Search results

Background: Birds that forage while covering distance during migration should adjust traveling behaviors as the availability of foraging habitat changes. Particularly, the behavior of those species that depend on bodies of water to find food yet manage to migrate over changing landscapes may be limited by the substantial variation in feeding opportunities along the route. Methods: Using GPS tracki

This is the Replicated Computational Results (RCR) Report for the article ‘Stress Testing Control Loops in Cyber-Physical Systems’. The article proposes a novel approach for testing Cyber-Physical Systems (CPS) based on the integration of the guarantees that can be provided with the control theoretical models into the software testing practices. This RCR report describes how to reproduce the empir

Dynamic task offloading is essential for real-time robotic applications, enabling them to adapt to fluctuating computational demands and maintain efficiency under changing conditions. This paper introduces a dynamic task offloading framework that incorporates monitoring, decision making, offloading triggering, and performance monitoring to optimize resource usage by offloading real-time tasks to e

The need for information about climate change is great. This information is usually based on climate model data, which often have systematic biases. Furthermore, climate information is based on ensembles of climate models, which raises the question about how such ensembles are affected by the choice of models and emission scenarios. Here, we aim to describe climate change in Sweden and neighbourin

Forest Canopy Height (FCH) is one of the key variables for understanding forest structure distribution and growth. Remotely sensed data such as the NASA Ice, Cloud and Land Elevation Satellite-2 (ICESat-2) ATL08 provides accurate FCH measurements; however, its point-based nature limits spatial continuity. This study addresses the challenge by generating a continuous FCH map over the West Usambara

A decentralized strategy for object transportation is presented, assuming that the object is grasped by a team of N cooperative manipulators. The proposed strategy consists of two steps. First, each robot estimates the wrenches applied to the object by all the others robots, even without all-to-all communication. Second, an admittance control scheme is used to limit internal wrenches, preventing e

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

Background: Magnetic resonance imaging (MRI) has traditionally been preferred over computed tomography (CT) for segmentation of intracranial structures due to its superior low contrast resolution. However, a reliable CT-based segmentation could improve patient management when MRI is not practical. Despite advancements in CT imaging, such as enhanced tissue differentiation using virtual monoenerget

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

Mixed-effects models are used to describe the inter-patient variability in drugs. Modeling of these variabilities include both fixed and random effects. Fixed effects relate covariates such as age and weight to compartment volumes and clearances, whereas random effects account for unexplained variability. Traditionally, the development of fixed effects models is an inefficient process where covari

In the mining industry, flotation is a commonly used process to separate valuable minerals from waste rock in a concentrator. The rougher flotation is the first stage of the process and in Boliden AB’s concentrator at Aitik, it consists of two lines of four flotation cells each. In this paper we consider one line and the buffer tank upstream of it. Modeling this process step, and maintaining an up

In this paper, we investigate the problem of decoder error propagation for spatially coupled low-density parity-check (SC-LDPC) codes with sliding window decoding (SWD). This problem typically manifests itself at signal-to-noise ratios (SNRs) close to capacity under low-latency operating conditions. In this case, infrequent but severe decoder error propagation can sometimes occur. To help understa

Clustering multiple motions from observed point trajectories is a fundamental task in understanding dynamic scenes. Most motion models require multiple tracks to estimate their parameters, hence identifying clusters when multiple motions are observed is a very challenging task. This is even aggravated for high-dimensional motion models. The starting point of our work is that this high-dimensionali

Modern integrated circuits (ICs) contain thousands of instruments to enable testing, tuning, monitoring, and so on. These on-chip instruments must be accessed through the ICs’ life- time. However, when ICs are mounted on Printed Circuit Boards (PCBs), access from system-level is challenged due to complex system hierarchies with a multitude of interfaces. In this paper we enable access from system-

Modern integrated circuits (ICs) include thousands of on-chip instruments to ensure that specifications are met and maintained. Scalable and flexible access to these instruments is offered by reconfigurable scan networks (RSNs), e.g. IEEE Std. 1687. As RSNs themselves can become faulty, there is a need to exclude and bypass faulty parts so that remaining instruments can be used. To avoid keeping t