No description available.

published_or_final_version / Chemistry / Doctoral / Doctor of Philosophy

published_or_final_version / abstract / toc / Physics / Master / Master of Philosophy

published_or_final_version / abstract / Statistics and Actuarial Science / Doctoral / Doctor of Philosophy

published_or_final_version / Physics / Master / Master of Philosophy

No description available.

In metrology, measurement uncertainty is understood as a range in which the true value of the measurement is likely to fall in. The recent years have seen a rapid development in evaluation of measurement uncertainty. ISO Guide to the Expression of Uncertainty in Measurement (GUM 1995) is the primary guiding document for measurement uncertainty. More recently, the Supplement 1 to the "Guide to the expression of uncertainty in measurement" – Propagation of distributions using a Monte Carlo method (GUM SP1) was published in November 2008. A number of software tools for measurement uncertainty have been developed and made available based on these two documents. The current software tools are mainly desktop applications utilising numeric computation with limited mathematical model handling capacity. A novel and generic web-based application, web-based Knowledge-Based Decision Support System (KB-DSS), has been proposed and developed in this research for measurement uncertainty evaluation. A Model-View-Controller architecture pattern is used for the proposed system. Under this general architecture, a web-based KB-DSS is developed based on an integration of the Expert System and Decision Support System approach. In the proposed uncertainty evaluation system, three knowledge bases as sub-systems are developed to implement the evaluation for measurement uncertainty. The first sub-system, the Measurement Modelling Knowledge Base (MMKB), assists the user in establishing the appropriate mathematical model for the measurand, a critical process for uncertainty evaluation. The second sub-system, GUM Framework Knowledge Base, carries out the uncertainty evaluation process based on the GUM Uncertainty Framework using symbolic computation, whilst the third sub-system, GUM SP1 MCM Framework Knowledge Base, conducts the uncertainty calculation according to the GUM SP1 Framework numerically based on Monte Carlo Method. The design and implementation of the proposed system and sub-systems are discussed in the thesis, supported by elaboration of the implementation steps and examples. Discussions and justifications on the technologies and approaches used for the sub-systems and their components are also presented. These include Drools, Oracle database, Java, JSP, Java Transfer Object, AJAX and Matlab. The proposed web-based KB-DSS has been evaluated through case studies and the performance of the system has been validated by the example results. As an established methodology and practical tool, the research will make valuable contributions to the field of measurement uncertainty evaluation.

No description available.

This research examines how the Targeted Separation Incentive Program, currently underway by the Navy, is being administered to bring about the voluntary separations of junior officers to meet the requirements of the Navyâ s most recent force reduction. This study evaluates the effects of past separation incentive programs as well as the current compensation package that the service-member may receive which is outlined in the Fiscal Year 2006 National Defense Authorization Act. In addition, an analysis was conducted of the costs associated with retaining the service-member versus the personal costs of that individual of leaving. The objective of this thesis is to evaluate the Department of the Navyâ s (DoN) Targeted Separation Incentive Program in order to see if this program can adequately meet the goals of the current force reduction and whether or not savings can be realized through alternative separation programs.

This course project is made up of two parts. Part one is an investigation and implementation of pricing of financial derivatives using numerical methods for the solution of partial differential equations. Part two is an introduction of Monte Carlo methods in financial engineering. The name of course is MA573:Computational Methods in Financial Mathematics, spring 2009, given by Professor Marcel Blais.