Fault reconstruction in linear dynamic systems using multivariate statistics

Treasure et al. (2004) recently proposed a new sub space-monitoring technique, based on the N4SID algorithm, within the multivariate statistical process control framework. This dynamic-monitoring method requires considerably fewer variables to be analysed when compared with dynamic principal component analysis (PCA). The contribution charts and variable reconstruction, traditionally employed for static PCA, are analysed in a dynamic context. The contribution charts and variable reconstruction may be affected by the ratio of the number of retained components to the total number of analysed variables. Particular problems arise if this ratio is large and a new reconstruction chart is introduced to overcome these. The utility of such a dynamic contribution chart and variable reconstruction is shown in a simulation and by application to industrial data from a distillation unit.

Improved reliability in diagnosing faults using multivariate statistics

This paper analyses multivariate statistical techniques for identifying and isolating abnormal process behaviour. These techniques include contribution charts and variable reconstructions that relate to the application of principal component analysis (PCA). The analysis reveals firstly that contribution charts produce variable contributions which are linearly dependent and may lead to an incorrect diagnosis, if the number of principal components retained is close to the number of recorded process variables. The analysis secondly yields that variable reconstruction affects the geometry of the PCA decomposition. The paper further introduces an improved variable reconstruction method for identifying multiple sensor and process faults and for isolating their influence upon the recorded process variables. It is shown that this can accommodate the effect of reconstruction, i.e. changes in the covariance matrix of the sensor readings and correctly re-defining the PCA-based monitoring statistics and their confidence limits. (c) 2006 Elsevier Ltd. All rights reserved.

Polarization and Angular Correlation Studies of X-Rays Emitted in Relativistic Ion-Atom Collisions

Particle and photon polarization phenomena occurring in collisions of relativistic ions with matter have recently attracted particular interest. Investiga- tions of the emitted characteristic x-ray and radiative electron capture radiation has been found to be a versatile tool for probing our present understanding of the dynamics of particles in extreme electromagnetic ¯elds. Owing to the progress in x-ray detector technology, in addition, accurate measurements of the linear po- larization for hard x-ray photons as well as the determination of the polarization plane became possible. This new diagnostic tool enables one today to derive in- formation about the polarization of the ion beams from the photon polarization features of the radiative electron capture process.

Multivariate Statistical Analysis Applied to an IL6 Signal Transduction Model in Hepatocytes

This paper introduces the application of linear multivariate statistical techniques, including partial least squares (PLS), canonical correlation analysis (CCA) and reduced rank regression (RRR), into the area of Systems Biology. This new approach aims to extract the important proteins embedded in complex signal transduction pathway models.The analysis is performed on a model of intracellular signalling along the janus-associated kinases/signal transducers and transcription factors (JAK/STAT) and mitogen activated protein kinases (MAPK) signal transduction pathways in interleukin-6 (IL6) stimulated hepatocytes, which produce signal transducer and activator of transcription factor 3 (STAT3).A region of redundancy within the MAPK pathway that does not affect the STAT3 transcription was identified using CCA. This is the core finding of this analysis and cannot be obtained by inspecting the model by eye. In addition, RRR was found to isolate terms that do not significantly contribute to changes in protein concentrations, while the application of PLS does not provide such a detailed picture by virtue of its construction.This analysis has a similar objective to conventional model reduction techniques with the advantage of maintaining the meaning of the states prior to and after the reduction process. A significant model reduction is performed, with a marginal loss in accuracy, offering a more concise model while maintaining the main influencing factors on the STAT3 transcription.The findings offer a deeper understanding of the reaction terms involved, confirm the relevance of several proteins to the production of Acute Phase Proteins and complement existing findings regarding cross-talk between the two signalling pathways.

The role of previous experience and attitudes toward statistics in statistics assessment outcomes among undergraduate psychology students

Previous research has demonstrated that students’ cognitions about statistics are related to their performance in statistics assessments. The purpose of this research is to examine the nature of the relationships between undergraduate psychology students’ previous experiences of maths, statistics and computing; their attitudes toward statistics; and assessment on a statistics course. Of the variables examined, the strongest predictor of assessment outcome was students’ attitude about their intellectual knowledge and skills in relation to statistics at the end of the statistics curriculum. This attitude was related to students’ perceptions of their maths ability at the beginning of the statistics curriculum. Interventions could be designed to change such attitudes with the aim of improving students’ learning of statistics.

Development of a QSPR correlation for the parachor of 1,3-dialkyl imidazolium based ionic liquids

Ionic liquids have received significant interest from both academia and industry for a wide range of applications which often requires knowledge of their thermophysical properties. Quantitative structure-property relationship correlations and group contribution methods for thermophysical properties of ionic liquids are a basic necessity for the development of computer aided molecular design approaches for these liquids and subsequently offer the potential for designing an ionic liquid having a desirable set of thermophysical properties. However, the limited availability of experimental thermophysical data and their quality have prevented the development of such tools. Based on previously reported experimental surface tension data, a correlation of the parachors with the molar volume of the ionic liquids has been developed. The predicted parachor values have been shown to be in good agreement with the experimental data. A maximum deviation of