We propose a method by which the set of linear extensions of an interval order may be partitioned into sets of linear extensions of weak orders, using so-called marked conngurations of the interval order. The technique relies heavily on the natural linear ordering of maximal antichains in interval orders. We also propose a method whereby sets from this partition can be generated with known prob...

Probabilistic inference for Bayesian networks is in general NP-hard using either exact algorithms or approximate methods. However, for very complex networks, only the approximate methods such as stochastic sampling could be used to provide a solution given any time constraint. There are several simulation methods currently available. They include logic sampling the first proposed stochastic met...

Constraint-based modeling has been widely used on metabolic networks analysis, such as biosynthetic prediction and flux optimization. The linear constraints, like mass conservation constraint, reversibility constraint, biological capacity constraint, can be imposed on linear algorithms. However, recently a non-linear constraint based on the second thermodynamic law, known as “loop law”, has eme...

The correct choice of time-step size is of crucial importance in the case of the (2, 4) finite-difference time-domain (FDTD) method, as it affects the algorithm’s overall accuracy and convergence rate. A description of the inherent discretisation error is introduced, which is exploited for the derivation of a simple, yet reliable, approximation of the optimum temporal sampling density. As the p...

Abstract We consider the direct and inverse scattering problems for partially coated obstacles. To this end, we first use the method of integral equations of the first kind together with variational methods to solve a scattering problem for the Helmholtz equation where the scattered field satisfies mixed Dirichletimpedance boundary conditions on the Lipschitz boundary of the scatterer D. We the...

In time-harmonic acoustic fields, energy streamlines are defined as the integral curves of the power-flux density vector, averaged over a period. They provide a tool to visualize the details of propagation of energy. After reviewing the role of energy streamlines in the linear sampling method for acoustic inverse scattering, this work formulates a physical interpretation of the same qualitative...

For the detection of hidden objects by low-frequency electromagnetic imaging the Linear Sampling Method works remarkably well despite the fact that the rigorous mathematical justification is still incomplete. In this work, we give an explanation for this good performance by showing that in the low-frequency limit the measurement operator fulfills the assumptions for the fully justified variant ...

Bird surveys are among the most widely used biodiversity inventories and serve as the basis for an increasing proportion of pure and applied ecological research. It is rarely possible to conduct exhaustive censuses of all individuals present at a particular site, so stopping rules are routinely used to determine when sampling should finish. Most bird survey methods use (implicit) effort-based s...

We describe a new sequential sampling method for constrained multi-way tables, with foundations in linear programming and sequential normal sampling. The method builds on techniques from other sequential algorithms in a way that scales well and can handle more challenging data sets. We apply the new algorithm to data to demonstrate its efficiency.

It is common practice to use weighting, poststratiication, and raking to correct for sampling and nonsampling biases and to improve eeciency of estimation in sample surveys. However, there is no standard method for computing sampling variances of estimates that use these adjustments in combination. In this paper we develop such a method, using three ideas: (1) a general notation that uniies the...