This research employs a non-parametric, fractional, linear programming method, Data Envelopment Analysis to examine the Customer Service Representative resource allocation efficiency of a major Canadian bank’s model. Two DEA models are proposed, (1) to evaluate the Bank’s national branch network in the context of employment only, by minimizing Full Time Equivalent (FTE) while maximizing over-the-counter (OTC) transaction volume; and (2) to evaluate the efficacy of the Bank’s own model in meeting the desired customer satisfaction benchmarks by maximizing fraction of transactions completed under management’s target time. Non-controllable constant-returns-to-scale and variable-returns to-scale model results are presented and further broken down into branch size segments and geographical regions for analysis. A comparison is conducted between the DEA model results and the Bank’s performance ratios and benchmarks, validating the use of the proposed DEA models for resource allocation efficiency analysis in the banking industry.

Rhizopus oryzae is a filamentous fungi which produces lactic acid and ethanol in fermentations. R. oryzae has numerous advantages for use industrial production of L-(+)-lactic acid but the yield of lactic acid produced on the basis of carbon consumed is low. Metabolic flux analysis of R. oryzae has shown that most of the pyruvate produced at the end of the glycolysis is channelled to ethanol, acetyl-CoA and oxaloacetate production. This study aimed to answer some questions addressed on the regulation of pyruvate branch point in R. oryzae and for this purpose biochemical characterisation of the enzymes acting at this branch point and cloning the genes coding for these enzymes have been done. Pyruvate decarboxylase was purified and characterised for the first time from R. oryzae. The purified enzyme has a Hill coefficient of 1.84 and the Km of the enzyme is 8.6 mM for pyruvate at pH 6.5. The enzyme is inhibited at pyruvate concentrations higher than 30 mM. The optimum pH for enzyme activity shows a broad range from 5.7 and 7.2. The monomer molecular weight was estimated as 59&plusmn / 2 kDa by SDS-PAGE analysis. Pyruvate decarboxylase (pdcA and pdcB) and lactate dehydrogenase (ldhA and ldhB) genes of R. oryzae have been cloned by PCR-cloning approach and the filamentous fungi Aspergillus niger was transformed with these genes. The A. niger transformed with either of the ldh genes of R. oryzae showed enhanced production of lactic acid compared to wild type. Citric acid production was also increased in these transformants while no gluconate production was observed Cloning of hexokinase gene from R. oryzae using degenerate primers was studied by the use of GenomeWalker kit (Clontech). The results of this study were evaluated by using some bioinformatics tools depending on the unassembled clone sequences of R. oryzae genome.

Improvements to highway safety have become a high priority for highway authorities due to increasing public awareness and concern of the high social and economic costs of accidents. However, satisfying this priority in an environment of limited budgets is difficult. It is therefore important to ensure that the funding available for highway safety improvements is efficiently utilized. In attempt to maximize the overall highway safety benefits, highway professionals usually invoke an optimization process. The objective of this thesis study is to develop a model for the selection of appropriate improvements on a set of black spots which will provide the maximum reduction in the expected number of accidents (total return), subject to the constraint that the amount of money needed for the implementation of these improvements does not exceed the available budget. For this purpose, a computer program, BSAP (Black Spot Analysis Program) is developed. BSAP is comprised of two separate, but integrated programs: the User Interface Program (UIP) and the Main Analysis Program (MAP). The MAP is coded in MATLAB and contains the optimization procedure itself and performs all the necessary calculations by using a Binary Integer Optimization model. The UIP, coded in VISUAL BASIC, was used for monitoring the menu for efficient data preparation and providing a user-friendly environment.

