A number of key areas in IP network engineering, management and surveillance greatly benefit from the ability to dynamically identify traffic flows according to the applications responsible for their creation. Currently such classifications rely on selected packet header fields (e.g. destination port) or application layer protocol decoding. These methods have a number of shortfalls e.g. many ap...

We study buoyancy driven convection in a laterally heated and two dimensional cavity under a uctuating acceleration eld, to model ow conditions in a microgravity environment. In the limit of a large aspect ratio cavity, (the length in the direction perpendicular to the temperature gradient is much larger than in the parallel direction), an analytic solution can be found in which the ow reaches ...

By studying the shape dynamics of three-particle clusters, we investigate the statistical geometry of a spatiotemporally chaotic experimental quasi-two-dimensional flow. We show that when shape and size are appropriately decoupled, these Lagrangian triangles assume statistically stationary shape distributions that depend on the flow scale, with smaller scales favoring more distorted triangles. ...

Knowledge of the fuel flow rate is important for accurate fuel burn and emissions inventory generation and for accurate engine performance modeling. In this paper, machine learning techniques are applied to aircraft flight recorder data to model the fuel flow rate as a function of the aircraft altitude, ground speed, vertical speed, and takeoff mass in the airborne phases of flight. Models are ...

This paper describes a framework for modeling program behavior and applies it to optimizing prescient instruction prefetch–a novel technique that uses helper threads to improve singlethreaded application performance. Spawn-target pair selection is optimized by modeling program behavior with Markov chains and analyzing them with path expression mappings. Mappings for reaching, and posteriori pro...

A recently developed class of models incorporating the cyton model of population generation structure into a conservation-based model of intracellular label dynamics is reviewed. Statistical aspects of the data collection process are quantified and incorporated into a parameter estimation scheme. This scheme is then applied to experimental data for PHA-stimulated CD4+T and CD8+T cells collected...

Numerical and experimental studies of transitional pipe flow have shown the prevalence of coherent flow structures that are dominated by downstream vortices. They attract special attention because they contribute predominantly to the increase of the Reynolds stresses in turbulent flow. In the present study we introduce a convenient detector for these coherent states, calculate the fraction of t...

Fine powders often tend to agglomerate due to van der Waals forces between the particles. These forces can be reduced significantly by covering the particles with nanoscaled adsorbates, as shown by recent experiments. In the present work a quantitative statistical analysis of the effect of powder flow regulating nanomaterials on the adhesive forces in powders is given. Covering two spherical po...

Timelapse microscopy imaging allows for long term monitoring of biological processes however a major bottleneck in assesing experimental outcome is the need for an automated analysis framework to extract essential statistics. In this study, we use Gabor texture descriptors to generate a high dimensional feature space which is analysed with PCA to provide unsupervised characterisation of texture...