In this dissertation, application of multi-way analysis is extended into new areas of environmental chemistry, microbiology, electrochemistry and organometallic chemistry. Additionally new practical aspects of some of the multi-way analysis methods are discussed. Parallel Factor Analysis Two (PARAFAC2) is used to classify a wide range of weathered petroleum oils using GC-MS data. Various chemical and data analysis issues exist in the current methods of oil spill analysis are discussed and the proposed method is demonstrated to have potential to be employed in identification of source of oil spills. Two important practical aspects of PARAFAC2 are exploited to deal with chromatographic shifts and non-diagnostic peaks.GEneralized Multiplicative ANalysis Of VAriance (GEMANOVA) is applied to assess the bactericidal activity of new natural antibacterial extracts on three species of bacteria in different structure and oxidation forms and different concentrations. In this work while the applicability of traditional ANOVA is restricted due to the high interaction amongst the factors, GEMANOVA is shown to return robust and easily interpretable models which conform to the actual structure of the data. Peptide-modified electrochemical sensors are used to determine three metal cations of Cu2+, Cd2+ and Pb2+ simultaneously. Two sets of experiments are performed using a four-electrode system returning a three-way array of size (sample ?? current ?? electrode) and a single electrode resulting in a two-way data set of size (sample ?? current). The data of former is modeled by N-PLS and that latter using PLS. Despite the presence of highly overlapped voltammograms and several sources of non-linearity N-PLS returns reasonable models while PLS fails. An intramolecular hydroamination reaction is catalyzed by several organometallic catalysts to identify the most effective catalysts. The reaction of starting material in the presence of 72 different catalysts is monitored by UV-Vis at two time points, before and after heating the mixtures in an oven. PARAFAC is applied to the three-way data set of (sample ?? wavelength ?? time) to resolve the overlapped UV-Vis peaks and to identify the effective catalysts using the estimated relative concentration of product (loadings plot of the sample mode).

Thesis (Ph.D.)--McMaster University, 2002. / Adviser: P.A. Taylor and John F. MacGregor. Includes bibliographical references. Also available via World Wide Web.

Thesis (Ph.D.)--McMaster University, 2002. / Adviser: P.A. Taylor and John F. MacGregor. Includes bibliographical references. Also available via World Wide Web.

Thesis (M.S.)--Rochester Institute of Technology, 2008. / Typescript. Includes bibliographical references (leaves 70-73).

Thesis (M.S.E.C.E.)--Baylor University, 2007. / Includes bibliographical references (p. 56-58).

Thesis (Ph.D.)--Rochester Institute of Technology, 2008. / Typescript. Includes bibliographical references (p. 175-179) and index.

Includes bibliographical references (p. 162-177).

Thesis (Ph. D.)--University of Florida, 2001. / Title from first page of PDF file. Document formatted into pages; contains xi, 124 p.; also contains graphics. Vita. Includes bibliographical references (p. 120-123).

Η ανάλυση σε κύριες συνιστώσες είναι μια τεχνική μείωσης του δείγματος. Χρησιμοποιείται όταν έχουμε ψηλά συσχετισμένες μεταβλητές. Μειώνει τον αριθμό των αρχικών μεταβλητών σε ένα μικρότερο αριθμό κύριων συνιστωσών που μετρούν τη μεγαλύτερη δυνατή διασπορά του δείγματος. Είναι μια διαδικασία που εφαρμόζεται για μεγάλα δείγματα. Η παραγοντική ανάλυση είναι μια τεχνική μείωσης των μεταβλητών του δείγματος η οποία αναγνωρίζει τον αριθμό των λανθάνουσων δομών και δημιουργεί μια δομή, ένα νέο σύνολο μεταβλητών, τους κοινούς παράγοντες που ερμηνεύουν το δείγμα. Προϋποθέτει μια δομή από μη παρατηρήσιμες μεταβλητές που δεν μπορούν να μετρηθούν άμεσα. Εκτιμά τους παράγοντες εκείνους που έχουν επίδραση και αντανακλούν τις αρχικές μεταβλητές. Επιτρέπει στον ερευνητή να περιγράψει αλλά ακόμη και να αναγνωρίσει τους παράγοντες εκείνους που παριστάνουν το δείγμα. Συμπεριλαμβάνει τους ειδικούς παράγοντες (ειδικά σφάλματα) που οφείλονται για την αναξιοπιστία των μετρήσεων. / Principal component analysis is a technique for reducing the sample, used when we have high correlated variables. It reduces the number of input variables into a smaller number of key components that measure the maximum sample variance. It is a process applied to large samples. Factor analysis is a technique to reduce the variables in the sample that identifies the number of latent structures and creates a structure, a new set of variables, called common factors explaining the sample. Implies a structure of non-observable variables that can not be measured directly. It considers the factors that affect and reflect the original variables. It allows the researcher to describe and even to identify the factors that represent the sample. Includes special factors (specific errors) due to unreliability of measurement.

Geochemistry plays a vital role in our understanding mechanisms behind major geological systems such as the Earth's crust and its oceans (Albarède, F. 2003). More recently, geo-chemistry has played a vital role in the field of forensic investigation and in period dating. Forensic soil samples have been traditionally analysed via examinations of colour, texture and mineral content by physical or chemical methods. However, these methods leave any organic or water-soluble fractions unexamined. Tephrochronology (the dating of sedimentary sequences using volcanic ash layers) is an important tool for the dating and correlation of sedimentary sequences containing archives and proxies of past environmental change. Its importance in this area has increased since the increased free carbon in out atmosphere has made radio-carbon dating unreliable. Tephrochronology requires successful geo-chemical identification of the tephras, a method reliant on electron probe micro-analysis (EPMA) to analyse major element composition. However, it is often impossible to differentiate key tephra layers using EPMA alone. Raman spectroscopy is commonly used in chemistry, since vibrational information is specific to the chemical bonds and symmetry of molecules, and can provide a fingerprint by which these can be identified. Here, we demonstrate how Raman spectroscopy can be used for the successful discrimination of mineral species in tephra through the analysis of individual glass shards. We further demonstrate how, with the use of oxidative preparation methods, Raman spectroscopy can be used to successfully discriminate between soil types using mineralogy as well as the organic and water-soluble fractions of soils.