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Resource reservation is a technique that allows isolating applications from interfering among each other. In the most classic setting, this method requires the periodic allocation of a given budget of resource over time. However, in reality, the actual budget allocation may deviate from its ideal value. Examples of causes of this deviation are: the presence of a system tick, the usage of shared re
Dissolved Organic Carbon (DOC) in inland waters plays an essential role in the global carbon cycle and has significant public health effects. Machine learning (ML) together with remote sensing has emerged as a powerful and promising combination to quantify water quality parameters from space. However, inland water sample data for DOC is limited. Hence, little is known about the potential to quanti
The notion of warping the rate of time is explored in the context of differentially flat systems to enable time-optimal motion by convex optimisation. Examples are given with systems configured on the special Euclidean groups SE(2) and SE(3), with and without differential constraints. The proposed method complements classical methods of motion planning, may be used in a real-time context with guar
This paper evaluates the utility of the feedback particle filter (FPF) for state estimation of SE(2)-configured dynamics in a real-time context. The filter is implemented in discrete time to fuse gyroscopic-and accelerometer measurements with Ultra-Wideband (UWB) and camera measurements. With this state information, the FPF is compared to other common filters in terms of the estimate mean square e
We give a method for designing a mechanical impedance to suppress the propagation of disturbances along a chain of masses. The key feature of our method is that it is scale free. This means that it can be used to give a single, fixed, design, with provable performance guarantees in mass chains of any length. We illustrate the approach by designing a bidirectional control law in a vehicle platoon i
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
Connected Autonomous Vehicles (AV)s can transform urban transportation systems and have the potential to improve the safety and efficiency, since human errors and distractions are removed. However, these systems are vulnerable to model uncertainties, communication impairments associated with the wireless communication, and external disturbances. As a result, vehicles need to drive at low speed and
Why is it that semidefinite relaxations have been so successful in numerous applications in computer vision and robotics for solving non-convex optimization problems involving rotations? In studying the empirical performance, we note that there are few failure cases reported in the literature, in particular for estimation problems with a single rotation, motivating us to gain further theoretical u
Methane emissions from boreal and arctic wetlands, lakes, and rivers are expected to increase in response to warming and associated permafrost thaw. However, the lack of appropriate land cover datasets for scaling field-measured methane emissions to circumpolar scales has contributed to a large uncertainty for our understanding of present-day and future methane emissions. Here we present the Borea
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
G.fast is a gap-bridging broadband technology on the way to a fully optical access network. G.fast is deployed in hybrid fiber-copper access networks and aiming to offer ubiquitous low-cost and high-speed broadband. For network operators, it is crucial to determine the location from where to deploy G.fast, the expected network coverage, and the expected bit rates. In this paper, we perform network
Traditional network architecture design of Low Power Wide Area Networks (LPWAN) is incapable of dynamically scaling resources based on the served traffic and requires manual procedures for network capacity upgrades. Today's over-provisioning approach based on proprietary hardware (HW) would not be cost and energy efficient to cope with the ever-increasing scale of Internet of Things (IoT) devices
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
We prove that for k ≫; 4√n regular resolution requires length nω(k) to establish that an ErdÅ's-Rényi graph with appropriately chosen edge density does not contain a k-clique. This lower bound is optimal up to the multiplicative constant in the exponent and also implies unconditional nω(k) lower bounds on running time for several state-of-the-art algorithms for finding maximum cliques in graphs.
AI solutions seem to appear in any and all application domains. As AI becomes more pervasive, the importance of quality assurance increases. Unfortunately, there is no consensus on what artificial intelligence means and interpretations range from simple statistical analysis to sentient humanoid robots. On top of that, quality is a notoriously hard concept to pinpoint. What does this mean for AI qu
Proper irrigation scheduling and agricultural water management require a precise estimation of crop water requirement. In practice, reference evapotranspiration (ETo) is firstly estimated, and used further to calculate the evapotranspiration of each crop. In this study, two new coupled models were developed for estimating daily ETo. Two optimization algorithms, the shuffled frog-leaping algorithm
The role of the Tibetan Plateau (TP) in El Niño-Southern Oscillation (ENSO) variability is investigated using coupled model experiments with different topography setups. Removing the TP results in weakened trade winds in the tropical Pacific, an eastward shift of atmospheric convection center, a shallower mixed layer in the equatorial Pacific, and a flattened equatorial thermocline, which leads to
