Models and algorithms for detection and tracking of coordinated groups

In this paper, we describe models and algorithms for detection and tracking of group and individual targets. We develop two novel group dynamical models, within a continuous time setting, that aim to mimic behavioural properties of groups. We also describe two possible ways of modeling interactions between closely using Markov Random Field (MRF) and repulsive forces. These can be combined together with a group structure transition model to create realistic evolving group models. We use a Markov Chain Monte Carlo (MCMC)-Particles Algorithm to perform sequential inference. Computer simulations demonstrate the ability of the algorithm to detect and track targets within groups, as well as infer the correct group structure over time. ©2008 IEEE.

Models and algorithms for tracking of maneuvering objects using variable rate particle filters

Standard algorithms in tracking and other state-space models assume identical and synchronous sampling rates for the state and measurement processes. However, real trajectories of objects are typically characterized by prolonged smooth sections, with sharp, but infrequent, changes. Thus, a more parsimonious representation of a target trajectory may be obtained by direct modeling of maneuver times in the state process, independently from the observation times. This is achieved by assuming the state arrival times to follow a random process, typically specified as Markovian, so that state points may be allocated along the trajectory according to the degree of variation observed. The resulting variable dimension state inference problem is solved by developing an efficient variable rate particle filtering algorithm to recursively update the posterior distribution of the state sequence as new data becomes available. The methodology is quite general and can be applied across many models where dynamic model uncertainty occurs on-line. Specific models are proposed for the dynamics of a moving object under internal forcing, expressed in terms of the intrinsic dynamics of the object. The performance of the algorithms with these dynamical models is demonstrated on several challenging maneuvering target tracking problems in clutter. © 2006 IEEE.

Model structure and uncertainty for stochastic non-point source modelling applications

The uncertainty associated with a rainfall-runoff and non-point source loading (NPS) model can be attributed to both the parameterization and model structure. An interesting implication of the areal nature of NPS models is the direct relationship between model structure (i.e. sub-watershed size) and sample size for the parameterization of spatial data. The approach of this research is to find structural limitations in scale for the use of the conceptual NPS model, then examine the scales at which suitable stochastic depictions of key parameter sets can be generated. The overlapping regions are optimal (and possibly the only suitable regions) for conducting meaningful stochastic analysis with a given NPS model. Previous work has sought to find optimal scales for deterministic analysis (where, in fact, calibration can be adjusted to compensate for sub-optimal scale selection); however, analysis of stochastic suitability and uncertainty associated with both the conceptual model and the parameter set, as presented here, is novel; as is the strategy of delineating a watershed based on the uncertainty distribution. The results of this paper demonstrate a narrow range of acceptable model structure for stochastic analysis in the chosen NPS model. In the case examined, the uncertainties associated with parameterization and parameter sensitivity are shown to be outweighed in significance by those resulting from structural and conceptual decisions. © 2011 Copyright IAHS Press.

Representations and algorithms for finite-state bisimulations of linear discrete-time control systems

While a large amount of research over the past two decades has focused on discrete abstractions of infinite-state dynamical systems, many structural and algorithmic details of these abstractions remain unknown. To clarify the computational resources needed to perform discrete abstractions, this paper examines the algorithmic properties of an existing method for deriving finite-state systems that are bisimilar to linear discrete-time control systems. We explicitly find the structure of the finite-state system, show that it can be enormous compared to the original linear system, and give conditions to guarantee that the finite-state system is reasonably sized and efficiently computable. Though constructing the finite-state system is generally impractical, we see that special cases could be amenable to satisfiability based verification techniques. ©2009 IEEE.

On Mixing and Shaking : Structure and Dynamics of Turbulent Stratified Flames

The drive for low emission combustion systems encourages applications using premixed flames. Yet in many applications, considerations of flame stability or mixing times lead to systems with neither premixed nor diffusion flames, which are often called technically premixed or stratified flames. In this talk we discuss the current state of understanding of the effect of mixing and extent of stratification on the structure, microstructure and dynamics of selected turbulent stratified flames. Over the past few years, a significant database of scalar and velocity data has been built to analyze the effects of unmixedness on local and global flame structure. Microscale studies of the flame structures show in detail how the effect of local stratification affects (or not!) the flame structure, flame surface density and scalar dissipation rates, and production of selected species. The experiments place exacting demands on current spectroscopic diagnostics, and reveal the progress and limits to our understanding of turbulent flames in general. The dynamics of stratified flames with respect to instabilities is also shown to be very rich, as the particular shape of the flames and the stabilization points are is significantly affected by the fuel distribution, modifying the rate and location of heat release, and thus the coupling with the surrounding acoustics and determining the onset of self-excitations.

Electronic structure and surface properties of SrBi2Ta2O9 and related oxides

The electronic structure of SrBi2Ta2O9 and related oxides such as SrBi2Nb2O9, Bi2WO6 and Bi3Ti4O12 have been calculated by the tight-binding method. In each case, the band gap is about 4.1 eV and the band edge states occur on the Bi-O layers and consist of mixed O p/Bi s states at the top of the valence band and Bi p states at the bottom of the conduction band. The main difference between the compounds is that Nb 5d and Ti 4d states in the Nb and Ti compounds lie lower than the Ta 6d states in the conduction band. The surface pinning levels are found to pin Schottky barriers 0.8 eV below the conduction band edge.