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Finite Element-Boundary Integral Simulation of Icing Effects on a Marine Radar Reflector

This paper presents simulations of the radar cross section for a marine corner reflector affected by icing as it is illuminated by 3 GHz marine radar. This is compared to the radar cross section for an unaffected reflector, and the consequences for radar range are investigated. To perform the simulations, a finite element-boundary integral hybrid method is used. The simulation code is based on sev

Dual Control by Reinforcement Learning Using Deep Hyperstate Transition Models

In dual control, the manipulated variables are used to both regulate the system and identify unknown parameters. The joint probability distribution of the system state and the parameters is known as the hyperstate. The paper proposes a method to perform dual control using a deep reinforcement learning algorithm in combination with a neural network model trained to represent hyperstate transitions.

Angular-Domain Massive MIMO Detection

In massive multiple-input multiple-output (MIMO) systems, the large size of channel state information (CSI) matrix significantly increases the computational complexity of uplink detection and size of required memory to store the channel data. To address these challenges, we propose to perform detection in the angular domain, where the channel information can be presented in a more condensed way. T

FedApp: a Research Sandbox for Application Orchestration in Federated Clouds using OpenStack

Multi-cluster federation is envisioned to be the next-generation cloud infrastructure, where it will play a vital part in the realization of concepts such as edge and fog computing. Orchestrating applications in federated environments poses new challenges to well-known research problems in various fields, such as load-balancing, auto-scaling, resource allocation and service migration. However, as

Closing the Feedback Loop in DevOps Through Autonomous Monitors in Operations

DevOps represent the tight connection between development and operations. To address challenges that arise on the bor- derline between development and operations, we conducted a study in collaboration with a Swedish company responsible for ticket management and sales in public transportation. The aim of our study was to explore and describe the existing DevOps environment, as well as to identify h

ESS Control System Data Lab - Executive Summary

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

Minimax Adaptive Estimation for Finite Sets of Linear Systems

For linear time-invariant systems with uncertain parameters belonging to a finite set, we present a purely eterministic approach to multiple-model estimation and propose an algorithm based on the minimax criterion using constrained quadratic programming. The estimator tends to learn the dynamics of the system, and once the uncertain parameters have been sufficiently estimated, the estimator behave

Weaklyhard. jl: Scalable analysis of weakly-hard constraints

Weakly-hard models have been used to analyse real-time systems subject to patterns of deadline hits and misses. However, the tools that are available in the literature have a set of shortcomings. The analysis they offer is limited to a single weaklyhard constraint and to patterns that specify the number of misses, rather than the number of hits. Furthermore, the scalability of the tools is limited

Multi-Armed Bandits in Brain-Computer Interfaces

The multi-armed bandit (MAB) problem models a decision-maker that optimizes its actions based on current and acquired new knowledge to maximize its reward. This type of online decision is prominent in many procedures of Brain-Computer Interfaces (BCIs) and MAB has previously been used to investigate, e.g., what mental commands to use to optimize BCI performance. However, MAB optimization in the co

Phonetic and phonological cues to prediction : Neurophysiology of Danish stød

A corpus study and a combined behavioural and neurophysiological study tested how phonetic and phonological features of the Danish creaky voice feature ‘stød’ influence predictive processing. Being associated with certain word endings, stød and its modal voice counterpart non-stød can cue upcoming speech. Stød has two phases. The first shows phonetic differences in pitch while the second, characte

A 12-GHz Reconfigurable Multicore CMOS DCO, With a Time-Variant Analysis of the Impact of Reconfiguration Switches on Phase Noise

This article introduces a 28-nm CMOS digitally controlled oscillator (DCO) based on eight oscillator cores, where the number of active cores can be reconfigured to be either 2, 4, 6, or 8, trading power consumption for phase noise without incurring an additional phase noise penalty. The impact of the reconfiguration pMOS switches on the phase noise performance is determined through a simple yet ri

A Structured Optimal Controller for Irrigation Networks

In this paper, we apply an optimal Linear Quadratic (LQ) controller, which has an inherent structure that allows for a distributed implementation, to an irrigation network. The network consists of a water reservoir and connected water canals. The goal is to keep the levels close to the set-points when farmers take out water. The LQ controller is designed using a first-order approximation of the ca

Nondestructive Testing Using mm-Wave Sparse Imaging Verified for Singly Curved Composite Panels

Nondestructive testing of composite materials is important in aerospace applications, and mm-wave imaging has been increasingly used for this purpose. Imaging is traditionally performed using Fourier methods, with inverse methods being an alternative. This communication presents a mm-wave imaging method with an inverse approach intended for nondestructive testing of singly curved composite panels

The importance of time of day for magnetic body alignment in songbirds

Spontaneous magnetic alignment is the simplest known directional response to the geomagnetic field that animals perform. Magnetic alignment is not a goal directed response and its relevance in the context of orientation and navigation has received little attention. Migratory songbirds, long-standing model organisms for studying magnetosensation, have recently been reported to align their body with

Property probes : live exploration of program analysis results

We present property probes, a mechanism for helping a developer explore partial program analysis results in terms of the source program interactively while the program is edited. A node locator data structure is introduced that maps between source code spans and program representation nodes, and that helps identify probed nodes in a robust way, after modifications to the source code. We have devel

A Belief Propagation Algorithm for Multipath-based SLAM with Multiple Map Features: A mmWave MIMO Application

In this paper, we present a multipath-based simultaneous localization and mapping (SLAM) algorithm that continuously adapts mulitiple map feature (MF) models describing specularly reflected multipath components (MPCs) from flat surfaces and point-scattered MPCs, respectively. We develop a Bayesian model for sequential detection and estimation of interacting MF model parameters, MF states and mobil

A High-Speed Comparator Using a New Regeneration Latch

This paper presents a high-speed comparator which employs a novel regeneration latch to enhance the comparison process. The regeneration stage employs an innovative mechanism that reduces the RC constant at the output while avoiding static power consumption. Furthermore, the proposed comparator is capable of operating seamlessly with a rail-to-rail input common-mode voltage. This is made possible

Distributed MIMO Measurements for Integrated Communication and Sensing in an Industrial Environment

Many concepts for future generations of wireless communication systems use coherent processing of signals from many distributed antennas. The aim is to improve communication reliability, capacity, and energy efficiency and provide possibilities for new applications through integrated communication and sensing. The large bandwidths available in the higher bands have inspired much work regarding sen

Enhanced Effective Aperture Distribution Function for Characterizing Large-Scale Antenna Arrays

Accurate characterization of large-scale antenna arrays is growing in importance and complexity for the fifth-generation (5G) and beyond systems, as they feature more antenna elements and require increased overall performance. The full 3D patterns of all antenna elements in the array need to be characterized because they are in general different due to construction inaccuracy, coupling, antenna ar

Quad-element LTE hidden car roof antenna system

This work presents the systematic design and optimization of a compact quad-element MIMO antenna system in a roof cavity for the expected channel behavior at a 700 MHz LTE band. Beginning with a standard low-profile antenna element, the desired radiation pattern is synthesized by structural modification. The configuration for a quad-element design is then optimized. The results show that the propo