In the context of Bayesian Probability Theory, we discuss a model for estimating the plasma ion effective charge Zeff , integrating data from both bremsstrahlung spectroscopy and individual impurity concentrations obtained via Charge Exchange Spectroscopy (CXS). The validity of the model, taking into account statistical as well as systematic uncertainties, is shown via the Deviance Information ...

When we learn of atrocities committed by psychopaths and by suicide terrorists, we are shocked by the evident lack of normal feeling for their fellow human beings. (By suicide terrorists, I mean to include not just the people who have carried out suicide missions, but also the people who plan and organize such attacks.) How could anyone be so callous to the suffering of others? We recognize two...

Synopsis Composite materials are increasingly used in structural applications within the marine industry. Due to the geometric complexity of marine structures, there is a practical requirement that they are assembled by joining smaller component pieces using either mechanical fasteners or adhesive bonding. In this paper Digital Image Correlation (DIC) is used to provide full-field analysis of t...

It has been previously proposed that alkalinity release from sediments can play an important role in the carbonate dynamics on continental shelves, lowering the pCO2 of seawater and hence increasing the CO2 uptake from the atmosphere. To test this hypothesis, sedimentary alkalinity generation was quantified within cohesive and permeable sediments across the North Sea during two cruises in Septe...

Stochastic volatility (SV) models provide useful tools to describe the evolution of asset returns, which exhibit time-varying volatility. This paper extends a basic SV model to capture a leverage effect, a fat-tailed distribution of asset returns and a nonlinear relationship between the current volatility and the previous volatility process. The Bayesian approach with the Markov chain Monte Car...

This paper considers small-area estimation with proportion data, and discusses the choice of upper-level model for the variation over areas. Inference about the random effects for the areas may depend strongly on the choice of this model, but this choice is not a straightforward matter. We show that posterior distributions of the deviances for the competing models provide a valuable tool for th...

Coordination of multiple behaviors independently obtained by a reinforcement learning method is one of the issues in order for the method to be scaled to larger and more complex robot learning tasks. Direct combination of all the state spaces for individual modules (subtasks) needs enormous learning time, and it causes hidden states. This paper presents a method of modular learning which coordi...

Although Di erential Interference Contrast (DIC) microscopy is a powerful visualization tool used to study live biological cells, its use so far has been limited to qualitative observations. The inherent non-linear relation between the object properties and the image intensity makes quantitative analysis di cult. Towards quantitatively measuring optical properties of objects from DIC images, we...

In this thesis, we study the optimal scaling problem for sampling from a target distribution of interest using a random walk Metropolis (RWM) algorithm. In order to implement this method, the selection of a proposal distribution is required, which is assumed to be a multivariate normal distribution with independent components. We investigate how the proposal scaling (i.e. the variance of the no...

prove clinical quality of care and patient safety, lower costs, reduce medical errors, and provide more patient-centered service as well as evidence-based practice. Healthcare costs can spin out of control easily. Misallocation of resources can quickly bring down quality of care, and the evidence for this is sharply increasing. Therefore, it is another challenge to utilize data efficiently and ...