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This article examines the economic incentives for Europeans to migrate to the so-called 'white man's grave' of West Africa. Ignorance and coercion have been proposed as explanations for migration to high mortality areas. We use data on the Royal African Company and their European employees on the Gold Coast during the period 1707-1740. We found that the employees received a premium above the wage
Measurements with unknown time delays are common in different applications such as microphone array, radio antenna array calibration, where the sources (e.g. sounds) are transmitted in unknown time instants. In this paper, we present a method for estimating unknown time delays from Time-Difference-of-Arrival (TDOA) measurements. We propose a novel rank constraint on a matrix depending on the measu
From at least the Late Neolithic through the end of the Bronze Age and onwards, people continued to inhabit the settlement of Asine. For this reason, the site makes an interesting starting point for discussing long term change. This short paper presents new data on the animal bones from Bronze Age Asine. The data set is used for a zooarchaeological discussion of the site from a diachronic perspect
In modeling unsteady compressible viscous flow problems with the compressible Navier-Stokes equations, time adaptive implicit methods are needed to solve the initial value problems that arise when discretizing the equations in accordance with the method of lines. The methods most used in industrial code today are a family of multistep methods called BDF-methods. Because BDF-methods with higher ord
In this thesis a new method for the numerical solution of coupled systems of ordinary differential equations is investigated. To understand this new method, the workings of existing Waveform iteration methods, in particular the Jacobi and Gauß-Seidel methods were explored first. These methods were introduced to be able to exploit multirate behaviour in systems and use an iterative procedure to suc
This thesis considers the problem of finding an optimal control policy for control problems in continuous time and space, utilising reinforcement learning techniques. Finding analytical solutions to optimal control problems is often intractable due to involved constraints, cost-function objectives, and uncertainty. The focal point will be on reinforcement learning RL techniques to find approximate
At self-similarity the strain history is implicit in and deducible from the strain field at each instance of the loading process. This fact is taken advantage of in a FEM-technique which allows the load to be applied in one single step, only, even when the incremental theory of plastic flow has to be used.Two self-similar problems are solved. Firstly an analytically solvable anti-plane strain crac
A non-Gaussian time series with a generalized Laplace marginal distribution is used to model road topography. The model encompasses variability exhibited by a Gaussian AR(1) process with randomly varying variance that follows a particular autoregressive model that features the gamma distribution as its marginal. A simple estimation method to fit the correlation coefficient of each of two autoregre
This paper contributes to semantic representation of human demonstrated actions for robot execution of time constrained tasks. We propose a semantic action encoding method based on interactions between the subject and objects in the scene. Our semantic framework is enriched with a descriptive spatial reasoning method which leads to accurate segmentation and recognition of unique action primitives.
The max-bisection and min-bisection problems are to find a partition of the vertices of a graph into two equal size subsets that, respectively, maximizes or minimizes the number of edges with endpoints in both subsets. We design the first polynomial time approximation scheme for the max-bisection problem on arbitrary planar graphs solving a long-standing open problem. The method of solution involv
A non-Gaussian time series with a generalized Laplace marginal distribution is used to model road topography. The model encompasses variability exhibited by a Gaussian AR(1) processwith randomly varying variance that follows a particular autoregressive model that features the gamma distribution as its marginal. A simple estimation method to fit the correlation coefficient of each of two autoregres
OBJECTIVES: To define the clinical spectrum time-course and prognosis of non-Asian patients positive for anti-MDA5 antibodies.METHODS: We conducted a multicentre, international, retrospective cohort study.RESULTS: 149 anti-MDA5 positive patients (median onset age 53 years, median disease duration 18 months), mainly females (100, 67%), were included. Dermatomyositis (64, 43%) and amyopathic dermato
Learning semantic-rich representations from raw unlabeled time series data is critical for downstream tasks such as classification and forecasting. Contrastive learning has recently shown its promising representation learning capability in the absence of expert annotations. However, existing contrastive approaches generally treat each instance independently, which leads to false negative pairs tha
Accurate imputation is essential for the reliabilityand success of downstream tasks. Recently, diffusion models haveattracted great attention in this field. However, these models neglect the latent distribution in a lower-dimensional space derivedfrom the observed data, which limits the generative capacityof the diffusion model. Additionally, dealing with the originalmissing data without labels be
The choice of procedure during public procurement is assumed to affect the overall result of the project. When studying the construction industry; delivery methods, payment systems and project specific variables may affect the end result. The question here is if project success is predicted by choice of procurement procedures. A survey was done on 222 road and railroad construction projects in Swe
