Separable spatiotemporal priors for convex reconstruction of time-varying 3D point clouds

Reconstructing 3D motion data is highly under-constrained due to several common sources of data loss during measurement, such as projection, occlusion, or miscorrespondence. We present a statistical model of 3D motion data, based on the Kronecker structure of the spatiotemporal covariance of natural motion, as a prior on 3D motion. This prior is expressed as a matrix normal distribution, composed of separable and compact row and column covariances. We relate the marginals of the distribution to the shape, trajectory, and shape-trajectory models of prior art. When the marginal shape distribution is not available from training data, we show how placing a hierarchical prior over shapes results in a convex MAP solution in terms of the trace-norm. The matrix normal distribution, fit to a single sequence, outperforms state-of-the-art methods at reconstructing 3D motion data in the presence of significant data loss, while providing covariance estimates of the imputed points.

Reconstruction of past UV radiation

Solar ultraviolet (UV) radiation has a broad range of effects concerning life on Earth. Soon after the mid-1980s, it was recognized that the stratospheric ozone content was declining over large areas of the globe. Because the stratospheric ozone layer protects life on Earth from harmful UV radiation, this lead to concern about possible changes in the UV radiation due to anthropogenic activity. Initiated by this concern, many stations for monitoring of the surface UV radiation were founded in the late 1980s and early 1990s. As a consequence, there is an apparent lack of information on UV radiation further in the past: measurements cannot tell us how the UV radiation levels have changed on time scales of, for instance, several decades. The aim of this thesis was to improve our understanding of past variations in the surface UV radiation by developing techniques for UV reconstruction. Such techniques utilize commonly available meteorological data together with measurements of the total ozone column for reconstructing, or estimating, the amount of UV radiation reaching Earth's surface in the past. Two different techniques for UV reconstruction were developed. Both are based on first calculating the clear-sky UV radiation using a radiative transfer model. The clear-sky value is then corrected for the effect of clouds based on either (i) sunshine duration or (ii) pyranometer measurements. Both techniques account also for the variations in the surface albedo caused by snow, whereas aerosols are included as a typical climatological aerosol load. Using these methods, long time series of reconstructed UV radiation were produced for five European locations, namely Sodankylä and Jokioinen in Finland, Bergen in Norway, Norrköping in Sweden, and Davos in Switzerland. Both UV reconstruction techniques developed in this thesis account for the greater part of the factors affecting the amount of UV radiation reaching the Earth's surface. Thus, they are considered reliable and trustworthy, as suggested also by the good performance of the methods. The pyranometer-based method shows better performance than the sunshine-based method, especially for daily values. For monthly values, the difference between the performances of the methods is smaller, indicating that the sunshine-based method is roughly as good as the pyranometer-based for assessing long-term changes in the surface UV radiation. The time series of reconstructed UV radiation produced in this thesis provide new insight into the past UV radiation climate and how the UV radiation has varied throughout the years. Especially the sunshine-based UV time series, extending back to 1926 and 1950 at Davos and Sodankylä, respectively, also put the recent changes driven by the ozone decline observed over the last few decades into perspective. At Davos, the reconstructed UV over the period 1926-2003 shows considerable variation throughout the entire period, with high values in the mid-1940s, early 1960s, and in the 1990s. Moreover, the variations prior to 1980 were found to be caused primarily by variations in the cloudiness, while the increase of 4.5 %/decade over the period 1979-1999 was supported by both the decline in the total ozone column and changes in the cloudiness. Of the other stations included in this work, both Sodankylä and Norrköping show a clear increase in the UV radiation since the early 1980s (3-4 %/decade), driven primarily by changes in the cloudiness, and to a lesser extent by the diminution of the total ozone. At Jokioinen, a weak increase was found, while at Bergen there was no considerable overall change in the UV radiation level.

Bayesian inference for multidimensional NMR image reconstruction

Reconstruction of an image from a set of projections has been adapted to generate multidimensional nuclear magnetic resonance (NMR) spectra, which have discrete features that are relatively sparsely distributed in space. For this reason, a reliable reconstruction can be made from a small number of projections. This new concept is called Projection Reconstruction NMR (PR-NMR). In this paper, multidimensional NMR spectra are reconstructed by Reversible Jump Markov Chain Monte Carlo (RJMCMC). This statistical method generates samples under the assumption that each peak consists of a small number of parameters: position of peak centres, peak amplitude, and peak width. In order to find the number of peaks and shape, RJMCMC has several moves: birth, death, merge, split, and invariant updating. The reconstruction schemes are tested on a set of six projections derived from the three-dimensional 700 MHz HNCO spectrum of a protein HasA.

