In this paper, we discuss how Bayesian networks can be used to develop automated situation-assessment tools suitable for use as decision aids in a command and control system. Inevitably, the introduction of a new technology raises a number of validation, systems integration and human-factors questions. Those issues pertinent to Bayesian network decision aids are identified and their implications discussed. We then describe in detail the implementation of such a system capable of providing Combat-ID and Threat Assessment advisories in the naval anti-air warfare role and its assessment within a realistic (synthetic) human-in-the-loop experiment. We discuss the experimental system, the experimental design and protocol and the experimental results. In a controlled experiment using 14 subjects with relevant military experience we found that the Bayes' net decision aid system was preferred by the majority of the experimental subjects and led to a number of operator performance improvements which could directly contribute to improved operational effectiveness.

Abstract : In this paper, we discuss how Bayesian networks can be used to develop automated situation-assessment tools suitable for use as decision aids in a command and control system. Inevitably, the introduction of a new technology raises a number of validation, systems integration and human-factors questions. Those issues pertinent to Bayesian network decision aids are identified and their implications discussed. We then describe in detail the implementation of such a system capable of providing Combat-ID and Threat Assessment advisories in the naval anti-air warfare role and its assessment within a realistic (synthetic) human-in-the-loop experiment. We discuss the experimental system, the experimental design and protocol and the experimental results. In a controlled experiment using 14 subjects with relevant military experience we found that the Bayes' net decision aid system was preferred by the majority of the experimental subjects and led to a number of operator performance improvements which could directly contribute to improved operational effectiveness.

The accuracy of tracking can be enhanced by the incorporation of prior information in the form of a local road map. For instance, the performance of ground target tracking algorithms can be improved by incorporating hard constraints (describing roads and junctions) into the tracking model. We describe an approach to enhancing tracking algorithms that uses 'probability fields' to represent the local road map information. The resulting 'Bayes-filter' equations are solved using particle filters and compared with a basic particle filter with no additional map information.

Bayesian networks are a powerful and convenient way of encoding expert knowledge. They can be used to infer such "high-level’ variables as "threat’ or "intent’, given observations, background and intelligence data. However, their usefulness depends on the model, i.e. the Bayesian network used for inference. We demonstrate how Bayesian multinets can be used to simplify the representation of certain complex domains, allowing a decomposition into simpler models that are conditionally independent given a class variable. We illustrate this concept using a threat assessment application, in which each component is specialised to a different class of threat and show how this simplifies model construction and target identification.

This paper presents a Bayesian network framework for situation assessment. The framework is generated from a set of technical requirements that would be a prerequisite for any situation assessment system. It is shown that Bayesian networks readily satisfy these requirements and produce a system that readily fits into the Endsley (1995) description of situation assessment. The framework can also be seen as part of the observe and orientate components of the OODA loop paradigm.

The late-stage demixing following spinodal decomposition of a three-dimensional symmetric binary fluid mixture is studied numerically, using a thermodynamically consistent lattice Boltzmann method. We combine results from simulations with different numerical parameters to obtain an unprecedented range of length and time scales when expressed in reduced physical units. (These are the length and time units derived from fluid density, viscosity, and interfacial tension.) Using eight large (2563) runs, the resulting composite graph of reduced domain size l against reduced time t covers 1 [lsim ] l [lsim ] 105, 10 [lsim ] t [lsim ] 108. Our data are consistent with the dynamical scaling hypothesis that l(t) is a universal scaling curve. We give the first detailed statistical analysis of fluid motion, rather than just domain evolution, in simulations of this kind, and introduce scaling plots for several quantities derived from the fluid velocity and velocity gradient fields. Using the conventional definition of Reynolds number for this problem, Reϕ = ldl/dt, we attain values approaching 350. At Reϕ [gsim ] 100 (which requires t [gsim ] 106) we find clear evidence of Furukawa's inertial scaling (l ∼ t2/3), although the crossover from the viscous regime (l ∼ t) is both broad and late (102 [lsim ] t [lsim ] 106). Though it cannot be ruled out, we find no indication that Reϕ is self-limiting (l ∼ t1/2) at late times, as recently proposed by Grant & Elder. Detailed study of the velocity fields confirms that, for our most inertial runs, the RMS ratio of nonlinear to viscous terms in the Navier–Stokes equation, R2, is of order 10, with the fluid mixture showing incipient turbulent characteristics. However, we cannot go far enough into the inertial regime to obtain a clear length separation of domain size, Taylor microscale, and Kolmogorov scale, as would be needed to test a recent ‘extended’ scaling theory of Kendon (in which R2 is self-limiting but Reϕ not). Obtaining our results has required careful steering of several numerical control parameters so as to maintain adequate algorithmic stability, efficiency and isotropy, while eliminating unwanted residual diffusion. (We argue that the latter affects some studies in the literature which report l ∼ t2/3 for t [lsim ] 104.) We analyse the various sources of error and find them just within acceptable levels (a few percent each) in most of our datasets. To bring these under significantly better control, or to go much further into the inertial regime, would require much larger computational resources and/or a breakthrough in algorithm design.

A simple extension of the Needleman and Wunsch algorithm for aligning pairs of protein sequences allows it to be used for the efficient generation of very large multiple-sequence alignments whose members are similar. This technique could have applications in a broad range of high-volume genomics projects.

