9,178 research outputs found

    Towards Identifying and closing Gaps in Assurance of autonomous Road vehicleS - a collection of Technical Notes Part 1

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    This report provides an introduction and overview of the Technical Topic Notes (TTNs) produced in the Towards Identifying and closing Gaps in Assurance of autonomous Road vehicleS (Tigars) project. These notes aim to support the development and evaluation of autonomous vehicles. Part 1 addresses: Assurance-overview and issues, Resilience and Safety Requirements, Open Systems Perspective and Formal Verification and Static Analysis of ML Systems. Part 2: Simulation and Dynamic Testing, Defence in Depth and Diversity, Security-Informed Safety Analysis, Standards and Guidelines

    An evaluation of NASA's program in human factors research: Aircrew-vehicle system interaction

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    Research in human factors in the aircraft cockpit and a proposed program augmentation were reviewed. The dramatic growth of microprocessor technology makes it entirely feasible to automate increasingly more functions in the aircraft cockpit; the promise of improved vehicle performance, efficiency, and safety through automation makes highly automated flight inevitable. An organized data base and validated methodology for predicting the effects of automation on human performance and thus on safety are lacking and without such a data base and validated methodology for analyzing human performance, increased automation may introduce new risks. Efforts should be concentrated on developing methods and techniques for analyzing man machine interactions, including human workload and prediction of performance

    Infrastructure networks and the competitiveness of the economy

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    This paper aims to examine how technical infrastructure networks may contribute to improving the competitiveness of the Hungarian economy. Consequently, our main question will be to establish how certain networks or sectors can promote competitiveness of the entire economy rather than how they could be more competitive in their own field. In the macroeconomic or regional sense competitiveness is interpreted as the entirety of safeguards and preconditions that provide a long term basis for success in a competitive market environment. The review of the economic, social, institutional and facility preconditions of competitiveness has highlighted that practically every component must be backed by a good system of relations: both strong, balanced internal relations promoting co-operation and external relations to assure outward linkages. Despite the above correlation, it would be a fallacy to assume that infrastructure networks as linking elements in general are factors per se improving competitiveness. In accordance with the level of development of the economy, the key forms of activity and the realistically attainable objectives, different linkages and service needs become key for the development of the economy in different stages

    Safe Reinforcement Learning for Sepsis Treatment

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    Sepsis, a life-threatening illness, is estimated to be the primary cause of death for 50,000 people a year in the UK and many more worldwide. Managing the treatment of sepsis is very challenging as it is frequently missed, at an early stage, and the optimal treatment is not yet clear. There are promising attempts to use Reinforcement Learning (RL) to learn the optimal strategy to treat sepsis patients, especially for the administration of intravenous fluids and vasopressors. However, RL agents only take the current state of patients into account when recommending the dosage of vasopressors. This is inconsistent with current clinical safety practice in which the dosage of vasopressors is increased or decreased gradually. A sudden major change of the dosage might cause significant harm to patients and as such is considered unsafe in sepsis treatment. In this paper, we have adapted one of the deep RL methods published previously and evaluated it to assess whether it has this kind of sudden major change when recommending the vasopressor dosage. Then, we have modified this method to address the above safety constraint and learnt a safer policy by incorporating current clinical knowledge and practice
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