Streamers often constitute the first stage of dielectric breakdown in strong electric fields: a nonlinear ionization wave transforms a nonionized medium into a weakly ionized nonequilibrium plasma. New understanding of this old phenomenon can be gained through modern concepts of (interfacial) pattern formation. As a first step towards an effective interface description, we determine the front w...

We describe a method for pattern extraction by adaptive propagation of a regional threshold to the rest of the image. In most images there is an easily thresholded region. We propagate the regional threshold to the entire image using a linear approximation of the image intensity gradients. This method is useful in the fields where the extraction of precise geometry of the binarized patterns is ...

The objective of this paper is to a design of pattern classification model based on the back-propagation (BP) algorithm for decision support system. Standard BP model has done full connection of each node in the layers from input to output layers. Therefore, it takes a lot of computing time and iteration computing for good performance and less accepted error rate when we are doing some pattern ...

This paper contributes towards engineering self-managing systems, starting from known routing schemes. Routing schemes are self-managing, because they create and maintain a set of distributed states in a dynamic environment, enabling service delivery under various constraints. Using the approach of separating the update propagation from the routing table computation in routing protocols, we con...

The stochastic partial differential equations (SPDEs) stated by Steyn-Ross and co-workers constitute a model of mesoscopic electrical activity of the human cortex. A simplification in which spatial variation and stochastic input are neglected yields ordinary differential equations (ODEs), which are amenable to analysis by techniques of dynamical systems theory. Bifurcation diagrams are develope...

Highly pathogenic avian influenza (HPAI) virus can spread rapidly, resulting in high mortality and severe economic damage. To minimize the damage incurred from such diseases, it is necessary to develop technology for analysing livestock disease and predicting livestock disease propagation. In this study, we propose a novel big data analytics model using extensive volumes of livestock disease oc...

In pattern recognition, statistical modeling, or regression, the amount of data is a critical factor affecting the performance. If the amount of data and computational resources are unlimited, even trivial algorithms will converge to the optimal solution. However, in the practical case, given limited data and other resources, satisfactory performance requires sophisticated methods to regularize...

This paper proposes Neural Network architecture for implementing associative memory. A new model has been developed that has good learning structure and high storage capacity. Hybrid Network Learning comprises interactive counter propagation network and associative memory. Interactive counter propagation network is used for pattern completion. The associative memory is applied for pattern assoc...

We study the propagation of an SIR (susceptible–infectious–recovered) disease over an agent population which, at any instant, is fully divided into couples of agents. Couples are occasionally allowed to exchange their members. This process of couple recombination can compensate the instantaneous disconnection of the interaction pattern and thus allow for the propagation of the infection. We stu...