Network reconstruction using knock-out and over-expression data

This paper outlines necessary and sufficient conditions for network reconstruction of linear, time-invariant systems using data from either knock-out or over-expression experiments. These structural system perturbations, which are common in biological experiments, can be formulated as unknown system inputs, allowing the network topology and dynamics to be found. We assume that only partial state measurements are available and propose an algorithm that can reconstruct the network at the level of the measured states using either time-series or steady-state data. A simulated example illustrates how the algorithm successfully reconstructs a network from data. © 2013 EUCA.

The local and global dimensions of metalliferous pollution derived from a reconstruction of an eight thousand year record of copper smelting and mining at a desert-mountain frontier in southern Jordan

Grattan, J.P., Gilbertson, D.D., Hunt, C.O. (2007). The local and global dimensions of metaliferrous air pollution derived from a reconstruction of an 8 thousand year record of copper smelting and mining at a desert-mountain frontier in southern Jordan. Journal of Archaeological Science 34, 83-110

Culture and Security: Symbolic Power and the Politics of International Security : The Reconstruction of Security in the Post-Cold War Era

Williams, Mike, Culture and Security: Symbolic Power and the Politics of International Security (Oxon: Routledge, 2007), pp.xii+172 RAE2008

Palynological perspectives on vegetation survey: a critical step for model-based reconstruction of Quaternary land cover

1. Quantitative reconstruction of past vegetation distribution and abundance from sedimentary pollen records provides an important baseline for understanding long term ecosystem dynamics and for the calibration of earth system process models such as regional-scale climate models, widely used to predict future environmental change. Most current approaches assume that the amount of pollen produced by each vegetation type, usually expressed as a relative pollen productivity term, is constant in space and time.
2. Estimates of relative pollen productivity can be extracted from extended R-value analysis (Parsons and Prentice, 1981) using comparisons between pollen assemblages deposited into sedimentary contexts, such as moss polsters, and measurements of the present day vegetation cover around the sampled location. Vegetation survey method has been shown to have a profound effect on estimates of model parameters (Bunting and Hjelle, 2010), therefore a standard method is an essential pre-requisite for testing some of the key assumptions of pollen-based reconstruction of past vegetation; such as the assumption that relative pollen productivity is effectively constant in space and time within a region or biome.
3. This paper systematically reviews the assumptions and methodology underlying current models of pollen dispersal and deposition, and thereby identifies the key characteristics of an effective vegetation survey method for estimating relative pollen productivity in a range of landscape contexts.
4. It then presents the methodology used in a current research project, developed during a practitioner workshop. The method selected is pragmatic, designed to be replicable by different research groups, usable in a wide range of habitats, and requiring minimum effort to collect adequate data for model calibration rather than representing some ideal or required approach. Using this common methodology will allow project members to collect multiple measurements of relative pollen productivity for major plant taxa from several northern European locations in order to test the assumption of uniformity of these values within the climatic range of the main taxa recorded in pollen records from the region.

Genetic algorithm for shipping route estimation with long-range tracking data : automatic reconstruction of shipping routes based on the historical ship positions for maritime safety applications

Ship tracking systems allow Maritime Organizations that are concerned with the Safety at Sea to obtain information on the current location and route of merchant vessels. Thanks to Space technology in recent years the geographical coverage of the ship tracking platforms has increased significantly, from radar based near-shore traffic monitoring towards a worldwide picture of the maritime traffic situation. The long-range tracking systems currently in operations allow the storage of ship position data over many years: a valuable source of knowledge about the shipping routes between different ocean regions. The outcome of this Master project is a software prototype for the estimation of the most operated shipping route between any two geographical locations. The analysis is based on the historical ship positions acquired with long-range tracking systems. The proposed approach makes use of a Genetic Algorithm applied on a training set of relevant ship positions extracted from the long-term storage tracking database of the European Maritime Safety Agency (EMSA). The analysis of some representative shipping routes is presented and the quality of the results and their operational applications are assessed by a Maritime Safety expert.