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Ego-Motion Recovery and Robust Tilt Estimation for Planar Motion Using Several Homographies

In this paper we suggest an improvement to a recent algorithm for estimating the pose and ego-motion of a camera which is constrained to planar motion at a constant height above the floor, with a constant tilt. Such motion is common in robotics applications where a camera is mounted onto a mobile platform and directed towards the floor. Due to the planar nature of the scene, images taken with such

TOA Sensor Network Calibration for Receiver and Transmitter Spaces with Difference in Dimension

We study and solve the previously unstudied problem of finding both sender and receiver positions from time of arrival (TOA) measurements when there is a difference in dimensionality between the affine subspaces spanned by receivers and senders. Anchor-free TOA network calibration has uses both in sound, radio and radio strength applications. Using linear techniques and requiring only a minimal nu

Important Ice Processes Are Missed by the Community Earth System Model in Southern Ocean Mixed-Phase Clouds : Bridging SOCRATES Observations to Model Developments

Global climate models (GCMs) are challenged by difficulties in simulating cloud phase and cloud radiative effect over the Southern Ocean (SO). Some of the new-generation GCMs predict too much liquid and too little ice in mixed-phase clouds. This misrepresentation of cloud phase in GCMs results in weaker negative cloud feedback over the SO and a higher climate sensitivity. Based on a model comparis

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

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

Detection of left bundle branch block and obstructive coronary artery disease from myocardial perfusion scintigraphy using deep neural networks

Myocardial perfusion scintigraphy, which is a non-invasive imaging technique, is one of the most common cardiological examinations performed today, and is used for diagnosis of coronary artery disease. Currently the analysis is performed visually by physicians, but this is both a very time consuming and a subjective approach. These are two of the motivations for why an automatic tool to support th

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

Skydd för visselblåsare – ett komplext område. Om det rättsliga skyddet för arbetstagare som slår larm om missförhållanden på arbetsplatsen

Syftet med denna uppsats är att granska det rättsliga skyddet för visselblåsare i Sverige. Syftet är även att utreda om eventuella problem som finns med detta skydd löses genom de lagförslag som finns i de offentliga utredningarna SOU 2013:79 och SOU 2014:31. Det finns inte någon lagstiftning i Sverige som specifikt inriktar sig på skydd för visselblåsare. Det rättsliga skyddet är komplext och berThe purpose of this paper is to examine the legal protection of whistleblowers in Sweden. The purpose is also to examine if any problems with this legal protection are solved by the bills in two Government Official Reports – SOU 2013:79 and SOU 2014:31. There is no specific regulation in Swedish law for the protection of whistleblowers. The legal protection is complex and different rules from diff

Methods for Optimal Model Fitting and Sensor Calibration

The problem of fitting models to measured data has been studied extensively, not least in the field of computer vision. A central problem in this field is the difficulty in reliably find corresponding structures and points in different images, resulting in outlier data. This thesis presents theoretical results improving the understanding of the connection between model parameter estimation and pos

Political Theologies at the End of the World

This article engages critically with one of the more original and thought-provoking efforts of recent years to respond philosophically to the current predicament of the world: Thomas Lynch’s 2019 study Apocalyptic Political Theology. While agreeing with Lynch that the urgency of our times calls for more radical approaches than cautious dialogue or reformist adaptation, it nonetheless argues that a

Testing variational estimation of process parameters and initial conditions of an earth system model

We present a variational assimilation system around a coarse resolution Earth System Model (ESM) and apply it for estimating initial conditions and parameters of the model. The system is based on derivative information that is efficiently provided by the ESM's adjoint, which has been generated through automatic differentiation of the model's source code. In our variational approach, the length of

Beyond the Politics of Numbness

Against the backdrop of Gaza and Europe’s muted response, this essay reflects on Elad Lapidot’s challenge to recognize the violence hidden in the language of peace.

Emergency Power for Wind Turbine Yaw System - Project initialization tool

The Yaw Power Backup System (YPBS) is a safety system that needs to be incorporated in the Wind Power Plant (WPP) in order to provide emergency power during a power outage. The YPBS enables the Wind Turbine Generator (WTG) to perform a yawing operation in extreme weather conditions. The yawing operation ensures the rotor is aligned with incoming wind, minimizing the acting forces on the blades and