The frequency with which acquisitions occur in the South African business environment served as motivation to evaluate the effect of acquisition announcements on the share performance of JSE listed shares. The basis of the study was to use event study methodology to evaluate short term effects as well as to investigate size effects in acquisition announcements. Companies were grouped into small and large companies using market capitalisation as segmentation criteria. To evaluate effects on the share price and volume traded, the market demand curve for traded securities was used. It proved to be a useful tool specifically in the evaluation of smaller companies, where information asymmetry was prevalent. The shift in the demand curve was evaluated by constructing a Demand Curve Variable, which showed the direction (if any) of the change in the demand curve. Acquisition announcements by JSE listed companies over the last seven years were evaluated and confounding events were controlled for. The findings supported the fact that there exist differences in the results of the small and large company samples when making acquisition announcements, and that small companies have more pronounced negative effects subsequent to the announcement of an acquisition. / Dissertation (MBA)--University of Pretoria, 2012. / Gordon Institute of Business Science (GIBS) / unrestricted

Primary goal of this thesis is to present proposed method for fatigue life evaluation applicable to light composite aircraft. The first chapter of this thesis is focused on certification specifications and requirements for fatigue life proof of structure. Significant part of this thesis is dedicated to fatigue life evaluation and guideline how to proceed in evaluation of fatigue data. Thesis also points out on possible methods of statistical fatigue data analysis and critical parts of structure in means of fatigue life. The last part of thesis is focused on design of experimental evaluation of structure including test rig and load sequence. This chapter also provides inside into possible means of introducing artificial defects into the structure.

Absolute quantitative PCR (qPCR) is a method that determines the concentration of DNA in a sample. Accurate, and reproducible quantification is required during forensic DNA processing since the results determine the volume of sample used during STR genotyping. If too little DNA is utilized allelic dropout can occur; if too much DNA is used an increase in the number of artifacts can result. In either case, sub-optimal DNA input-masses can lead to the misinterpretation of the evidentiary profile, by increasing the probability of drop in and/or drop out. Generally, the qPCR method used during forensic DNA processing employs a set of standards, which are run with the questioned samples and used to generate a standard curve. These data are then used to establish a linear equation that is subsequently utilized to estimate the concentration of DNA in the unknown sample. However, standard curves have been shown to be prone to systematic and random error effects that impact the accuracy of the concentration estimate. This study examines two alternative methods to determine the DNA concentration for unknown samples, and compares them to the currently accepted protocol of running new dilutions/standards with every assay. The two alternative methods are: 1) using a validated standard curve, and 2) using linear regression of efficiency. To examine the feasibility of using these two methods for forensic purposes, two samples were quantified, using qPCR, in quadruplicate over the course of three years and concentrations were calculated using all three methods. Effects that time, kit lot, and instrument calibration had on the concentrations was examined for both total human and Y-DNA. Specifically, methods were compared by examining variances in concentration over the three- year period, and contrasting these results with the variances obtained within runs. The method which resulted in the smallest changes in concentration over time was regarded as the most stable. Results show that of the three methods, the use of a validated curve resulted in less variation of DNA concentration between multiple runs. Further, the factor that had the largest impact on concentration variance was the calibration of the instrument. Based on these results, recommendations are provided.

Prior research demonstrates that military service disconnects men from past social and personal disadvantages and thus potentially alters normal life-course patterns of development. Much of this research, however, has been conducted only with World War II veterans. Relatively few studies have examined the influence of military service in Vietnam and its impact on altering individual trajectories of development. Through latent growth curve models, the authors examine the impact of military service in Vietnam on drug use and arrests across the life-course. Longitudinal data collected by the Marion County Youth study (1964-1979) were used to track a sample of men over a 15-year period. Analyses of these data revealed substantial nonrandom selection effects associated with service in Vietnam. Lower-class youths with already established delinquent patterns were significantly more likely to have served in Vietnam. It also appears, however, that service in Vietnam significantly increased individual drug use and, hence, offending rates.

The notation of t/i-numbers is used to describe all possible curves on surfaces.

Thesis (M.M. (Finance & Investment))--University of the Witwatersrand, Faculty of Commerce, Law and Management, Graduate School of Business Administration, 2013. / This thesis addresses the core issue of Funds Transfer Pricing (FTP) that has been brought about by the dynamic nature in the changes in the financial industry. This research has drawn up elements from a systematic historical perspective of how a funds pricing policy has been carried out among the banks. The research has made use of the elements of classical economic theory to formulate a conceptual model that will assist in the understanding of the dynamics of the driving changes in Funds Transfer Prices. In an effort to bridge the theoretical and empirical gap in classical economics and the value chain theory, a simple systematic model was constructed. This model was used to understand the dynamics of future changes in the Funds Transfer Pricing. This was done by first analysing the various components that have influenced the basic elements of the model. The basic elements are the liabilities, assets and the Treasury of banking institutions. The interaction of these elements forms the basis of the Funds Transfer Pricing model that was formulated. Using this model, banking institutions would be able to maximize profits and ensure customer satisfaction at the same time. The simple model proposed handles the problems that are caused by the more complex methods used and offers a practical and simple approach to Funds Transfer Pricing in commercial banks.

Over the past few decades, visualization and application researchers have been investigating vortices and have developed several algorithms for detecting vortex-like structures in the flow. These techniques can adequately identify vortices in most computational datasets, each with its own degree of accuracy. However, despite these efforts, there still does not exist an entirely reliable vortex detection method that does not require significant user intervention. The objective of this research is to solve this problem by introducing a novel vortex analysis technique that provides more accurate results by optimizing the threshold for several computationally-efficient, local vortex detectors, before merging them using the Bayesian method into a more robust detector that assimilates global domain knowledge based on labeling performed by an expert. Results show that when choosing the threshold well, combining the methods does not improve accuracy; whereas, if the threshold is chosen poorly, combining the methods produces significant improvement.

The purpose of this paper is to examine the interactions between two plant species endemic to Florida and develop a model for the growth of one of the plant species. An equation for the growth of Hypericum cumulicola is developed through analyzing how the distance to and the height of the nearest Ceratiola ericoides (Florida rosemary) affects the growth of Hypericum cumulicola. The hypericums were separated into five separate regions according to the distance to the nearest rosemary plant. The parameters for a basic growth equation were obtained in each of the five regions and compared to each other along with the average deviations in each of the five regions. Analysis of the five separate regions aided in the creation of different growth equations that each encompassed all of the regions together. Four different growth equations are developed and then compared and analyzed for their accuracy.

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