Sequential Quantiles via Hermite Series Density Estimation

Sequential quantile estimation refers to incorporating observations into quantile estimates in an incremental fashion thus furnishing an online estimate of one or more quantiles at any given point in time. Sequential quantile estimation is also known as online quantile estimation. This area is relevant to the analysis of data streams and to the one-pass analysis of massive data sets. Applications include network traffic and latency analysis, real time fraud detection and high frequency trading. We introduce new techniques for online quantile estimation based on Hermite series estimators in the settings of static quantile estimation and dynamic quantile estimation. In the static quantile estimation setting we apply the existing Gauss-Hermite expansion in a novel manner. In particular, we exploit the fact that Gauss-Hermite coefficients can be updated in a sequential manner. To treat dynamic quantile estimation we introduce a novel expansion with an exponentially weighted estimator for the Gauss-Hermite coefficients which we term the Exponentially Weighted Gauss-Hermite (EWGH) expansion. These algorithms go beyond existing sequential quantile estimation algorithms in that they allow arbitrary quantiles (as opposed to pre-specified quantiles) to be estimated at any point in time. In doing so we provide a solution to online distribution function and online quantile function estimation on data streams. In particular we derive an analytical expression for the CDF and prove consistency results for the CDF under certain conditions. In addition we analyse the associated quantile estimator. Simulation studies and tests on real data reveal the Gauss-Hermite based algorithms to be competitive with a leading existing algorithm.Comment: 43 pages, 9 figures. Improved version incorporating referee comments, as appears in Electronic Journal of Statistic

Shape memory alloy based smart landing gear for an airship

The design and development of a shape memory alloy based smart landing gear for aerospace vehicles is based on a13; novel design approach. The smart landing gear comprises a landing beam, an arch, and a superelastic nickeltitanium shape memory alloy element. This design is of a generic nature and is applicable to a certain class of light13; aerospace vehicles. In this paper a specixFB01;c case of the shape memory alloy based smart landing gear design and13; development applicable to a radio controlled semirigid airship (radio controlled blimp) of 320 m3 volume is13; presented.Ajudicious combination of carbon xFB01;ber reinforced plastic for the landing beam, cane (naturally occurring13; plant product) wrapped with carbon xFB01;ber reinforced plastic for the arch, and superelastic shape memory alloy is13; used in the development. An appropriate sizing of the arch and landing beam is arrived at to meet the dual requirement of low weight and high-energy dissipation while ndergoing x201C;large elasticx201D; (large nonlinear recoverable13; elastic strain) deformations to ensure soft landings when the airship impacts the ground. The soft landing is required13; to ensure that shock and vibration are minimized (to protect the sensitive payload). The inherently large energydissipating character of the superelastic shape memory alloy element in the tensile mode of deformation and the superior elastic bounce back features of the landing gear provide the ideal solution.Anonlinear analysis based on the classical and xFB01;nite element method approach is followed to analyze the structure. Necessary experiments and tests have been conducted to check the veracity of the design. Good correlation has been found between the analyses and testing. This exercise is intended to provide an alternate method of developing an efxFB01;cient landing gear with satisfactory geometry for a x201C;certain class of light aerospace vehiclesx201D; such as airships, rotorcraft, and other light unmanned air vehicles

Effects of Polyox in Fountain Solution

Polyox is a polymer of ethylene oxide. It is soluble in water and commercially available. The effects of Polyox in fountain solutions were studied and evaluated. The same concentration (one-half percent of Polyox in water) at different pH and blending times, was tested for physical properties and printability. The physical property tests made were of viscosity, surface tension and contact angle. The printability tests were conducted as roll-up, ability to clean up the plate, resistance to scumming, printing sharpness and resolution properties. The experiments were conducted under controlled press conditions and the properties of each test solution were reported. Roll-up, the ability to clean up the plate, and resistance-to-scumming test were repeated five times and the average taken. Printing sharpness and resolution tests at high and low ink film thickness were run two times and 25 samples of each test were taken for obtaining the average. The results show that the effect of Polyox in fountain solution is as good as standard fountain solution

Estimating the Impact of Highways on Average Travel Velocities and Market Size

In this paper we examine the link between additions to highway infrastructure and development of a market area. We do so by first relating highway travel speeds to added highway-mileage and then relating travel speed to the size of the market area. This approach bypasses issues in the public finance literature that derive from estimates of highway infrastructure spending. Also, rather than examining the effects of improved transportation efficiency on enhancements of productivity, this research examines their effect on enhancements in demand for local production. Our thought, which is borne out in the literature, is that industry-level productivity in a metropolitan area may be improved only marginally by lower delivered prices of inputs due to very localized improvements in the freight transportation system. On the other hand, the market for locally produced goods and services will expand somewhat uniformly across industries due to generally improved traffic movements in a metropolitan area. By applying this approach to data from the Texas Transportation Institute, we find a significant but small positive effect of highways and arterials (as opposed to other roadways) on changes in metropolitan urbanized area and metropolitan population change. This suggests that demand for local production may well be enhanced by expansions of highway and principal arterials infrastructure.

