Using a simple model we investigate how the flow field in a contact binary can alter its topology under the influence of Coriolis forces. In the case studied, closed streamlines form over a relatively large area. This result causes us to review critically the argument that all surface streamlines can meet in a stagnation point, leading to a constant Jacobi energy over the whole surface. A gener...

Adaptive optimal design with a cost constraint is considered, both for nonlinear regression and Bernoulli type experiments, with application in clinical trials. The strong consistency and asymptotic normality of the estimators is proved for designs over a finite space, both when the cost level is fixed, and the adaptive design converges to an optimum constrained design, and when the objective i...

Let an inductive valuation L on the family of binary tries or Patricia tries or digital search trees be defined in the following way: L(t) = L(t,) + L(t,) + R(t), where tc and t, denote the left and right subtrees of t and R depends only on the size (the number of records) 1 t 1 of t. Let LN denote L restricted to the trees of size N. In Theorem 1 we give sufficient conditions on the sequence r...

This fifth installment is devoted to an in-depth study of CA Characteristic Functions, a unified global representation for all 256 one-dimensional Cellular Automata local rules. Except for eight rather special local rules whose global dynamics are described by an affine (mod 1 ) function of only one binary cell state variable, all characteristic functions exhibit a fractal geometry where self-s...

In this paper generation of binary sequences derived from chaotic sequences defined over Z4 is proposed. The six chaotic map equations considered in this paper are Logistic map, Tent Map, Cubic Map, Quadratic Map and Bernoulli Map. Using these chaotic map equations, sequences over Z4 are generated which are converted to binary sequences using polynomial mapping. Segments of sequences of differe...

The Generative T opographicMapping (GTM)was developed and introduced as a principle dalternativ eto the Self-Organising Map for, principally, visualising high dimensional continuous data. There are many cases where the observation data is ordinal and discrete and the application of methods developed speci cally for continuous data is inappropriate. Based on the continuous GTM data model a non-l...

We introduce a novel dynamic model for discrete time-series data, in which the temporal sampling may be nonuniform. The model is specified by constructing a hierarchy of Poisson factor analysis blocks, one for the transitions between latent states and the other for the emissions between latent states and observations. Latent variables are binary and linked to Poisson factor analysis via Bernoul...

We propose a new deep architecture for topic modeling, based on Poisson Factor Analysis (PFA) modules. The model is composed of a Poisson distribution to model observed vectors of counts, as well as a deep hierarchy of hidden binary units. Rather than using logistic functions to characterize the probability that a latent binary unit is on, we employ a Bernoulli-Poisson link, which allows PFA mo...

In this Paper, we worked on the modeling of packet loss within MPLS environment. The research exploited real data from a real network running MPLS as its core switching. The data were obtained from 6 nodes, each node participated with 6 hours of traffic segments used as data set, all nodes formed 36 hours as testing data. Each dataset was divided into one-hour segment, each segment loss and no-...