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This thesis analyzes the factors that influence the decision of first-term Naval Veterans (NAVETs), who are eligible for reenlistment, to choose to affiliate with the Selected Reserve (SELRES). A model of the determinants of affiliation is specified and estimated using data on active Navy separations and Navy Reserve accessions during the period between 1990 and 2002. The data set analyzed the affiliation decisions of 388,637 NAVETs. Some of the features in the maximum likelihood logit model include the use of rating groups to determine differences in affiliation patterns by occupational categories, determining differences over various time periods, and looking at pay and unemployment rate elasticities across rating groups. Overall, NAVET affiliation in the SELRES is found to depend upon Reserve pay, unemployment rates, census region, gender, race, marital status, dependency status, age at time of separation from active duty, education, mental category, and Navy rating. More specifically, the findings indicate that technical ratings are more responsive to changes in pay than nontechnical ratings, while the unemployment elasticity indicates that affiliation increases with an increase in the unemployment rate. Various time periods were analyzed to determine if the drawdown years of the early 1990s differed from the rest of the sample, and to determine if differences existed during and after the 'dot.com' boom of the late 1990s. In both cases, models in the restricted period were found to be significantly different from the pooled period. Females, Blacks and Hispanics were more likely to affiliate, while those NAVETs who are married, have children, and are older are less likely to affiliate. Finally, there was a significant regional effect in the probability of affiliation.

Recent world events have affected the rates at which the United States Army Reserve (USAR) recruits and retains enlisted members. As these rates fluctuate, it becomes difficult for the USAR to forecast its recruiting requirements. This thesis describes a statistical model and an associated software tool designed to provide precise forecasts of aggregate USAR enlisted personnel trends. In particular, the tool can assist in forecasting specific USAR enlisted end strength requirements using aggregate accession, retention and attrition rates. Entitled the Army Reserve Enlisted Aggregate Flow Model (AREAFM), the tool uses a Markov Growth Model and, for the purposes of this thesis, it is standardized using fiscal year 2001 (FY01) through FY03 data and validated with FY04 data. The AREAFM is intended for annual use in forecasting the number of enlisted accessions required to achieve USAR end strength. The model can also be used to evaluate how adjustments in accession, promotion and attrition rates, perhaps as the result of changes in USAR manpower policies or current events, might affect the assigned strength. / US Army Reserve (USAR) author.

M.Phil. / Coal forms an important role in the energy balance of the world economy. Despite having lost market share to gas in recent years, due to its vast reserves coal will continue to play a massive role in future energy markets. Up to now numerous studies have been completed on the major coal producing countries including South Africa, Australia and the United States. However no in-depth study of the smaller coal producing countries in Africa has been done. This dissertation would first identify the coal producing countries in Africa, estimate the possible reserves of each country and with the use of maps show the location of these reserves. Thereafter this dissertation will evaluate the infrastructure of the different coal producing countries to determine the possible coal export opportunities that exist in these countries. Factors influencing these export opportunities will also be investigated. The study will include South Africa but it will in no way be the focal point. A study of this nature will be extremely informative giving conclusions to the potential coal reserves that exist throughout Africa and will identify the possible export potential of this region.

Contemporary efforts to conserve and restore the marine environment are centred on regulating anthropogenic activities in defined ocean areas through marine protected areas (MPAs). This spatially explicit approach is contingent upon a good understanding of the biology and distribution of species. However, our understanding of many rare and threatened benthic species, for which conservation MPAs are currently being designated, is poor. The fan mussel, Atrina fragilis (Pennant 1777), a rare and vulnerable sessile benthic species that shows a reduced distribution compared to historical accounts, was used as a case species. Identifying the larvae of sessile benthic species is an essential first step in informing their conservation. Here, the first description of larva belonging to A. fragilis is presented along with key life-history traits. A point process modelling framework appropriate for the analysis of presence-only data, along with techniques to address both observer bias and uncertainties with historical occurrence records, were employed to successfully predict the distribution of A. fragilis, revealing potentially important drivers in its current distribution. The transport of A. fragilis larva, taking into account key aspects of life-history, habitat suitability and fine scale hydrodynamics, was modelled to investigate potential levels of connectivity within the Scottish sea area, allowing the potential supply of larvae to areas of suitable habitat and the Scottish MPA network to be evaluated. To date there has been no consideration of the likely effectiveness of measures in most inshore MPAs. Here we assessed the siting of MPAs in relation to fishing intensity and seabed ruggedness on the west coast of Scotland. The results suggest little reduction in fishing pressure is effected by current restrictions on activity in the subset of MPAs investigated, with protection principally being applied to rugged areas that may already act as natural refugia for vulnerable benthic species such as A. fragilis.

Accurately estimating hydrocarbon reserves is important, because it affects every phase of the oil and gas business. Unfortunately, reserves estimation is always uncertain, since perfect information is seldom available from the reservoir, and uncertainty can complicate the decision-making process. Many important decisions have to be made without knowing exactly what the ultimate outcome will be from a decision made today. Thus, quantifying the uncertainty is extremely important. Two methods for estimating original hydrocarbons in place (OHIP) are volumetric and material balance methods. The volumetric method is convenient to calculate OHIP during the early development period, while the material balance method can be used later, after performance data, such as pressure and production data, are available. In this work, I propose a methodology for using a Bayesian approach to quantify the uncertainty of original gas in place (G), aquifer productivity index (J), and the volume of the aquifer (Wi) as a result of combining volumetric and material balance analysis in a water-driven gas reservoir. The results show that we potentially have significant non-uniqueness (i.e., large uncertainty) when we consider only volumetric analyses or material balance analyses. By combining the results from both analyses, the non-uniqueness can be reduced, resulting in OGIP and aquifer parameter estimates with lower uncertainty. By understanding the uncertainty, we can expect better management decision making.

Thesis (Ph. D.)--University of Texas at Austin, 1999. / Vita. Includes bibliographical references (leaves 343-385). Available also in a digital version from Dissertation Abstracts.

Thesis (Ph. D.)--University of Queensland, 2002. / Includes bibliographical references.

Thesis (Ph. D.)--Virginia Polytechnic Institute and State University, 1999. / Paper copy printed by UMI (University Microfilms International), 1999. Includes bibliographical references (p. 94-99). Original electronic version available via Internet.

Thesis (M.A.)--University of Hong Kong, 2001. / Includes bibliographical references.