From the article: The ethics guidelines put forward by the AI High Level Expert Group (AI-HLEG) present a list of seven key requirements that Human-centered, trustworthy AI systems should meet. These guidelines are useful for the evaluation of AI systems, but can be complemented by applied methods and tools for the development of trustworthy AI systems in practice. In this position paper we propose a framework for translating the AI-HLEG ethics guidelines into the specific context within which an AI system operates. This approach aligns well with a set of Agile principles commonly employed in software engineering. http://ceur-ws.org/Vol-2659/
Due to the changing technological possibilities of services, the demands that society places on the level of service provided by the Dutch Central Government (DCG) are changing rapidly. To accommodate this, the Dutch government is improving its processes in such a way that they become more agile and are continuously improved. However, the DCG struggles with the implementation of improvement tools that can support this. The research described in this paper aims to deliver key factors that influence the adoption of tools that improve the agile way of working and continuous improvement at the DCG. Therefore, a literature review has been conducted, from which 24 factors have been derived. Subsequently, 9 semi structured interviews have been conducted to emphasize the perspective of employees at the DCG. In total, 7 key factors have been derived from the interviews. The interviewees consisted of both employees from departments who already worked with tools to improve agile working and continuous improvement as well as employees from departments who haven’t used such tools yet. An important insight based on this research is that the aims, way of working and scope of the improvement tools must be clear for all the involved co-workers
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Physical and psychosocial stress and recovery are important performance determinants. A holistic approach that monitors these performance determinants over a longer period of time is lacking. Therefore this study aims to investigate the effect of a player’s physical and psychosocial stress and recovery on field-test performance. In a prospective non-experimental cohort design 10 female Dutch floorball players were monitored over 6 months. To monitor physical and psychosocial stress and recovery, daily training-logs and three-weekly the Recovery-Stress Questionnaire for Athletes (RESTQ-Sport) were filled out respectively. To determine field-test performance 6 Heart rate Interval Monitoring System (HIMS) and 4 Repeated Modified Agility T-test (RMAT) measurements were performed. Multilevel prediction models were applied to account for within-players and between-players field-test performance changes. The results show that more psychosocial stress and less psychosocial recovery over 3 to 6 weeks before testing decrease HIMS performance (p≤0.05). More physical stress over 6 weeks before testing improves RMAT performance (p≤0.05). In conclusion, physical and psychosocial stress and recovery affect submaximal interval-based running performance and agility up to 6 weeks before testing. Therefore both physical and psychosocial stress and recovery should be monitored in daily routines to optimize performance.
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Agricultural/horticultural products account for 9% of Dutch gross domestic product. Yearly expansion of production involves major challenges concerning labour costs and plant health control. For growers, one of the most urgent problems is pest detection, as pests cause up to 10% harvest loss, while the use of chemicals is increasingly prohibited. For consumers, food safety is increasingly important. A potential solution for both challenges is frequent and automated pest monitoring. Although technological developments such as propeller-based drones and robotic arms are in full swing, these are not suitable for vertical horticulture (e.g. tomatoes, cucumbers). A better solution for less labour intensive pest detection in vertical crop horticulture, is a bio-inspired FW-MAV: Flapping Wings Micro Aerial Vehicle. Within this project we will develop tiny FW-MAVs inspired by insect agility, with high manoeuvrability for close plant inspection, even through leaves without damage. This project focusses on technical design, testing and prototyping of FW-MAV and on autonomous flight through vertically growing crops in greenhouses. The three biggest technical challenges for FW-MAV development are: 1) size, lower flight speed and hovering; 2) Flight time; and 3) Energy efficiency. The greenhouse environment and pest detection functionality pose additional challenges such as autonomous flight, high manoeuvrability, vertical take-off/landing, payload of sensors and other equipment. All of this is a multidisciplinary challenge requiring cross-domain collaboration between several partners, such as growers, biologists, entomologists and engineers with expertise in robotics, mechanics, aerodynamics, electronics, etc. In this project a co-creation based collaboration is established with all stakeholders involved, integrating technical and biological aspects.
Due to the exponential growth of ecommerce, the need for automated Inventory management is crucial to have, among others, up-to-date information. There have been recent developments in using drones equipped with RGB cameras for scanning and counting inventories in warehouse. Due to their unlimited reach, agility and speed, drones can speed up the inventory process and keep it actual. To benefit from this drone technology, warehouse owners and inventory service providers are actively exploring ways for maximizing the utilization of this technology through extending its capability in long-term autonomy, collaboration and operation in night and weekends. This feasibility study is aimed at investigating the possibility of developing a robust, reliable and resilient group of aerial robots with long-term autonomy as part of effectively automating warehouse inventory system to have competitive advantage in highly dynamic and competitive market. To that end, the main research question is, “Which technologies need to be further developed to enable collaborative drones with long-term autonomy to conduct warehouse inventory at night and in the weekends?” This research focusses on user requirement analysis, complete system architecting including functional decomposition, concept development, technology selection, proof-of-concept demonstrator development and compiling a follow-up projects.
The project is for protecting valuable museum contents against seismic actions. Assessment and protection methods and equipment will be developed and tested. - Assessment methods for seismic safety of museum contents- Protective devices for the musem contentsA museum virtual exhibition room (MVER) will be created, it will contain exhibits such as sculptures and artefacts of different size and geometry, while the proposed experimental work will first examine the seismic behaviour of the test specimens without any protection system. The tests will be repeated using different protective configurations, emphasising on low-mass base isolation systems. Two new and highly efficient base isolation systems will be extensively tested for the first time. The first isolator is a pendulum-based system, while the second utilises shape-memory-alloy wires.The project will also develop and calibrate novel numerical models for single- and two- block rocking systems, while experimental and numerical results will be combined in order to develop quick overturning assessment criteria for the artefacts considered.The final task of the project will combine the shaking table experimental outcomes with numerical results using calibrated numerical models in order to develop fragility curves for museum artefacts.
