The work deals with development and application of Radial basis functions neural networks (RBFNN) for spatial predictions. Geostatistical tools for spatial correlation analysis (variography) are used to qualify and quantify the estimation results. Geostatistical analysis is performed on the residuals obtained at the training and test sample locations. Variogram of residuals explores spatial cor...

This paper presents a SRGM (software reliability growth model) with both change-point and environmental function based on NHPP (non-homogeneous Poisson process). Although a few research projects have been devoted to the change-point problems of SRGMs, consideration of the variation of environmental factors in the existing models during testing time is limited. The proposed model is one of a few...

Findings Wireless sensors are a growing area of research focus. In previous works Niazi and Hussain (2011a, b), a formal model of wireless sensor networks has been given along with an agent-based simulation model. The idea was to use sensing to examine and identify complex behavior such as flocking. The papers also presented a formal specification model is based on the Z formal specification la...

We constructed a Lotka–Volterra-like competition model to study the role of environmental generalists in maintaining ecosystem function under a range of species richnesses and environmental conditions. Ecosystem function was quantified as community biomass, proportion of initial species that coexist through time, and resilience and resistance to perturbation. Generalist and specialist species w...

The evidence is becoming strong that the luminosity function of galaxies varies with environment. Higher density, more dynamically evolved regions appear to have more dwarfs per giant. The situation is becoming clearer as a result of wide field imaging surveys with the CanadaFrance-Hawaii and Subaru telescopes and spectroscopy of faint dwarfs with the Keck telescope. We report here on extensive...