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The ability to quickly acquire 3D models is an essential capability needed in many disciplines including robotics, computer vision, geodesy, and architecture. In this paper we present a novel method for real-time camera tracking and 3D reconstruction of static indoor environments using an RGB-D sensor. We show that by representing the geometry with a signed distance function (SDF), the camera pose
The purpose of this study was to understand what, according to social workers and people with criminal backgrounds in Panama, contributes to change in criminal behaviour amongst delinquent youth with focusing on projects using football, religion and community as changing means. The empirical data was collected according to micro-ethnographical requirements and consisted of twelve hours of observat
This thesis aims to understand the exclusionary process that leads women to be underrepresented in the renewable energy industry in Sweden. Through interviews and a ground theory approach to the analysis of the data, this thesis aims to explore the perception and experiences of women during their higher education in heavy math STEM careers and later their career choices this thesis will provide an
The European Union implements the Environmental Noise Directive (END), which offers a framework for evaluating and assessing environmental noise. All EU members are required to create strategic noise maps to inform the public about noise pollution and its effects. This study followed these directives and guidelines to collect the required data and employed the NORD2000 model to simulate traffic no
This research is investigating the socio-ecological benefits of Indigenous Knowledge in law and decision making, focusing on the inclusion of the indigenous concept Sumak Kawsay, translated to Buen Vivir, and the Constitutional Rights of Nature in Ecuador. The Eurocentric and dominant cultural model has had a monopoly on the production of knowledge ever since the start of colonialism but today'
We consider the statistical sparse jump model, a recently developed, robust and interpretable regime switching model, to identify features that drive the return dynamics of the largest cryptocurrencies. The approach simultaneously performs feature selection, parameter estimation, and state classification. Our large number of candidate features comprises cryptocurrency, sentiment, and financial mar
Introduction Vitamin K has been suggested to have protective effects against progression of vascular calcification and development of cardiovascular disease (CVD). However, few well-powered randomised controlled trials have examined whether vitamin K prevents progression of vascular calcification in individuals from the general population. The aim of the InterVitaminK trial is to investigate the e
Jump models switch infrequently between states to fit a sequence of data while taking the ordering of the data into account We propose a new framework for joint feature selection, parameter and state-sequence estimation in jump models. Feature selection is necessary in high-dimensional settings where the number of features is large compared to the number of observations and the underlying states d
Understanding the loss surface of neural networks is essential for the design of models with predictable performance and their success in applications. Experimental results suggest that sufficiently deep and wide neural networks are not negatively impacted by suboptimal local minima. Despite recent progress, the reason for this outcome is not fully understood. Could deep networks have very few, if
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
Given a network of receivers and transmitters, the process of determining their positions from measured pseudoranges is known as network self-calibration. In this paper we consider 2D networks with synchronized receivers but unsynchronized transmitters and the corresponding calibration techniques, known as Time-Difference-Of-Arrival (TDOA) techniques. Despite previous work, TDOA self-calibration i
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
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
Real-time fault monitoring and control of the Vacuum Assisted Resin Transfer Moulding production process requires knowledge of the position of the epoxy flow-front inside the mould. Therefore, a fast and accurate flow-front tracking system is highly prized. Physics-informed grey-box models deliver a good trade-off between high fidelity and data-driven black-box models for designing such a flow-fro
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
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
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
This study seeks to explore the pragmaticalization process of (it's) no biggie, through a corpus-based taxonomical and statistical examination. The research study involves (i) elaborating a taxonomy of no biggie constructions by exploring the variability of the pragmatic functions and the syntactic features associated with the construction; (ii) monitoring the links between the taxonomical types o
