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Additional file 1. Methods in selection of 8 IRLPs.

NSFC [11171228, 10801111, 10971171]; fundamental Research Funds for the Central University [2010121006]; Natural Science Foundation of Fujian Province of China [2010J05011]

The infiltration kinetics of liquid metal into a fibrous preform was analyzed theoretically on the basis of Darcy's law and the assumptions that the porous preform can be treated as “bundles of capillaries” and that the liquid flow penetrating the preform is laminar. Experiments in infiltration kinetics were carried out with respect to an Al–1.5 Mg aluminium alloy/alumina short fiber preform system. It was revealed that an incubation time is required to activate infiltration, that there is a parabolic dependence of the infiltrated depth on the infiltration time for an infiltration process under constant external pressure, and that the infiltration rate can be well predicted by the equation derived by the theoretical model proposed in the present paper. Both the incubation time and the infiltration rate are influenced significantly by the applied pressure.

Image segmentation is an important processing step in many image, video and computer vision applications. Artificial Immune Systems (AIS) is a diverse area of research that attempts to bridge the divide between immunological and engineering. In this paper, we present a threshold method based on granular immune algorithm (GIA) for image segmentation, which includes granular hierarchy and immunological mechanism. Based on two granular hierarchies, the method can not only execute multi-point parallel search from local to global searching field but also find better solutions with small generation and mean numbers of function values. So this method has better performance in stabilization and convergence that GA. Our experimental results indicate that the proposed method here is very suitable for image segmentation

In recent years, there has been a growth of investigation into the use of artificial immune system as a source of inspiration and metaphor for computational tasks. In this paper, we present a fault diagnosis algorithm based on artificial immune mechanism that can execute multi-point parallel search from local to global searching field and increase the diversity of antigen population and the ability of searching maximum. At last, we apply this algorithm to the fault diagnosis system. Simulation studies show that the proposed method is feasible and recognize the fault correctly.