The application of multivariate statistical methods for understanding food consumer behaviour

Understanding consumer behaviour is a necessary precondition for a targeted communication strategy. The behaviour is a complex phenomenon and research needs to undertake a rigorously apply sophisticated methods. This article entails the combined utilisation of categorical principal component analysis and cluster analysis to determine the major, relatively homogenous consumer groups and this is coupled with confirmatory factor analysis and structural model building to understand consumer behaviour, based on Fishbein and Ajzent’s theoretic model.Categorical principal component analysis, cluster analysis, confirmatory factor analysis, consumers’ segmentation, structural model building, Research Methods/ Statistical Methods,

Optimization of Submerged Arc Welding process Parameters Using PCA-Based Taguchi Approach.

The present study highlights Optimization of submerged arc welding (SAW) process parameters in order to obtain optimal parametric combination to yield favourable weld bead geometry in mild steel plates IS 2062. Taguchi’s L25 orthogonal array (OA) design and signal- to- noise ratio (S/N ratio) have been used in this study.Penetration (P), bead width (W), reinforcement (R) and Percentage dilution (D) are selected as objective functions. The principal component analysis coupled with Taguchi method has been applied to solve this multi response optimization problem. Carried out to meet basic assumption of Taguchi method, individual response correlations have been eliminated first by means of principal component analysis (PCA).The correlated responses then transformed into uncorrelated or independent quality indices called principal components. The principal components converted as single objective function called multiple performance index (MPI). The developed models have checked for adequacy and significance based on ANOVA test. Accuracy of optimization was confirmed by conducting confirmation tests. Results indicate feasibility of Taguchi analysis coupled with principal component analysis (PCA) in continuous improvement in welding industry.Â

A novel methodology to create generative statistical models of interconnects

This paper addresses the problem of constructing a generative statistical model for an interconnect starting from a limited set of S-parameter samples, which are obtained by simulating or measuring the interconnect for a few random realizations of its stochastic physical properties. These original samples are first converted into a pole-residue representation with common poles. The corresponding residues are modeled as a correlated stochastic process by means of principal component analysis and kernel density estimation. The obtained model allows generating new samples with similar statistics as the original data. A passivity check is performed over the generated samples to retain only passive data. The proposed approach is applied to a representative coupled microstrip line example

Modeling meander morphodynamics over self-formed heterogeneous floodplains

This work addresses the signatures embedded in the planform geometry of meandering rivers consequent to the formation of floodplain heterogeneities as the river bends migrate. Two geomorphic features are specifically considered: scroll bars produced by lateral accretion of point bars at convex banks and oxbow lake fills consequent to neck cutoffs. The sedimentary architecture of these geomorphic units depends on the type and amount of sediment, and controls bank erodibility as the river impinges on them, favoring or contrasting the river migration. The geometry of numerically generated planforms obtained for different scenarios of floodplain heterogeneity is compared to that of natural meandering paths. Half meander metrics and spatial distribution of channel curvatures are used to disclose the complexity embedded in meandering geometry. Fourier Analysis, Principal Component Analysis, Singular Spectrum Analysis and Multivariate Singular Spectrum Analysis are used to emphasize the subtle but crucial differences which may emerge between apparently similar configurations. A closer similarity between observed and simulated planforms is attained when fully coupling flow and sediment dynamics (fully-coupled models) and when considering self-formed heterogeneities that are less erodible than the surrounding floodplain