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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
Background: In patients with chronic obstructive pulmonary disease (COPD), the relationship between short-term bronchodilator reversibility and longer-term response to bronchodilators is unclear. Here, we investigated whether the efficacy of long-acting bronchodilators is associated with reversibility of airflow limitation in patients with COPD with a low exacerbation risk not receiving inhaled co
INTRODUCTION Despite preeclampsia being one of the most severe obstetrical complications there is only scant research describing women's experiences of preeclampsia. The aim of this study was to explore women's experience during pregnancy and the postpartum period regarding the provided information and care concerning preeclampsia. METHODS A qualitative study was designed. Semi-structured face-to-
The learning with errors (LWE) problem is one of the main mathematical foundations of post-quantum cryptography. One of the main groups of algorithms for solving LWE is the Blum–Kalai–Wasserman (BKW) algorithm. This paper presents new improvements of BKW-style algorithms for solving LWE instances. We target minimum concrete complexity, and we introduce a new reduction step where we partially reduc
In this paper, we present a side-channel attack on a first-order masked implementation of IND-CCA secure Saber KEM. We show how to recover both the session key and the long-term secret key from 24 traces using a deep neural network created at the profiling stage. The proposed message recovery approach learns a higher-order model directly, without explicitly extracting random masks at each executio
It is unclear how to address PTSD in the context of chronic pain management. Here we examine the potential benefits of an addition of prolonged exposure (PE) therapy for PTSD for adults attending multidisciplinary CBT for chronic pain. Four adults seeking treatment for chronic pain from a specialized pain rehabilitation service were offered PE for PTSD using a replicated, randomized, single-case e
Efficient protection of huge amount of IoT produced data is key for wide scale data analytic services. The most efficient way is to use pure symmetric encryption as that allows both fast decryption at the analytic engine side as well as energy efficient encryption at the IoT side. However, symmetric encryption can only be performed if there is a way to directly map an encrypted object to the corre
Denna sammanläggningsavhandling bygger på den kritiska teorins ambition att som en motbild till rådande läge skapa en bild av hur ett frigörande och i politiskt avseende realistiskt alternativ skulle kunna se ut, ett alternativ som innebär att personer som har utsatts för sexuellt våld får ett erkännande och kan delta i samhällslivet på lika villkor som andra. Mer specifikt är syftet att förstå hThe compilation dissertation is shaped by the ambition of Critical Theory, which is to imagine an alternative and emancipatory political reality to the status quo, where people who have been subjected to sexual violence are recognised and enjoy parity of participation in social life. More specifically, it aims to understand how victim-survivors of sexual violence in Iceland perceive, experience, a
OBJECTIVE: Although fear of birth is common during pregnancy and childbirth, the best treatment for fear of birth in clinical care remain unclear. Strong evidence suggests that continuity models of midwifery care can benefit women and birth outcomes, though such models are rare in Sweden. Because women with fear of birth could benefit from such models, the aim of this qualitative study was to exam
Closed-loop controlled drug dosing has the potential of revolutionizing clinical anesthesia. However, interpatient variability in drug sensitivity poses a central challenge to the synthesis of safe controllers. Identifying a full individual pharmacokinetic–pharmacodynamic (PKPD) model for this synthesis is clinically infeasible due to limited excitation of PKPD dynamics and presence of unmodeled d
Disc brake creep groan is a stick-slip phenomenon which results in a low frequency noise in road vehicles that could occur at low vehicle speeds and brake torques. Simulation approaches are used predict the stick-slip phenomena for disc brakes. These approaches depend on the friction model used. Tribometers can be used to map how the local coefficient of friction (CoF) depends on the contact press
A search for the direct production of the supersymmetric partners of τ-leptons (staus) in final states with two hadronically decaying τ-leptons is presented. The analysis uses a dataset of pp collisions corresponding to an integrated luminosity of 139 fb-1, recorded with the ATLAS detector at the Large Hadron Collider at a center-of-mass energy of 13 TeV. No significant deviation from the expected
The relaxation systems are an important subclass of the passive systems that arise naturally in applications. We exploit the fact that they have highly structured state-space realisations to derive analytical solutions to some simple H-infinity type optimal control problems. The resulting controllers are also relaxation systems, and often sparse. This makes them ideal candidates for applications i
This paper proposes a convex approach to the Frisch-Kalman problem that identifies the linear relations among variables from noisy observations. The problem was proposed by Ragnar Frisch in 1930s, and was promoted and further developed by Rudolf Kalman later in 1980s. It is essentially a rank minimization problem with convex constraints. Regarding this problem, analytical results and heuristic met
Machine and reinforcement learning (RL) are increasingly being applied to plan and control the behavior of autonomous systems interacting with the physical world. Examples include self-driving vehicles, distributed sensor networks, and agile robots. However, when machine learning is to be applied in these new settings, the algorithms had better come with the same type of reliability, robustness, a
In this paper we consider adaptive distributed stabilization for uncertain multivariable linear systems with a time-varying diagonal matrix gain. We show that an unknown system matrix being an M-matrix is a sufficient condition to ensure uncertain linear systems to be stabilizable by matrix high gains, and derive a threshold condition to ensure exponential stability of uncertain linear systems sta
Fast and accurate homography estimation is essential to many computer vision applications, including scene degenerate cases and planarity detection. Such cases arise naturally in man-made environments, and failure to handle them will result in poor positioning estimates. Most modern day consumer cameras are affected by some level of radial distortion, which must be compensated for in order to get
