The use of the required navigation performance (RNP) procedure has been increasing for aircraft navigation, since it allows for better optimisation of the airspace, which is increasingly congested. The present work aims to investigate the application of the functional resonance analysis method (FRAM), combined with the quantitative analysis provided by the Bayesian belief network (BBN), to demonstrate the existing variability in functions that are part of the complex navigation system based on the RNP procedure, specifically when the aircraft approaches the airport (approach phase). As a result, it is possible to analyse the variability that occurs in the studied system and the BBN complemented the study by allowing a quantitative interpretation of the functions considered most important for the execution of an RNP approach procedure.

A Bayesian Belief Network (BBN) for assessing the potential risk of dengue virus emergence and distribution in Western Australia (WA) is presented and used to identify possible hotspots of dengue outbreaks in summer and winter. The model assesses the probabilities of two kinds of events which must take place before an outbreak can occur: (1) introduction of the virus and mosquito vectors to places where human population densities are high; and (2) vector population growth rates as influenced by climatic factors. The results showed that if either Aedes aegypti or Ae. albopictus were to become established in WA, three centres in the northern part of the State (Kununurra, Fitzroy Crossing, Broome) would be at particular risk of experiencing an outbreak. The model can also be readily extended to predict the risk of introduction of other viruses carried by Aedes mosquitoes, such as yellow fever, chikungunya and Zika viruses.

In recent years, cooperation of heterogeneous multiagents (HMAs) has achieved formidable results and gained an increasing attention by researchers. This paper presents an entertainment robot system based on the HMAs' cooperation. This robot is used to distinguish the basic information of a person from the audience and entertain him in the exhibition hall. The main agents include the Arbitration System (AS), the Face Recognition System (FRS), the Position Cognition System (PCS), and the Behavior Planner (BP), which are carved up according to their respective functions. Each agent completes its own task independently and the robot finishes the whole mission through their cooperation. The hybrid control architecture and the data-fusion algorithm based on Bayesian Belief Network are also discussed in this paper.