Sökresultat

We study the one-dimensional version of the Rudin–Osher–Fatemi (ROF) denoising model and some related TV-minimization problems. A new proof of the equivalence between the ROF model and the so-called taut string algorithm is presented, and a fundamental estimate on the denoised signal in terms of the corrupted signal is derived. Based on duality and the projection theorem in Hilbert space, the proo

Inference of CO2 surface fluxes using atmospheric CO2 observations in atmospheric inversions depends critically on accurate representation of atmospheric transport. Here we characterize regional-scale CO2 transport uncertainties due to uncertainties in meteorological fields using a mesoscale atmospheric model and an ensemble of simulations with flow-dependent transport errors. During a 1-month sum

This study systematically examines the regional uncertainties and biases in carbon dioxide (CO2) mole fractions from two of the state-of-the-art global CO2 analysis products, namely, the Copernicus Atmosphere Monitoring Service (CAMS) real-time atmospheric analysis from the European Centre for Medium-Range Weather Forecasts (ECMWF) and the CarbonTracker Near-Real-Time (CT-NRT) reanalysis from the

The fact that deep learning based algorithms used for digital pathology tend to overfit to the site of the training data is well-known. Since an algorithm that does not generalize is not very useful, we have in this work studied how different data augmentation techniques can reduce this problem but also how data from different sites can be normalized to each other. For both of these approaches we

The Learning with Errors problem (LWE) is one of the main candidates for post-quantum cryptography. At Asiacrypt 2017, coded-BKW with sieving, an algorithm combining the Blum-Kalai-Wasserman algorithm (BKW) with lattice sieving techniques, was proposed. In this paper, we improve that algorithm by using different reduction factors in different steps of the sieving part of the algorithm. In the Rege

In this paper we address the problem of resource allocation for alarm traffic in industrial Internet of Things networks using massive MIMO. We formulate the general problem of how to allocate pilot signals to alarm traffic such that delivery is guaranteed, while also minimising the number of pilots reserved for alarms, thus maximising the channel resources available for other traffic, such as indu

In vivo dosimetry of IMRT from Copenhagen University Hospital

The problem of monotone smoothing splines with bounds is formulated as a constrained minimization problem of the calculus of variations. Existence and uniqueness of solutions of this problem is proved, as well as the equivalence of it to a finite dimensional but nonlinear optimization problem. A new algorithm for computing the solution which is a spline curve, using a branch and bound technique, i

Learning a computationally efficient kernel from data is an important machine learning problem. The majority of kernels in the literature do not leverage the geometry of the data, and those that do are computationally infeasible for contemporary datasets. Recent advances in approximation techniques have expanded the applicability of the kernel methodology to scale linearly with the data size. Data

The problem of estimating receiver or sender node positions from measured receiver-sender distances is a key issue in different applications such as microphone array calibration, radio antenna array calibration, mapping and positioning using UWB or using round-trip-time measurements between mobile phones and WiFi-units. In this paper we address the problem of optimally estimating a receiver positi

In this paper we study the problem of estimating receiver and sender positions from time-difference-of-arrival measurements, assuming an unknown constant time-difference-of-arrival offset. This problem is relevant for example for repetitive sound events. In this paper it is shown that there are three minimal cases to the problem. One of these (the five receiver, five sender problem) is of particul

This study explores the online communication strategies of anti-tourism movements to evaluate their potential contributions to place branding—a topic that has received limited scholarly attention. While prior research often views such movements as antagonistic to place branding efforts, we challenge this assumption. Through an analysis of nine movements across five countries, we apply the typology

Background Long-term pathological breathlessness is a life-limiting symptom that risks taking control of the individual’s life. We aimed to evaluate how locus of control (LOC), an individual’s perceived control of present and past life events, relates to breathlessness in a middle-aged general population. Methods A population-based, cross-sectional analysis of people aged 50–64 years was conducted

Combining forecasts from multiple temporal aggregation levels exploits information differences and mitigates model uncertainty, while reconciliation ensures a unified prediction that supports aligned decisions at different horizons. It can be challenging to estimate the full cross-covariance matrix for a temporal hierarchy, which can easily be of very large dimension, yet it is difficult to know a

Planar motion is an important and frequently occurring situation in mobile robotics applications. This thesis concerns estimation of ego-motion and pose of a single downwards oriented camera under the assumptions of planar motion and known internal camera parameters. The so called essential matrix (or its uncalibrated counterpart, the fundamental matrix) is frequently used in computer vision appli

We consider the problem of designing distinguishers and nonrandomness detectors for stream ciphers using the maximum degree monomial test. We construct an improved algorithm to determine the subset of key and IV-bits used in the test. The algorithm is generic, and can be applied to any stream cipher. In addition to this, the algorithm is highly tweakable, and can be adapted depending on the desire

The Bit Flipping algorithm is a hard decision decoding algorithm originally designed by Gallager in 1962 to decode Low Density Parity Check Codes (LDPC). It has recently proved to be much more versatile, for Moderate Parity Check Codes (MDPC) or Euclidean metric. We further demonstrate its power by proposing a noisy Euclidean version of it. This tweak allows to construct a lattice based key exchan

In this paper we direct our attention to the problem of discretization effects in intensity transformations of images. We propose to use the Wasserstein metric (also known as the Earth mover distance) to bootstrap the transformation process. The Wasserstein metric gives a mapping between gray levels that we use to direct our image mapping. In order to spatially regularize the image mapping we appl