Monte Carlo simulation studies have been carried out for monolayer films formed on the (100) plane of model fcc crystals with different corrugation of the gas-solid potential. It has been demonstrated that the low temperature structure of monolayer films depends strongly on the gas-surface potential corrugation as well as on the size of adsorbed atoms. The effects of the gas-surface potential corrugation on the melting transition have been determined for a series of systems, exhibiting different structure of the solid phase.

Regarding wireless sensor network parameter estimation of the propagation model is a most important issue. Variations of the received signal strength indicator (RSSI) parameter are a fundamental problem of a system based on signal strength. In the present paper, we propose an algorithm based on Bayesian filtering techniques for estimating the path-loss exponent of the log-normal shadowing propagation model for outdoor RSSI measurements. Furthermore, in a series of experiments, we will demonstrate the usefulness of the particle filter for estimating the RSSI data. The stability of this algorithm and the differences in determined path-loss exponent for both method were also analysed. The proposed method of dynamic estimation results in significant improvements of the accuracy of RSSI values when compared with the experimental measurements. It should be emphasised that the path-loss exponent mainly depends on the RSSI data. Our results also indicate that increasing the number of inserted particles does not significantly raise the quality of the estimated parameters.