Filetype
Driven by the idea to use alarm data to explore machine learning across Industry 4.0 applications, the goal of this pilot study was to explore how to collect, store, manage and share data from the ESS Control System. Generally, we seek to make any control system data available for research and innovation but started with alarms as a feasible domain in which to explore machine learning. The goals w
While social movement scholars have long recognized the importance of collective memory and shared pasts in the construction of collective identities, less attention has focused on the role of imagined futures. Based on a long-term ethnographic study of radical left-libertarian groups in Sweden, this paper explores the role of utopia in structuring, influencing, and evaluating actions and practice
This paper presents an angular-domain massive MIMO detector which exploits sparsity in massive MIMO channel along with a reconfigurable systolic array architecture to achieve high area efficiency. The underlying idea is to perform signal detection in the angular domain, where the channel matrix can have much lower dimension due the limited number of dominant angles (of arrival and departure) of th
Clays can be synthesised to have specific functional properties, which have been exploited in a range of industrial processes. A key characteristic of clay is the presence of a negatively charged surface, surrounded by an oppositely charged rim. Because of that, clays are able to sequester cationic compounds resulting in the formation of ordered layered structures, known as tactoids. Recent resear
Stored energies of radiating systems have generated research interest for several decades due to their relationship with Q-factor and fractional bandwidth. In this paper material derivatives are used to provide a new interpretation of widely used stored energy expressions. This provides a fundamental relationship between stored energies of radiating systems and their electromagnetic material prope
The number of degrees of freedom is a crucial parameter in many electromagnetic problems. In for example modern communication systems spatial diversity is often employed through multiple beams to enhance capacity and reliability. However, while the degrees of freedom can be computed, their connection to physical quantities is not as easily understood. To address this issue, this paper proposes a s
Brain-computer interfaces (BCIs) translate brain activity into digital commands for interaction with the physical world. The technology has great potential in several applied areas, ranging from medical applications to entertainment industry, and creates new conditions for basic research in cognitive neuroscience. The BCIs of today, however, offer only crude online classification of the user's cur
In this paper we propose a shared regression network to jointly estimate the pose of multiple objects, replacing multiple object-specific solutions. We demonstrate that this shared network can outperform other similar approaches that rely on multiple object-specific models by evaluating it on the TLESS dataset using the VSD (Visible Surface Discrepancy). Our approach offers a less complex solution
Channel sounding is essential for the development of radio systems. One flexible strategy is the switched-array-based channel sounding, where antenna elements are activated at different time instants to measure the channel spatial characteristics. Although its hardware complexity is decreased due to fewer radio-frequency (RF) chains, sequentially switching the antenna elements can result in aliasi
In modern industrial settings with small batch sizes it should be easy to set up a robot system for a new task. Strategies exist, e.g. the use of skills, but when it comes to handling forces and torques, these systems often fall short. We introduce an approach that provides a combination of task-level planning with targeted learning of scenario-specific parameters for skill-based systems. We propo
Upper bounds on the focusing efficiency of aperture fields and lens systems are formulated using integral equation representations of Maxwell’s equations and Lagrangian duality. Two forms of focusing efficiency are considered based on lens exit plane fields and optimal polarization currents within lens design regions of prescribed shape and available materials. Bounds are compared against the perf
Characteristic modes are formulated using the scattering dyadic, which maps incident plane waves to scattered far fields generated by an object of arbitrary material composition. Numerical construction of the scattering dyadic using arbitrary full-wave electromagnetic solvers is demonstrated in examples involving a variety of dielectric and magnetic materials. Wrapper functions for computing chara
This paper studies the problem of coordinating a group of nth-order integrator systems. As for the well-studied conventional consensus problem, we consider linear and distributed control with only local and relative measurements. We propose a closed-loop dynamic that we call serial consensus and prove it achieves nth order consensus regardless of model order and underlying network graph. This alle
When we speak, we typically also gesture. Gestures are an integral part of language use in both production and comprehension. They are therefore also vital in second language (L2), foreign language (FL), and bilingualism studies since they can open new windows on cognitive processes, interaction practices, and learning. This entry discusses methods and tools for studying second language users' and
In this paper, we present a global solution to a nonlinear H-infinity optimal control problem for control-affine systems with an associated potential function. We also give a closed-form expression for an optimal controller and demonstrate its potential for sparsity. This paper thus advances a recent result which considers the same problem restricted to systems with symmetric state matrix and nonl
This thesis concerns control of capacity-constrained networks. These systems involve many agents interconnected by a resource distribution network. The capacity to generate and distribute this resource is constrained. This applies, for instance, to power grids, communication networks, smart surveillance camera networks, and district heating networks. District heating networks in particular are the
High-dimensional problems have long been considered the Achilles' heel of Bayesian optimization. Spurred by the curse of dimensionality, a large collection of algorithms aim to make it more performant in this setting, commonly by imposing various simplifying assumptions on the objective. In this paper, we identify the degeneracies that make vanilla Bayesian optimization poorly suited to high-dimen