A statistical investigation into the properties and dynamics of biological populations experiencing environmental variability

Student Number : 9908888R - MSc research report - School of Statistics and Actuarial Science - Faculty of ScienceMuch research has been devoted towards the understanding of population behaviour. Such understanding has often been furthered through the development of theoretical population models. This research report explores a variety of population models and their implications. The implications of the various models are explored using both analytical results and simulations. Specific aspects of population behaviour studied include gross fluctuation characteristics and extinction probabilities for a population. This research report starts with an overview of Deterministic Models. This is followed by a study of Birth and Death Processes, Branching Processes and Models that incorporate environmental variability. Finally, we study the maximum likelihood approach to population parameter estimation. The more notable theoretical results derived include: the development of models that incorporate the population’s history; models that incorporate discontinuous environmental changes and the development of a means of parameter estimation for a Stochastic Differential Equation

EFFECTIVE MODULUS OF CRACKED BODIES: A FINITE ELEMENT ANALYSIS

This thesis considers how cracks in an elastic body can alter the body’s elastic properties. In the present study the elastic property of note is the elastic or young’s modulus. It is desired to investigate to what extent the number and orientation of cracks can cause a reduction in the elastic modulus. Because of the complex nature of the elastic fields resulting from multiple cracks interacting together in a finite geometry an analytical solution is not possible or considered. Rather the Finite Element Method is used to determine the elastic response to a body with many cracks. This provides a convenient mechanism to study the complex crack geometries and interactions that are currently analyzed. The present study considers purely elastic deformation and uses Linear Elastic Fracture Mechanics (LEFM) where necessary. The goal here is not to calculate the typical Stress Intensity Factors (SIF) of an elastic crack analysis but rather to predict how the presence of multiple interacting cracks of various sizes and configurations will possibly reduce the elastic modulus. Previous research has produced limited definitive results on this topic and the present study attempts to provide some significant concrete data on the elastic modulus reduction if it occurs

Nonparametric Transient Classification using Adaptive Wavelets

Classifying transients based on multi band light curves is a challenging but crucial problem in the era of GAIA and LSST since the sheer volume of transients will make spectroscopic classification unfeasible. Here we present a nonparametric classifier that uses the transient's light curve measurements to predict its class given training data. It implements two novel components: the first is the use of the BAGIDIS wavelet methodology - a characterization of functional data using hierarchical wavelet coefficients. The second novelty is the introduction of a ranked probability classifier on the wavelet coefficients that handles both the heteroscedasticity of the data in addition to the potential non-representativity of the training set. The ranked classifier is simple and quick to implement while a major advantage of the BAGIDIS wavelets is that they are translation invariant, hence they do not need the light curves to be aligned to extract features. Further, BAGIDIS is nonparametric so it can be used for blind searches for new objects. We demonstrate the effectiveness of our ranked wavelet classifier against the well-tested Supernova Photometric Classification Challenge dataset in which the challenge is to correctly classify light curves as Type Ia or non-Ia supernovae. We train our ranked probability classifier on the spectroscopically-confirmed subsample (which is not representative) and show that it gives good results for all supernova with observed light curve timespans greater than 100 days (roughly 55% of the dataset). For such data, we obtain a Ia efficiency of 80.5% and a purity of 82.4% yielding a highly competitive score of 0.49 whilst implementing a truly "model-blind" approach to supernova classification. Consequently this approach may be particularly suitable for the classification of astronomical transients in the era of large synoptic sky surveys.Comment: 14 pages, 8 figures. Published in MNRA

Effects of Arginine on the Kinetics of Bovine Insulin Aggregation Studied by Dynamic Light Scattering

In the fields of protein science and medicine, understanding the kinetics of protein aggregation are significant in the research and treatment of certain amyloid diseases such as Alzheimer’s. Previous studies have suggested that arginine can increase the solubility of certain proteins, suppress protein aggregation, and assist in the refolding of aggregated proteins; however, the molecular mechanisms by which arginine can influence protein aggregation are still unclear. Bovine insulin was employed as a model system for further understanding the effects of arginine on protein aggregation. Using Dynamic Light Scattering (DLS), we studied the concentration-dependent and temperature-dependent suppression of aggregation in insulin by means of arginine. Arginine concentrations from 10mM to 500mM were shown to have produced a concentration-dependent increase in the lag time of the aggregation, which is the period preceding protein aggregation. DLS measurements of insulin in the presence of arginine from 60°C to 85°C showed a significant increase in the aggregation delay for samples with arginine compared to control samples without arginine. Arginine samples were shown to have delayed aggregation by up to a factor of 7.5. From Arrhenius analysis, we also found that the activation energy of 1mM insulin was 17 ± 5 kcal/mol while the energy of the insulin samples with 500mM arginine was higher (26 ± 3 kcal/mol). These energy values are in accordance with the energy associated with β-sheet formation, which is about 0.5 kcal/mol/residue (or ~25 kcal/mol for monomeric insulin). The 9 kcal/mol difference may quantify the barrier effect of arginine on insulin aggregation