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Background: Markov models are models used to describe movement of individuals between states. In medicine, Markov models are used to describe, for example, disease progression and the effects of interventions on such progression. The models can further be used to identify medical risk groups and aid clinicians in clinical decision making. Although accurate individual predictions are crucial for ut
Covariate modeling provides individual predictions of outcomes by disease progression models. Current methodology for mapping covariates onto model parameters is limited by predefined parametric functions which can result in inadequate covariate selection and biased predictions by the final model. Furthermore, present methodology scales poorly to high-dimensional data due to combinatorial limitati
This paper presents a method for online estimation of contact properties during in-hand sliding manipulation with a parallel gripper. We estimate the static and Coulomb friction as well as the contact radius from tactile measurements of contact forces and sliding velocities. The method is validated in both simulation and real-world experiments. Furthermore, we propose a heuristic to deal with fast
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Denna rapport analyserar framväxten av hundvänlig turism i Sverige och belyser dess betydelse för besöksnäringens utveckling. Studien visar att hunden i allt högre grad betraktas som en familjemedlem, vilket påverkar resenärers beteenden, val av destination och konsumtionsmönster. Hundägare utgör en reseaktiv och kommersiellt attraktiv målgrupp som främst reser inom Sverige och efterfrågar naturbaThis report analyses the emergence of dog-friendly tourism in Sweden and highlights its significance for the hospitality industry's development. The study shows that dogs are increasingly regarded as family members, influencing travellers’ behaviour, destination choices, and consumption patterns. Dog owners represent a travel-active and commercially attractive target group that primarily travels d
Spherical motion is a special case of camera motion where the camera moves on the imaginary surface of a sphere with the optical axis normal to the surface. Common sources of spherical motion are a person capturing a stereo panorama with a phone held in an outstretched hand, or a hemi-spherical camera rig used for multi-view scene capture. However, traditional structure-from-motion pipelines tend
Lines and points are complementary local features, whose combination has proven effective for applications such as SLAM and Structure-from-Motion. The backbone of these pipelines are the local feature matchers, establishing correspondences across images. Traditionally, point and line matching have been treated as independent tasks. Recently, GlueStick proposed a GNN-based network that simultane-ou
Monocular depth estimation (MDE) models have undergone significant advancements over recent years. Many MDE models aim to predict affine-invariant relative depth from monocular images, while recent developments in large-scale training and vision foundation models enable reasonable estimation of metric (absolute) depth. However, effectively leveraging these predictions for geometric vision tasks, i
Motivated by the well established idea that collective wisdom is greater than that of an individual, we propose a novel learning dynamics as a sort of companion to the Abelson model of opinion dynamics. Agents are assumed to make independent guesses about the true state of the world after which they engage in opinion exchange leading to consensus. We investigate the problem of finding the optimal
Traditionella, rörbaserade dagvattensystem räcker inte längre till i förtätade städer för att möta krav på vattenkvalitet och översvämningsskydd vid extrem nederbörd. Därför efterfrågas naturbaserade och multifunktionella lösningar, här omnämnda som blå-grön infrastruktur, som kan hantera flera samhällsutmaningar samtidigt.Implementeringen av sådana lösningar försvåras dock av många och ibland sam
Scholars propose some new directions for researching statistical learning (SL), including the need to adopt stimuli with greater ecological validity. The language sciences are moving in these directions. Studies investigating adult SL after short exposure to an unfamiliar (spoken or signed) language show that SL can occur from richer, continuous, multimodal input, suggesting that learners are able
In this chapter, we explore mathematical tools for assessing the stability, convergence, and boundedness of trajectories in generally nonlinear dynamical systems. We delve into the seminal theorems introduced by A. Lyapunov which are primarily concerned with the stability of equilibrium points. The chapter progresses to discuss the extension of Lyapunov's Theory, due to LaSalle, aimed at assessing
This paper presents a decentralized strategy for a team of N robotic manipulators cooperatively grasping and manipulating an object. A two-step strategy has been designed. In the first step, each robot runs N − 1 consensus-based estimators to estimates the wrenches applied to the object by its teammates even when direct all-to-all communication is unavailable. In the second step, each manipulator
Resource provisioning for applications hosted in the cloud is a difficult task due to inherent performance variability in the infrastructure. Control theory has proven to be an efficient tool to increase the predictability of cloud applications. However, a prerequisite for a successful control design is an adequate model of the involved dynamics. In this paper we focus on modeling of controlled se
Distributed multiple-input multiple-output (MIMO), also known as cell-free massive MIMO, has emerged as a promising technology for sixth-generation (6G) wireless networks. This letter introduces an indoor channel measurement campaign designed to explore the behavior of multipath components (MPCs) in distributed MIMO channels. Fully coherent channels were measured between eight distributed uniform
Structure-from-Motion (SfM) has become a ubiquitous tool for camera calibration and scene reconstruction with many downstream applications in computer vision and beyond. While the state-of-the-art SfM pipelines have reached a high level of maturity in well-textured and well-configured scenes over the last decades, they still fall short of robustly solving the SfM problem in challenging scenarios.
Digital control systems introduce unavoidable computational latencies. For some controllers this time delay inhibits practical use, even though they in theory could provide more efficient control. For example, solving an optimization problem each sampling period when using model predictive control. By sampling faster than the computation time and executing independent controllers on distributed ha
