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Predicting module-lattice reduction
Get PDFIs module-lattice reduction better than unstructured lattice reduction? This question was highlighted as 'Q8' in the Kyber NIST standardization submission (Avanzi et al., 2021), as potentially affecting the concrete security of Kyber and other module-lattice-based schemes. Foundational works on module-lattice reduction (Lee, Pellet-Mary, Stehlé, and Wallet, ASIACRYPT 2019; Mukherjee and Stephens-Davidowitz, CRYPTO 2020) confirmed the existence of such module variants of LLL and block-reduction algorithms, but focus only on provable worst-case asymptotic behavior. In this work, we present a concrete average-case analysis of modulelattice reduction. Specifically, we address the question of the expected slope after running module-BKZ, and pinpoint the discriminant of the number field at hand as the main quantity driving this slope. We convert this back into a gain or loss on the blocksize : module-BKZ in a number field of degree requires an SVP oracle of dimension to reach the same slope as unstructured BKZ with blocksize . This asymptotic summary hides further terms that we predict concretely using experimentally verified heuristics. Incidentally, we provide the first open-source implementation of moduleBKZ for some cyclotomic fields. For power-of-two cyclotomic fields, we have , and conclude that module-BKZ requires a blocksize larger than its unstructured counterpart by . On the contrary, for all other cyclotomic fields we have , so module-BKZ provides a sublinear gain on therequired blocksize, yielding a subexponential speedup of
Improving access to intermediate care through flexibility: Simulation study
Get PDFObjective Growing demand for intermediate care, combined with nurse shortages, is increasing the pressure on the accessibility of these services. This study uses simulation as an innovative approach to assess the effectiveness of policy interventions on waiting times and hospital admissions, aiming to identify strategies that better meet rising care demands and improve accessibility. Design A discrete-event simulation study modeling patient flows in intermediate care facilities. Setting and Participants The simulation model incorporates insights from health care professionals to represent patient flows, admissions, bed capacities, and operational constraints across both intermediate care and hospital settings. Methods The simulation model incorporates patient arrivals, admissions, and discharges within intermediate care. The study evaluates the impact of the following interventions on patient flow and accessibility: bed pooling between care types, flexible admission hours and transfer times, and the use of emergency beds. Results Partial bed pooling (10%) between high-complex and geriatric rehabilitation beds reduces waiting times by more than 1 day (a 25% to 42% reduction). Currently, average waiting times are approximately 2 days for low-complex care, and around 4 days for both high-complex care and geriatric rehabilitation. Expanding admission hours, particularly with 24/7 availability, decreases waiting times and hospital congestion. Eliminating emergency beds increases hospital admissions by 18%. By implementing multiple interventions, such as bed pooling and 24/7 admissions, accessibility shows the greatest improvement, with waiting times for high-complex patients reduced by more than 2 days (a 60% reduction) and decreased hospital admissions by 60%. Conclusion and Implications This study illustrates that access to intermediate care can be improved through bed pooling, flexible admission hours and transfer times, and the use of emergency beds, without the need to expand bed capacity. The results demonstrate that these interventions can optimize patient flow, reduce hospital admissions, and enhance overall system efficiency. Furthermore, the study demonstrates that simulation models are valuable tools for exploring policy and system changes within intermediate care settings
Fashion beneath the skin - a fashion exhibition experience in social virtual reality
Get PDFSocial VR allows users to interact with each other and explore virtual spaces together. This demo presents a social VR fashion museum, where visitors engage with fashion artefacts. The experience spans across three different spaces designed for various goals. This application, created following a human-centred approach, explores how the visitors interact with each other and the exhibits, considering their 3D volumetric representation and changing environmental context throughout the experience
Effect of fire department response time on fire damage in the Netherlands
No full textFire department response times are often used as a measure of their performance, even though its influence on the outcome is not well understood. In this study, we investigate the effect of the response time on the final damage to a building after a fire. We use a partial proportional odds model to measure how one extra minute of response time influences the probability of the damage exceeding a certain threshold, using data on building fires in the Netherlands from 2018 to 2022. Our results show that the probability of large damage increases almost linearly with the response time. As a rule of thumb, the probability of large damage increases with an average of 1% with each additional minute of response time. Furthermore, to minimize the probability of total loss each minute after a response time of about 10 min becomes increasingly more valuable
Art de Blaauw, CIO Rijk: 'We stellen steeds beter prioriteiten op digitaal gebied' - Dutch IT Leaders - 11-02-2025
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Zes toonaangevende projecten in Imaging Technologies gehonoreerd binnen NWO HTSM Call - linkmagazine - 09-05-2025
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Spatio-temporal point process models for interval-censored data
Get PDFIn this thesis, we develop a number of statistical frameworks within which interval-censored data can be modelled. By interval-censored data, we refer to data in which events can be partially observed in the form of temporal intervals, instead of being fully observed as simply a point in time and space. The base statistical model consists of two separate stochastic processes. One is responsible for the interval censoring mechanism, whereas the other process is a point process modelling the behaviour of the underlying stochastic process responsible for the event times. We blend approaches from stochastic processes, point process theory and measure theory to develop rigorous theoretical and modelling frameworks for temporal data. The spatial location of a point may also play a significant role in modelling, and in many cases, the geometry of the spatial component of the data is quite complex. We extend the underlying point process to take values on Euclidean graphs, and develop robust simulation and parameter estimation methods for this complex spatio-temporal model. The developed statistical theory has significant potential to be applied in the field of criminology, as both burglaries and arson fires are often only partially observed and recorded by victims and law enforcement. Models developed in this thesis are applied to a number of simulated and real-life data sets, with the full spatio-temporal model being applied to a car arson fire data set in Enschede
