The effect of missing data on robust Bayesian spectral analysis

This is the author accepted manuscript. The final version is available from the publisher via the DOI in this record.Published in: Machine Learning for Signal Processing (MLSP), 2013 IEEE International Workshop on Date of Conference: 22-25 Sept. 2013We investigate the effects of missing observations on the robust Bayesian model for spectral analysis introduced by Christmas [2013]. The model assumes Student-t distributed noise and uses an automatic relevance determination prior on the precisions of the amplitudes of the component sinusoids and it is not obvious what their effect will be when some of the otherwise temporally uniformly sampled data is missing

Bayesian Spectral Analysis with Student-t Noise

PublishedArticleWe introduce a Bayesian spectral analysis model for one-dimensional signals where the observation noise is assumed to be Student-t distributed, for robustness to outliers, and we estimate the posterior distributions of the Student-t hyperparameters, as well as the amplitudes and phases of the component sinusoids. The integrals required for exact Bayesian inference are intractable, so we use variational approximation. We show that the approximate phase posteriors are Generalised von Mises distributions of order 2 and that their spread increases as the signal to noise ratio decreases. The model is demonstrated against synthetic data, and real GPS and Wolf’s sunspot data

Inexact Bayesian point pattern matching for linear transformations

PublishedArticleWe introduce a novel Bayesian inexact point pattern matching model that assumes that a linear transformation relates the two sets of points. The matching problem is inexact due to the lack of one-to-one correspondence between the point sets and the presence of noise. The algorithm is itself inexact; we use variational Bayesian approximation to estimate the posterior distributions in the face of a problematic evidence term. The method turns out to be similar in structure to the iterative closest point algorithm.This work was supported by the University of Exeter’s Bridging the Gaps initiative, which was funded by EPSRC award EP/I001433/1 and the collaboration was formed through the Exeter Imaging Network

Variational Bayesian tracking: whole track convergence for large scale ecological video monitoring

This is the author accepted manuscript. The final version is available from the publisher via the DOI in this record.Conference paper: IEEE International Joint Conference on Neural Networks (IJCNN), 4-9 Aug. 2013, Dallas, Texas, USA.Variational Bayesian approximations offer a computationally fast alternative to numerical approximations for Bayesian inference. We examine variational Bayesian methods for filtering and smoothing continuous hidden Markov models, in particular those with sharply-peaked, nonlinear observations densities. We show that, by making variational updates in the correct order, robust convergence to the tracked state may be achieved. We apply the whole track convergence algorithm to tracking wild crickets in video streams and describe how animals may be identified from the characteristics of their tracks. We also show how identifying alphanumeric tags may be read under poor lighting conditions

An Examination of the Feasibility of Linear Deterministic Sea Wave Prediction in Multi-Directional Seas Using Wave Profiling Radar: Theory, Simulation and Sea Trials

This is the final version of the article. Available from the American Meteorological Society via the DOI in this record.For a number of maritime tasks there is a short time period, typically only a few tens of seconds, where a critical event occurs which defines a limiting wave height for the whole operation. Examples are the recovery of fixed and rotary winged aircraft, cargo transfers, final pipe mating in fluid transfer operations and launch/recovery of small craft. The recovery of a 30 ton rescue submersible onto a mother ship in the NATO Submarine Rescue System is a prime example. In such applications short term Deterministic Sea Wave Prediction (DSWP) can play a vital role in extending the sea states under which the system can be safely deployed. DSWP also has great potential in conducting experimental sea wave research at full scale. This report explores the feasibility of using data from an experimental wave profiling radar in achieving DSWP. The report includes theory, simulation and field testing. Two forms of DSWP are employed, a fixed point system based upon a restricted set of wave directions, from which we obtain some success, and the other a fully two dimensional technique, which requires further development. The main finding is that using wave profiling radar for DSWP offers promise but requires improvements both to the spatial reliability and resolution of the wave profiling radar, and to the temporal resolution of its sweep before the technique can be considered to be viable as a usable tool.The authors acknowledge funding from the European Union FP7 and U.K. Ministry of Defence NSRS projects

An update: improvements in imaging perfluorocarbon-mounted plant leaves with implications for studies of plant pathology, physiology, development and cell biology.

Plant leaves are optically complex, which makes them difficult to image by light microscopy. Careful sample preparation is therefore required to enable researchers to maximize the information gained from advances in fluorescent protein labeling, cell dyes and innovations in microscope technologies and techniques. We have previously shown that mounting leaves in the non-toxic, non-fluorescent perfluorocarbon (PFC), perfluorodecalin (PFD) enhances the optical properties of the leaf with minimal impact on physiology. Here, we assess the use of the PFCs, PFD, and perfluoroperhydrophenanthrene (PP11) for in vivo plant leaf imaging using four advanced modes of microscopy: laser scanning confocal microscopy (LSCM), two-photon fluorescence microscopy, second harmonic generation microscopy, and stimulated Raman scattering (SRS) microscopy. For every mode of imaging tested, we observed an improved signal when leaves were mounted in PFD or in PP11, compared to mounting the samples in water. Using an image analysis technique based on autocorrelation to quantitatively assess LSCM image deterioration with depth, we show that PP11 outperformed PFD as a mounting medium by enabling the acquisition of clearer images deeper into the tissue. In addition, we show that SRS microscopy can be used to image PFCs directly in the mesophyll and thereby easily delimit the "negative space" within a leaf, which may have important implications for studies of leaf development. Direct comparison of on and off resonance SRS micrographs show that PFCs do not to form intracellular aggregates in live plants. We conclude that the application of PFCs as mounting media substantially increases advanced microscopy image quality of living mesophyll and leaf vascular bundle cells

Thigh-length compression stockings and DVT after stroke

Controversy exists as to whether neoadjuvant chemotherapy improves survival in patients with invasive bladder cancer, despite randomised controlled trials of more than 3000 patients. We undertook a systematic review and meta-analysis to assess the effect of such treatment on survival in patients with this disease