Transformation Based Ensembles for Time Series Classification

Until recently, the vast majority of data mining time series classification (TSC) research has focused on alternative distance measures for 1-Nearest Neighbour (1-NN) classifiers based on either the raw data, or on compressions or smoothing of the raw data. Despite the extensive evidence in favour of 1-NN classifiers with Euclidean or Dynamic Time Warping distance, there has also been a flurry of recent research publications proposing classification algorithms for TSC. Generally, these classifiers describe different ways of incorporating summary measures in the time domain into more complex classifiers. Our hypothesis is that the easiest way to gain improvement on TSC problems is simply to transform into an alternative data space where the discriminatory features are more easily detected. To test our hypothesis, we perform a range of benchmarking experiments in the time domain, before evaluating nearest neighbour classifiers on data transformed into the power spectrum, the autocorrelation function, and the principal component space. We demonstrate that on some problems there is dramatic improvement in the accuracy of classifiers built on the transformed data over classifiers built in the time domain, but that there is also a wide variance in accuracy for a particular classifier built on different data transforms. To overcome this variability, we propose a simple transformation based ensemble, then demonstrate that it improves performance and reduces the variability of classifiers built in the time domain only. Our advice to a practitioner with a real world TSC problem is to try transforms before developing a complex classifier; it is the easiest way to get a potentially large increase in accuracy, and may provide further insights into the underlying relationships that characterise the problem

Trapped radiation experiment

Trapped radiation detector on Mariner IV space probe measurement of outer Van Allen belt - feasibility of detecting trapped radiation at Mar

Project 7708 understanding heritage crime in Kent and Medway – a data analytical approach

Our research was concerned with the geographical areas of Kent and Medway and involved the spatial and temporal analysis of ‘heritage-specific offences’, ‘targeted heritage crime’ and ‘crime within, at or close to heritage sites’. The crime data consisted of offence type and location details for the 1,122,180 crimes recorded by Kent Police during the period under study. The geographical data we utilised included locations of Conservation Areas, Listed Buildings, Scheduled Monuments, Registered Parks and Gardens, Registered Battlefields, World Heritage Sites, Protected Wreck Sites and ‘Heritage at Risk’ sites in Kent and Medway. Our best estimates suggest that currently approximately one in five Listed Buildings and one in four Places of Worship in Kent and Medway experience some form of crime each year. About one in ten Scheduled Monuments suffer crime, or it occurs nearby. Just over one half of Registered Parks or Gardens have one or more crimes a year within them. For Conservation Areas the proportion is (not unexpectedly) much larger, at closer to four in five. We utilised local Moran’s I to identify spatial clusters at a regional level using LSOA-level crime data. This revealed several LSOAs on the fringes of areas of high levels of crime that could be particularly vulnerable to the spread of crime and therefore heritage-specific locations within these areas could be managed to halt the ‘spread’ of crime towards the periphery of the town. In Kent and Medway Places of Worship (mostly Christian churches) are experiencing increasing numbers of crimes, and this has been particularly the case since around summer 2016. The rate of increase appears higher than that of all other crimes in the same period, both in general and at other heritage locations. There is clear statistical evidence that metal thefts from churches have also been increasing markedly since around summer 2016. The rate of increase appears higher than that of most other crimes. There is statistically significant correlation between metal thefts from churches in Kent and Medway with both the price of lead and mixed brass. Finally, we discovered that machine learning as a method of heritage crime prevention shows promise

Mutation independently affects reproductive traits and dauer larvae development in mutation accumulation lines of Caenorhabditis elegans

Developmental decisions are important in organismal fitness. For the nematode Caenorhabditis elegans, which is naturally found in the ephemeral food patches formed by rotting plant material, correctly committing to dauer or non-dauer larval development is key to genotype survival. To investigate the link between reproductive traits, which will determine how populations grow, and dauer larvae formation, we have analysed these traits in mutation accumulation lines of C. elegans. We find that reproductive traits of individual worms-the total number of progeny and the timing of progeny production-are highly correlated with the population size observed in growing populations. In contrast, we find no relationship between reproduction traits and the number of dauer larvae observed in growing populations. We also do not observe a mutational bias in dauer larvae formation. These results indicate that the control of dauer larvae formation is distinct from the control of reproduction and that differences in dauer larvae formation can evolve rapidly

Absence of martian radiation belts and implications thereof

Absence of electrons in Mars atmosphere and implications thereo

Slip at the edge of complete contacts

We describe an asymptotic method for calculating the size of a zone of partial slip at the edge of a complete contact of arbitrary edge angle and coefficient of friction. Above a critical coefficient of friction the contact remains stuck, and this critical value is explored. A distributed dislocation method is used and the use of different types of numerical quadrature is explored. The size of the slip zone, and its dependence on the contact edge angle and coefficient of friction, are explored

The Evolution of Blue Stragglers Formed Via Stellar Collisions

We have used the results of recent smoothed particle hydrodynamic simulations of colliding stars to create models appropriate for input into a stellar evolution code. In evolving these models, we find that little or no surface convection occurs, precluding angular momentum loss via a magnetically-driven stellar wind as a viable mechanism for slowing rapidly rotating blue stragglers which have been formed by collisions. Angular momentum transfer to either a circumstellar disk (possibly collisional ejecta) or a nearby companion are plausible mechanisms for explaining the observed low rotation velocities of blue stragglers. Under the assumption that the blue stragglers seen in NGC 6397 and 47 Tuc have been created solely by collisions, we find that the majority of these blue stragglers cannot have been highly mixed by convection or meridional circulation currents at anytime during their evolution. Also, on the basis of the agreement between the predictions of our non-rotating models and the observed blue straggler distribution, the evolution of blue stragglers is apparently not dominated by the effects of rotation.Comment: 36 pages, including 1 table and 7 postscript figures (LaTeX2e). Also avaliable at http://astrowww.phys.uvic.ca/~ouellet/ . Accepted for publication in A