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This paper discusses methods to test the performance of the adaptation layer in a self-adaptive system. The problem is notoriously hard, due to the high degree of uncertainty and variability inherent in an adaptive software application. In particular, providing any type of formal guarantee for this problem is extremely difficult. In this paper we propose the use of a rigorous probabilistic approac
Distributed camera surveillance systems typically consist of multiple cameras that need to store some fraction of their video streams in a central storage node. The disk space of this node as well as the network between the cameras and this central node constitute shared resources. In the paper the disk space allocation as well as the network bandwidth reservation are solved using techniques norma
Internal positivity offers a computationally cheap certificate for external (inputoutput) positivity of a linear time-invariant system. However, the drawback with this certificate lies in its realization dependency. First, computing such a realization requires finding a polyhedral cone with a potentially high number of extremal generators that lifts the dimension of the state-space representation,
Time-triggered real-time systems achieve deterministic behavior using schedules that are constructed offline, based on scheduling constraints. Their deterministic behavior makes time-triggered systems suitable for usage in safety-critical environments, like avionics. However, this determinism also allows attackers to fine-tune attacks that can be carried out after studying the behavior of the syst
Presents a new view of the standard of living development in Sweden during the agricultural revolution, using evidence on the ability to overcome short-term economic stress. The results corroborate previous findings, based on a variety of indicators, that standard of living in Sweden increased for most people after the mid-nineteenth century, but also support a more negative view of the immediate
Model Predictive Control (MPC) is an efficient point-to-point trajectory-generation method for robots that can be used in situations that occur under time constraints. The motion plan can be recalculated online to increase the accuracy of the trajectory when getting close to the goal position. We have implemented this strategy in a Franka Emika Panda robot, a redundant collaborative robot, by exte
Semialgebraic proof systems have been studied extensively in proof complexity since the late 1990s to understand the power of Gröbner basis computations, linear and semidefinite programming hierarchies, and other methods. Such proof systems are defined alternately with only the original variables of the problem and with special formal variables for positive and negative literals, but there seems t
This thesis deals with the general problem of controlling rigid-body systems through space, with a special focus on unmanned aerial vehicles (UAVs). Several promising UAV control algorithms have been developed over the past decades, enabling truly astounding feats of agility when combined with modern sensing technologies. However, these control algorithms typically come without global stability gu
Recurrent neural networks (RNNs) are efficient for classification of sequential data such as speech and audio due to their high precision on tasks. However, power efficiency, the required memory capacity and bandwidth requirements make them less suitable for battery powered devices. In this work, we introduce FLoPAD-GRU: a system on a chip (SoC) for efficient processing of gated recurrent unit (GR
There is a large variability between individuals in the response to anesthetic drugs, that seriously limits the achievable performance of closed-loop controlled drug dosing. Full individualization of patient models based on early clinical response data has been suggested as a means to improve performance with maintained robustness (safety). We use estimation theoretic analysis and realization theo
Vitamin D analogues are in clinical use for prevention and treatment of secondary hyperparathyroidism (HPT) in chronic renal failure. Despite recent advances there is a need for vitamin D derivatives with maintained parathyroid hormone suppressive activity and less hypercalcemic and hyperphosphatemic toxicity. Here we show coincident increased expression of the vitamin D activating enzyme 25-hydro
Numerous modelling efforts have attempted to characterize the effects of different non-pharmaceutical interventions (NPIs) on the Covid-19 spread. Arguably the most famous is one published in Nature by an Imperial College group. A slight variation of it was later published in Science by a group of Oxford researchers. Both publications are based on hierarchical Bayesian modelling that aims to expla
Novel methods for the inference of radiation intensityfunctions defined over known surfaces are proposed, intendedfor use in surveying applications with mobile spectrometers.Previous approaches, based on the maximum likelihoodexpectation maximization (ML-EM) framework with Poissonlikelihoods, are extended to better handle spatially continuousintensity statistics using ideas from Gaussian filtering
This article addresses the distributed cooperative control design for a class of sampled-data teleoperation systems with multiple slave mobile manipulators grasping an object in the presence of communication bandwidth limitation and time delays. Discrete-time information transmission with time-varying delays is assumed, and the Round-Robin (RR) scheduling protocol is used to regulate the data tran
A 32 Kb dual-port low-voltage SRAM in 28 nm FD-SOI, featuring foundry supplied high-density 6T bitcells, is presented. Dual-port configurability is realized by a unique dual-rail architecture, utilizing boost techniques that guarantee reliable operation in low-voltage. The area cost of the array is 62% lower, compared to widely used 8T two-port or dual-port SRAM arrays. The SRAM reliably operates
ControlSystems.jl enables the powerful features of the Julia language to be leveraged for control design and analysis.The toolbox provides types for state-space, transfer-function, and time-delay models, together with algorithms for design and analysis.Julia's mathematically-oriented syntax is convenient for implementing control algorithms, and its just-in-time compilation gives performance on par
In inverse optimal control, an optimal controller is synthesized with respect to a meaningful, a posteriori defined, cost functional. Our work illustrates the usefulness of this approach in the control of converter-based power systems and networked systems in general, and thereby in finding controllers with topological structure and known optimality properties. In particular, we design an inverse
Low-rank inducing unitarily invariant norms have been introduced to convexify problems with a low-rank/sparsity constraint. The most well-known member of this family is the so-called nuclear norm. To solve optimization problems involving such norms with proximal splitting methods, efficient ways of evaluating the proximal mapping of the low-rank inducing norms are needed. This is known for the nuc
Caustics are a challenging light transport phenomenon to render in real-time, and most previous approaches have used screen-space accumulation based on the fast rasterization hardware of GPUs. This limits the position of photon collection points to first hit screen space locations, and leads to missing caustics that should be visible in a mirror’s reflection. In this paper we propose an algorithm