A novel method for the identification of correlated pairs in aligned homologous protein sequences is presented and evaluated against a model of simulated protein evolution incorporating covariation. Our method is shown to be capable of identifying all coevolutionary pairs of sites, with minimal interference by background correlations, in aligned sequence sets containing approximately 60 sequences with a tree depth of at least 30 accepted point mutations. This result is expected even in the presence of a large degree of neutral and non-correlated evolution. It is postulated that, since naturally occurring protein families may be subject to stronger selection pressures and a lesser degree of neutral evolution, this method of covariation analysis may be generally more robust than the model would indicate.

This paper describes Ludwig, a versatile code for the simulation of Lattice-Boltzmann (LB) models in 3D on cubic lattices. In fact, Ludwig is not a single code, but a set of codes that share certain common routines, such as I/O and communications. If Ludwig is used as intended, a variety of complex fluid models with different equilibrium free energies are simple to code, so that the user may concentrate on the physics of the problem, rather than on parallel computing issues. Thus far, Ludwig's main application has been to symmetric binary fluid mixtures. We first explain the philosophy and structure of Ludwig which is argued to be a very effective way of developing large codes for academic consortia. Next we elaborate on some parallel implementation issues such as parallel I/O, and the use of MPI to achieve full portability and good efficiency on both MPP and SMP systems. Finally, we describe how to implement generic solid boundaries, and look in detail at the particular case of a symmetric binary fluid mixture near a solid wall. We present a novel scheme for the thermodynamically consistent simulation of wetting phenomena, in the presence of static and moving solid boundaries, and check its performance.

We simulate late-stage coarsening of a 3-D symmetric binary fluid. With reduced units l,t (with scales set by viscosity, density and surface tension) our data extends two decades in t beyond earlier work. Across at least four decades, our own and others' individual datasets (< 1 decade each) show viscous hydrodynamic scaling (l ~ a + b t), but b is not constant between runs as this scaling demands. This betrays either the unexpected intrusion of a discretization (or molecular) lengthscale, or an exceptionally slow crossover between viscous and inertial regimes.

We present simulation results of late-stage coarsening of a 3D symmetric binary fluid using a lattice Boltzmann method on a 256(3) grid. With reduced lengths and times L. T (scales set by viscosity, density and surface tension) our datasets taken together cover 1 < L <10(5) 10 < T < 10(8), equivalent to Reynolds numbers 0.1 < Re < 350.At Re > 100 we find clear evidence of Furukawa's inertial scaling (L proportional to T-2/3), after a very broad crossover from the viscous regime (L proportional to T).

We study a dense solution of an amphiphilic species using the dissipative particle dynamics (DPD) algorithm, focussing on the smectic mesophase. Since DPD is locally momentum-conserving, it gives at large length scales a faithful representation of the isothermal hydrodynamics of the system. Results are presented for the phase diagram of a minimal amphiphile model, consisting of rigid AB dimers in a solution of C monomers, for the coarsening dynamics of a polydomain smectic phase, and for the formation of a monodomain smectic when shear is applied.

Symmetric binary fluids, quenched into a regime of immiscibility, undergo phase separation by spinodal decomposition. In the late stages, the fluids are separated by sharply defined, but curved, interfaces: the resulting Laplace pressure drives fluid flow. Scaling ideas (of Siggia and of Furukawa) predict that, ultimately, this flow should become turbulent as inertial effects dominate over viscous ones. The physics here is complex: mesoscale simulation methods (such as lattice Boltzmann and dissipative particle dynamics) can play an essential role in its elucidation, as we describe. Likewise, it is a matter of experience that immiscible fluids will mix, on some lengthscale at least, if stirred vigorously enough. A scaling theory (of Doi and Ohta) predicts the dependence of a steady state domain size on shear rate, but assumes low Reynolds number (inertia is neglected). Our preliminary simulation results (three-dimensional, so far only on small systems) show little sign of the kind of steady state envisaged by Doi and Ohta; they raise instead the possibility of an oriented domain texture which can continue to coarsen until either inertial effects, or (in our simulations) finite size effects, come into play.

The separation of a binary fluid mixture into its constituent phases involves the interaction of numerous physical phenomena. Studying such a transition gives insight into the underlying mechanisms, their respective strengths and at what stage in the separation each becomes important or dominant. Large scale simulations of three dimensional spinodal decomposition in a binary fluid using Dissipative Particle Dynamics show the approach to a linear time dependence in domain coarsening. We present interface and velocity maps which clearly demonstrate the Siggia mechanism for domain growth.

A study has been made of the density profile of mutually avoiding rod-like particles in the space between two parallel plates, held in equilibrium with a bulk phase of isotropic, semidilute rods, using a self-consistent integral equation which becomes exact as the rod aspect radio L/D → ∞. Computer simulation investigations of finite aspect ratio systems also have been undertaken, and the extended Gibbs adsorption isotherm used to express the free energy (as a function of plate separation) in terms of an integral of the surface excess with respect to chemical potential. This allows thermodynamic properties, such as surface tension and the depletion force between plates, to be found. For L/D → ∞, the results confirm both the thermodynamic consistency of the integral equation, and the accuracy of previous work on the depletion force (based on calculating only the contact density of rods at the walls). To extract thermodynamic data from the simulations, the same Gibbs isotherm method is very efficient, as it utilizes the statistics of the full density profile rather than just the contact density. Precise thermodynamic results for confined rod systems have been obtained from simulation for the first time. Those for L/D = 10 and 20 are shown to be quite close to the predictions for infinite aspect ratio.