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Constraining terrestrial carbon fluxes through assimilation of SMOS products

The ongoing ESA funded'SMOS + Vegetation' project combines a retrieval component that aims at further improving the SMOS VOD product with an assimilation component that aims at demonstrating the added value of this product in constraining simulated land surface fluxes of carbon dioxide. This contribution focuses on the project's modelling and assimilation component. We describe the construction of

Regional CO2 inversions with LUMIA, the Lund University modular inversion algorithm, v1.0

Atmospheric inversions are used to derive constraints on the net sources and sinks of CO2 and other stable atmospheric tracers from their observed concentrations. The resolution and accuracy that the fluxes can be estimated with depends, among other factors, on the quality and density of the observational coverage, on the precision and accuracy of the transport model used by the inversion to relat

Customer Perceived Service Quality

The purpose of this study is to develop a general understanding of the areas of alliances and service quality as well as their relation to each other, through a consumer perception. Further, to discover more detailed and close up knowledge of customer perceived service quality within airline alliances. This is done by identifying particularly significant dimensions in the service process that have

Shape-aware label fusion for multi-atlas frameworks

Despite of having no explicit shape model, multi-atlas approaches to image segmentation have proved to be a top-performer for several diverse datasets and imaging modalities. In this paper, we show how one can directly incorporate shape regularization into the multi-atlas framework. Unlike traditional multi-atlas methods, our proposed approach does not rely on label fusion on the voxel level. Inst

Fast and robust stratified self-calibration using time-difference-of-arrival measurements

In this paper we study the problem of estimating receiver and sender positions using time-difference-of-arrival measurements. For this, we use a stratified, two-tiered approach. In the first step the problem is converted to a low-rank matrix estimation problem. We present new, efficient solvers for the minimal problems of this low-rank problem. These solvers are used in a hypothesis and test manne

Demonstration : A cloud-native digital twin with adaptive cloud-based control and intrusion detection

Digital twins are taking a central role in the industry 4.0 narrative. However, they are still illusive. Many aspects of the digital-twins have yet to materialize. For example, to what degree will they be integrated into cloud and industry 4.0 systems as well as how and if they should augment their physical counterpart. Those choices are accompanied by challenging security aspects, many of which h

Estimating nonlinear chirp modes exploiting sparsity

The decomposition of nonlinear chirp modes is a challenging task, typically requiring prior knowledge of the number of modes a signal contains. In this work, we present a greedy nonlinear chirp mode estimation (NCME) technique that forms the used decomposition basis from the signal itself, using an arctangent demodulation technique. The resulting decomposition is formed by considering the residual

Tropospheric ozone radiative forcing uncertainty due to pre-industrial fire and biogenic emissions

pTropospheric ozone concentrations are sensitive to natural emissions of precursor compounds. In contrast to existing assumptions, recent evidence indicates that terrestrial vegetation emissions in the pre-industrial era were larger than in the present day. We use a chemical transport model and a radiative transfer model to show that revised inventories of pre-industrial fire and biogenic emission

Dimensionality reduction in forecasting with temporal hierarchies

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

The Community Inversion Framework v1.0 : A unified system for atmospheric inversion studies

Atmospheric inversion approaches are expected to play a critical role in future observation-based monitoring systems for surface fluxes of greenhouse gases (GHGs), pollutants and other trace gases. In the past decade, the research community has developed various inversion software, mainly using variational or ensemble Bayesian optimization methods, with various assumptions on uncertainty structure

The consolidated European synthesis of CO2emissions and removals for the European Union and United Kingdom : 1990-2018

Reliable quantification of the sources and sinks of atmospheric carbon dioxide (CO2), including that of their trends and uncertainties, is essential to monitoring the progress in mitigating anthropogenic emissions under the Kyoto Protocol and the Paris Agreement. This study provides a consolidated synthesis of estimates for all anthropogenic and natural sources and sinks of CO2 for the European Un

Mapping and Merging Using Sound and Vision : Automatic Calibration and Map Fusion with Statistical Deformations

Over the last couple of years both cameras, audio and radio sensors have become cheaper and more common in our everyday lives. Such sensors can be used to create maps of where the sensors are positioned and the appearance of the surroundings. For sound and radio, the process of estimating the sender and receiver positions from time of arrival (TOA) or time-difference of arrival (TDOA) measurements

High-resolution source localization exploiting the sparsity of the beamforming map

Beamforming technology plays a significant role in source localization and quantification. As traditional delay-and-sum beamformers generally yield low spatial resolution, as well as suffer from the occurrence of spurious sources, different forms of deconvolution methods have been proposed in the literature. In this work, we propose two approaches based on a sparse reconstruction framework combine

Exponential Set-Point Stabilization of Underactuated Vehicles Moving in Three-Dimensional Space

This paper investigates the stabilization of underactuated vehicles moving in a three-dimensional vector space. The vehicle's model is established on the matrix Lie group SE(3), which describes the configuration of rigid bodies globally and uniquely. We focus on the kinematic model of the underactuated vehicle, which features an underactuation form that has no sway and heave velocity. To compensat

Robust image-to-image color transfer using optimal inlier maximization

In this paper we target the color transfer estimation problem, when we have pixel-to-pixel correspondences. We present a feature-based method, that robustly fits color transforms to data containing gross outliers. Our solution is based on an optimal inlier maximization algorithm that maximizes the number of inliers in polynomial time. We introduce a simple feature detector and descriptor based on

Fast solvers for minimal radial distortion relative pose problems

In this paper we present a unified formulation for a large class of relative pose problems with radial distortion and varying calibration. For minimal cases, we show that one can eliminate the number of parameters down to one to three. The relative pose can then be expressed using varying calibration constraints on the fundamental matrix, with entries that are polynomial in the parameters. We can

Polynomial Solvers for Saturated Ideals

In this paper we present a new method for creating polynomialsolvers for problems where a (possibly infinite) subsetof the solutions are undesirable or uninteresting. Thesesolutions typically arise from simplifications made duringmodeling, but can also come from degeneracies which areinherent to the geometry of the original problem.The proposed approach extends the standard action matrixmethod to

The Misty Three Point Algorithm for Relative Pose

There is a significant interest in scene reconstructionfrom underwater images given its utility for oceanic researchand for recreational image manipulation. In this paperwe propose a novel algorithm for two view camera motionestimation for underwater imagery. Our method leveragesthe constraints provided by the attenuation propertiesof water and its effects on the appearance of the color todetermin