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Several techniques were studied to select and prioritize technologies for a complex system. Based on the findings, a method called Pareto Optimization and Selection of Technologies (POST) was formulated to efficiently explore the combinatorial technology space. A knapsack problem was selected as a benchmark problem to test-run various algorithms and techniques of POST. A Monte Carlo simulation using the surrogate models was used for uncertainty quantification. The concepts of graph theory were used to model and analyze compatibility constraints among technologies. A probabilistic Pareto optimization, based on the concepts of Strength Pareto Evolutionary Algorithm II (SPEA2), was formulated for Pareto optimization in an uncertain objective space. As a result, multiple Pareto hyper-surfaces were obtained in a multi-dimensional objective space; each hyper-surface representing a specific probability level. These Pareto layers enabled the probabilistic comparison of various non-dominated technology combinations. POST was implemented on a technology exploration problem for a 300 passenger commercial aircraft. The problem had 29 identified technologies with uncertainties in their impacts on the system. The distributions for these uncertainties were defined using beta distributions. Surrogate system models in the form of Response Surface Equations (RSE) were used to map the technology impacts on the system responses. Computational complexity of technology graph was evaluated and it was decided to use evolutionary algorithm for probabilistic Pareto optimization. The dimensionality of the objective space was reduced using a dominance structure preserving approach. Probabilistic Pareto optimization was implemented with reduced number of objectives. Most of the technologies were found to be active on the Pareto layers. These layers were exported to a dynamic visualization environment enabled by a statistical analysis and visualization software called JMP. The technology combinations on these Pareto layers are explored using various visualization tools and one combination is selected. The main outcome of this research is a method based on consistent analytical foundation to create a dynamic tradeoff environment in which decision makers can interactively explore and select technology combinations.

Phylogenetic models generally assume a homogeneous, time reversible, stationary process. These assumptions are often violated by the real, far more complex, evolutionary process. This thesis is centered on non-homogeneous, lineage-specific, properties of molecular sequences. It consist several related but independent studies. LineageSpecificSeqgen, an extension to the Seq-Gen program, which allows generation of sequences with changes in the proportion of variable sites, is introduced. This program is then used in a simulation study showing that changes in the proportion of variable sites can hinder tree estimation accuracy, and that tree reconstruction under the best-fit model chosen using a relative test can result in a wrong tree. In this case, the less commonly used absolute model-fit was a better predictor of tree estimation accuracy. This study found that increased taxon sampling of lineages that have undergone a change in the proportion of variable sites was critical for accurate tree reconstruction and that, in contrast to some earlier findings, the accuracy of maximum parsimony is adversely affected by such changes. This thesis also addresses the well-known long-branch attraction artifact. A nonparametric bootstrap test to identify changes in the substitution process is introduced, validated, and applied to the case of Microsporidia, a highly reduced intracellular parasite. Microsporidia was first thought to be an early branching eukaryote, but is now believed to be sister to, or included within, fungi. Its apparent basal eukaryote position is considered a result of long-branch attraction due to an elevated evolutionary rate in the microsporidian lineage. This study shows that long-branch estimates and basal positioning of Microsporidia both correlate with increased proportions of radical substitutions in the microsporidian lineage. In simulated data, such increased proportions of radical substitutions leads to erroneous long-branch estimates. These results suggest that the long microsporidian branch is likely to be a result of an increased proportion of radical substitutions on that branch, rather than increased evolutionary rate per se. The focus of the last study is the intriguing case of Mesostigma, a fresh water green alga for which contradicting phylogenetic relationships were inferred. While some studies placed Mesostigma within the Streptophyta lineage (which includes land plants), others placed it as the deepest green algae divergence. This basal positioning is regarded as a result of long-branch attraction due to poor taxon sampling. Reinvestigation of a 13- taxon mitochondrial amino acid dataset and a sub-dataset of 8 taxa reveals that site sampling, and in particular the treatment of missing data, is just as important a factor for accurate tree reconstruction as taxon sampling. This study identifies a difficulty in recreating the long-branch attraction observed for the 8-taxon dataset in simulated data. The cause is likely to be the smaller number of amino acid characters per site in simulated data compared to real data, highlighting the fact that there are properties of the evolutionary process that are yet to be accurately modeled.

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