altholz anhand von Fluoreszenzabklingzeitbildern zu automatisieren, werden zwei neuronale Netzwerke (NN) evaluiert. Das erste NN ist ein MLP (Multi Layer Perceptron), das das Altholz anhand von Erwartungswert und Standardabweichung eines Fluoreszenzabklingzeitbildes klassifiziert. Das zweite untersuchte NN ist ein CNN (Convolutional Neural Network), das das Holz direkt anhand der Fluoreszenzabklingzeitbilder klassifiziert. Beide Netzwerke sind in Python implementiert, um die spätere Verwendung in einem automatischen Klassifizierungs- und Sortierprozess zu erleichtern. Die Evaluation der NN zeigt vielversprechende Ergebnisse zur automatisierten Klassifikation von Altholz.
One major problem of a continuous process like plastic extrusion is their incapability to deal with non-local gas pressure. This is an inherent problem because a continuous process has an open end in the feeding port where pressure can escape. In this study a novel feeding system was developed to enable granulate feeding into gas pressurized processes inside a single- or twin-screw extruder. With this apparatus gas pressure can be applied inside the extrusion process. The apparatus separates the pressurized extruder from the dosing equipment that feeds the extruder. It keeps the pressure inside the system while continuously feeding new material into the process. A small-scale prototype was designed for proof-of concept. The small size of the prototype was able to handle small amounts of granulates of around 100 - 200 g/h. An applied gas pressure of 8 bar was achieved. In future optimizations, throughput can be increased and maximum applied gas pressure towards 15-20 bar.
The pandemic has highlighted the fact that healthcare systems around the world are under pressure. Demographic change is leading to an increasing shortage of care workers in most countries, and the demographic challenge is only just beginning in most societies. While robots are widely used in industry, robotic support in healthcare is still limited to very specialised robots in the operating theatre. The question of what type of deployment is likely to be successful in a healthcare scenario is not only a technological or economical question, but also one of technology acceptance.
In this paper we analyse the acceptance of robots in elderly care from the perspective of patients, patient families, and geriatric care professionals. To understand the various positions and to identify the suitability of existing acceptance models, we applied stakeholder mapping to conduct qualitative interviews with 14 people with different knowledge backgrounds and levels of involvement in care situations, based on 9 videos showing different robots and application scenarios.
The results confirmed that existing technology acceptance models need to be extended by factors such as robot appear-ance. We found that the background knowledge of the respondents influences the results of the questions about e.g. safety concerns. In addition, we found that the contribution to patients' self-determination and independence is an im-portant factor that is not included in existing technology acceptance models. Finally, the discovery of a significant dis-crepancy between the self-perception and the external perception of the different stakeholders regarding the acceptance of a service robot can be explained by the stakeholder positions involved caring for the benefit of a specific patient.
These findings encourage further research, especially with the underlying assumption that technology acceptance in healthcare is not just a patient issue, but a stakeholder issue. Stake holder mapping is a valid tool to analyze the inter-dependences for acceptance of robots. Therefore, we suggest using a tool such as stakeholder mapping to further ana-lyze these issues.