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The aim of this study is to compare 2 EEG pattern classification methods towards the development of BCI. The methods are: (1) discriminant stepwise, and (2) Principal Component Analysis (PCA)-Linear Discriminant Analysis (LDA) joint method. Both methods use Fisher's LDA approach, but differ in the data dimensionality reduction procedure. Data were recorded from 3 male subjects 20-30 years old. Three runs per subject took place. The classification methods were tested in 240 trials per subject after merging all runs for the same subject. The mental tasks performed were feet, tongue, left hand and right hand movement imagery. In order to avoid previous assumptions on preferable channel locations and frequency ranges, 105 (21 electrodesx5 frequency ranges) electroencephalogram (EEG) features were extracted from the data. The best performance for each classification method was taken into account. The discriminant stepwise method showed better performance than the PCA based method. The classification error by the stepwise method varied between 31.73% and 38.5% for all subjects whereas the error range using the PCA based method was 39.42% to 54%.

Sensitivity analysis methods were used in conjunction with a mathematical model for corrosion pit initiation in the vicinity of MnS inclusions in stainless steel to investigate the relationship between physicochemical parameters and the potential and concentration distributions. The finite difference method with central differences was used to calculate sensitivities. The mathematical model of pit initiation included 20 species plus the potential and 13 physicochemical parameters including rate constants for chemical and electrochemical surface reactions and equilibrium constants for homogeneous reactions. It was found that the potential and concentration profiles are most sensitive to the Tafel slope of the rate of electrochemical dissolution of sulfur-containing inclusions and least sensitive to changes in the equilibrium coefficients of the homogeneous reactions. The rate constant for the electrochemical reaction for dissolution of sulfide inclusions was also found to be significant. The procedure provides a first step toward selecting the most important parameters, designing critical experiments, and selecting the hypothesis that best fits experimental data.