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In this theoretical paper we consider the problem of accurately triangulating a scene plane. Rather than first triangulating a set of points and then fitting a plane to these points, we try to minimize the back-projection errors as functions of the plane parameters directly. As this is both geometrically and statistically meaningful our method performs better than the standard two step procedure.
Stochastic optimal power flow can provide the system operator with adequate strategies for controlling the power flow to maintain secure operation under stochastic parameter variations. One limitation of stochastic optimal power flow has been that only steady-state variable limits have been used as security constraints. In many systems voltage stability and small-signal stability also play an impo
Precision agriculture requires detailed crop status information at high spatial and temporal resolutions. Remote sensing can provide such information, but single sensor observations are often incapable of meeting all data requirements. Spectral-temporal response surfaces (STRSs) provide continuous reflectance spectra at high temporal intervals. This is the first study to combine multispectral sate
The rate of constitutive isoprenoid emissions from plants is driven by plant emission capacity under specified environmental conditions (E-S, the emission factor) and by responsiveness of the emissions to instantaneous variations in environment. In models of isoprenoid emission, E-S has been often considered as intrinsic species-specific constant invariable in time and space. Here we analyze the v
Nowadays, the same piece of code should run on different architectures, providing performance guarantees in a variety of environments and situations. To this end, designers often integrate existing systems with ad-hoc adaptive strategies able to tune specific parameters that impact performance or energy—for example, frequency scaling. However, these strategies interfere with one another and unpred
This work presents an event-based control structure using the generalized predictive control (GPC) algorithm with actuator deadband. The main objective of this work is to limit the number of controlled system updates. In this approach, the controlled process is sampled with a constant sampling time and is updated in an asynchronous way that depends on the obtained control signal value. To achieve
Gradient orientations are a common feature used in many computer vision algorithms. It is a good feature when the gradient magnitudes are high, but can be very noisy when the magnitudes are low. This means that some gradient orientations are matched with more confidence than others. By estimating this uncertainty, more weight can be put on the confident matches than those with higher uncertainty.
We analyze reinforcement learning under so-called "dynamic reinforcement." In reinforcement learning, each agent repeatedly interacts with an unknown environment (i.e., other agents), receives a reward, and updates the probabilities of its next action based on its own previous actions and received rewards. Unlike standard reinforcement learning, dynamic reinforcement uses a combination of long-ter
LTHs 8:e Pedagogiska Inspirationskonferens, 17 december 2014 Abstract—Vi har studerat hur omfattningen av den kursansvariga lärarens behörighetsgivande pedagogikutbildning (BHU) samvarierar med studenternas bedömningar av den pedagogiska kvalitén på kurser uttryckt genom kursutvärderingarnas data från Course Experience Questionnaire (CEQ). Vi har även studerat hur CEQ-resultaten ser ut beroende
https://www.lth.se/fileadmin/lth/genombrottet/konferens2014/34_Borell_Andersson.pdf - 2026-05-15
Microsoft Word - Avtal postdoktor för underskrift 080904.doc Avtal Bilaga 2008-09-04 Parter Arbetsgivarsidan: Arbetsgivarverket Arbetstagarsidan: OFR:s förbundsområden inom det statliga förhandlings- området sammantagna Saco-S Facket för Service och Kommunikation (SEKO) Avtal om tidsbegränsad anställning som post- doktor 1 § Avtalet gäller arbetstagare som anställs som postdoktor och som i huvudsa
For many assembly operations force control is needed, but force sensors may be expensive and add mass to the system. An alternative is to use the motor torques, though friction causes large disturbances. The Coulomb friction can be quite well known when a joint is moving, but has much larger uncertainties for velocities close to zero. This paper presents a method for force estimation that account
We have developed the novel Aerosol Dynamics, gas- and particle-phase chemistry model for laboratory CHAMber studies (ADCHAM). The model combines the detailed gas-phase Master Chemical Mechanism version 3.2 (MCMv3.2), an aerosol dynamics and particle-phase chemistry module (which considers acid-catalysed oligomerization, heterogeneous oxidation reactions in the particle phase and non-ideal interac
A knee injury with anterior cruciate ligament (ACL) rupture may cause deficits in proprioception, increased laxity and decreased muscle strength. Although it may be common knowledge that these factors affect knee function, only a few studies have been performed where this has been investigated in the clinical situation, and the results are not conclusive. The purpose of this study was therefore to
One of the main limiting factors in improving glucose control for type 1 diabetes mellitus (T1DM) subjects is the lack of a precise description of meal and insulin intake effects on blood glucose. Knowing the magnitude and duration of such effects would be useful not only for patients and physicians, but also for the development of a controller targeting glycaemia regulation. Therefore, in this pa
We investigate dual decomposition approaches for optimization problems arising in low-level vision. Dual decomposition can be used to parallelize existing algorithms, reduce memory requirements and to obtain approximate solutions of hard problems. An extensive set of experiments are performed for a variety of application problems including graph cut segmentation, curvature regularization and more
We consider the problem of distributed convergence to efficient outcomes in coordination games through dynamics based on aspiration learning. Our first contribution is the characterization of the asymptotic behavior of the induced Markov chain of the iterated process in terms of an equivalent finite-state Markov chain. We then characterize explicitly the behavior of the proposed aspiration learnin
A local-scale Gaussian dispersion-deposition model (OML-DEP) has been coupled to a regional chemistry-transport model (DEHM with a resolution of approximately 6 km x 6 km over Denmark) in the Danish Ammonia Modelling System, DAMOS. Thereby, it has been possible to model the distribution of ammonia concentrations and depositions on a spatial resolution down to 400 m x 400 m for selected areas in De
Cluster analysis of particle number size distributions from background sites across Europe is presented. This generated a total of nine clusters of particle size distributions which could be further combined into two main groups, namely: a south-to-north category (four clusters) and a west-to-east category (five clusters). The first group was identified as most frequently being detected inside and
We present the first method to handle curvature regularity in region-based image segmentation and inpainting that is independent of initialization. To this end we start from a new formulation of length-based optimization schemes, based on surface continuation constraints, and discuss the connections to existing schemes. The formulation is based on a cell complex and considers basic regions and bou
We construct a variational formulation for the problem of interpolating seismic data in the case of missing traces. We assume that we have derivative information available at the traces. The variational problem is essentially the minimization of the integral over the smallest eigenvalue of the structure tensor associated with the interpolated data. This has the physical meaning of penalizing the l
