MCS diversity and classifier confidence: A Bayesian approach

Bayes' rule is introduced as a coherent averaging strategy for multiclassifier system (MCS) output, and as a strategy for eliminating the uncertainty associated with a particular choice of classifier-model parameters. We use a Markov-Chain Monte Carlo method for efficient selection of classifiers to approximate the computationally intractable elements of the Bayesian approach --- the set of classifiers so selected is our MCS. Furthermore we exploit the massive sampling (thousands of classifiers) within the Bayesian framework to encompass an estimate of the confidence to be placed in any classification result --- thus providing a sound basis for rejection of some MCS classification results. We present uncertainty envelopes as one way to derive these confidence estimates from the population of classifiers that constitutes the MCS, and we show that as the diversity among component classifiers increases so does the accuracy of confident classification estimates, but diversity is not a panacea. If diversity is increased by elaboration of the data models then care must be taken to fit model sampling and model complexity, otherwise diversity can have the negative effect of leading to excessive numbers of low confidence classifications

Structural disordering in WC thin films induced by SiC additions

An investigation has been conducted into the structural disordering in WC thin films induced by SiC additions. The effect of this disordering on film hardness is also reported. In this investigation, WC-SiC films with a SiC content varying from 11.6 to 38.2 pet were deposited using dual rf magnetron sputtering. The relative Si and W content in the films was determined using electron microprobe analysis. Analysis by X-ray diffraction (XRD) confirmed that, within this compositional range, the film structure transformed from crystalline to amorphous. The XRD patterns showed that the crystalline films consisted primarily of WC1-x, along with a small amount Of W2C; no clear evidence for a separate crystalline SiC phase was found. High-resolution transmission electron microscopy (HRTEM) studies showed that with a lower Si content, the films consisted of crystallites 3 to 5 nm in diameter embedded in an amorphous phase. As the Si content increased, the amorphous phase content increased, both as interlayers between crystallites and as particles within the crystallites. Further Si increases led to a structure consisting of a high density of interconnected amorphous particles within well-defined semicrystalline domains separated by a thin amorphous interlayer. At the highest Si content, a clear two-phase morphology evolved, consisting of two nearly amorphous but distinct phases, which suggests a fine-scale partial-phase separation between the WC and the SiC. At the atomic level, it was found that Si decreased the coherence length within the crystalline phase, resulting in a structure of mixed crystalline/highly disordered phases scaled in the range of 2 to 4 nm. Despite the significant alterations in the film structures due to SiC additions, the hardness and modulus of the films were essentially constant within the compositional range of the transition, although films with SiC contents of less than similar to 11 pet had significantly lower hardness levels. It is proposed that the effects of Si on hardness can be explained in terms of competition between the percolation threshold and the amorphization-inducing effect of Si

Monte Carlo study of the domain growth in nonstoichiometric two-dimensional binary alloys

We use a nearest-neighbor antiferromagnetic Ising model with spin-exchange dynamics to study by Monte Carlo simulations the dynamics of ordering in low-temperature quenched nonstoichiometric A xB 1 − x binary alloys. By implementing the conserved spin-exchange dynamics into the Monte Carlo method the system evolves so that the density is preserved while the order parameter is not. The simulations have been carried out on a two-dimensional square lattice and the stoichiometric value of the composition x is x 0 =0.50. By using different values of x ranging from 0.60≤x≤ x 0 =0.50, we study the influence of the off-stoichiometry on the dynamics of ordering. Regarding the behavior of the excess particles all along the ordering process, we obtain two different regimes. (i) At early to intermediate times the density of excess particles at the interfaces rapidly increases, reaching a saturated value. This density of saturation depends on both composition and temperature. As a consequence of this, since the disorder tends to be localized at the interfaces, the local order inside the growing domains is higher than the equilibrium value. (ii) Once saturation is reached, the system evolves so that the density of excess particles at the interfaces remains constant. During this second regime the excess particles are expelled back to the bulk as the total interface length decreases. We use two different measures for the growth: the total interface length and the structure factor. We obtain that during the second regime scaling holds and the domain-growth process can be characterized, independently on x, by a unique length which evolves according to l(t)∼ t n being n ∼ (0.50–0.40). Although the growth process tends to be slower as x increases, we find that the domain-wall motion follows the main assumptions underlying the Allen-Cahn theory. This is indicative that the coupling between diffusive excess particles and curvature-driven interface motion does not modify the essential time dependence but varies (slows down) the growth rate of the growth law, i.e., l(t)= k 1 / 2 xt , with k x decreasing with x. We suggest that the logarithmic growth experimentally observed in some nonstoichiometric binary materials has to do with the existence of specific interactions (not present in our case) between diffusive particles and domain walls. These interactions are of crucial importance in determining the essential time dependence of the growth law