Most design of experiments assumes predetermined design regions. Design regions with uncertainty are of interest in the first chapter. This chapter proposes optimal designs under a two-part model to handle the uncertainty in the design region. In particular, the logit model in the two-part model is used to assess the uncertainty on the boundary of the design region. The second chapter proposes an efficient and effective multi-layer data collection scheme (Layers of Experiments) for building accurate statistical models to meet tight tolerance requirement commonly encountered in nano-fabrication. "Layers-of-Experiments" (LOE) obtain sub-regions of interest (layer) where the process optimum is expected to lie and collect more data in the sub-regions with concentrated focus. The third chapter contributes a new design criterion combining model-based optimal design and model-free space-filling design in a constraint manner. The proposed design is useful when the fitted statistical model is required to have both characteristics: accuracy in statistical inference and design space exploration. The fourth chapter proposes adaptive combined designs in the layers of experiments. This chapter also develops methods to improve model quality by combining information from various layers and from engineering models. Combined designs are modified to improve its efficiency by incorporate collected field data from several layers of experiments. Updated engineering models are used to build more accurate statistical models.

The central task in phylogenetics is to infer the evolutionary relationships among a given set of species. These relationships are usually represented by a phylogenetic tree with the species of interest at the leaves and where the internal vertices of the tree represent ancestral species. The amount of available molecular data is increasing exponentially and, given the continual advances in sequencing techniques and throughput, this explosive growth will likely continue. These vast amounts of available data mean that biologists are able to assemble large multi-gene datasets for use in phylogenetic analyses, which presents distinct computational challenges. Supertree methods comprise one approach to reconstructing large phylogenies, given estimated trees for overlapping subsets of the entire set of taxa. These source trees are combined into a single supertree on the full set of taxa using various algorithmic techniques. When the data allow, the competing approach is a combined analysis (also known as a “super-matrix” or “total evidence” approach), whereby the different sequence data matrices for each of the different subsets of taxa are put into a single super-matrix, and a tree is estimated on that super-matrix. In this dissertation, I present simulation software I designed to allow users to compare the relative performance of different supertree methods, as well as that of combined analysis, on more realistic data and on a larger scale than has been used up to this point. I present an extensive simulation study that uses this software to compare the performance of supertree methods and combined analysis, and that demonstrates a need for more topologically accurate supertree methods. I also introduce a new supertree method that I have developed that outperforms the most commonly used, and what until now has arguably been the most accurate, supertree method. / text

No description available.

No description available.

No description available.

No description available.

Thesis (Ph. D.)--Drexel University, 2006. / Includes abstract and vita. Includes bibliographical references (leaves 156-161).

Thesis (M.S. in Joint Campaign Planning and Strategy)--Joint Forces Staff College, Joint Advanced Warfighting School, 2006. / "14 APR 2006." Electronic version of original print document. Includes bibliographical references (p. 64-68).

The impetus for the research undertaken in this dissertation hinges on concern for the low priority status attached to aesthetic issues in public deliberation on matters concerning environmental and ethical issues. Although interconnected reasons are identified for the prevalence of this attitude a principal reason is the tendency to assume a conventional understanding of aesthetic value as primarily concern for visual or formal appearance, a consequence of which is that it is treated as of superficial significance only to be considered after more pressing issues have been addressed, for example, economic ones. A ifirther concern, however, is the prevalence in environmental theory/ethics to take a similar view in the way that aesthetic value tends to be considered an unsuitable basis on which to establish an environmental ethic or as of only partial significance in environmental protection and management. While contextualist theorists in environnental aesthetics have made significant contributions in redressing this attitude the discipline is divided between two schools of thought namely scientific cognitivists and non-cognitivists. In arguing against the cognitivist position I develop and advance a non-cognitive approach that focuses on the relational dimension of aesthetic experience and value. Relationship, though largely implicit or assumed in non-cognitive accounts, is undeveloped theoretically particularly as a locus of value in itself I contend that aesthetic value communicates the quality and merit of the relations that given things embody and express. I illustrate how a relational approach raises issues of identity and meaning; issues that are not addressed in environmental theory or mainstream axiological approaches. The significance of the approach rests in its practical and theoretical implication particularly as it bears on the concept of nature; of natural and unnatural value; on issues of beauty, ugliness and sacredness and on the culture/nature dualism predominant in environmental thinking and practice. Moreover, and importantly, a relational approach to aesthetic value extends the reach of environmental aesthetics from a focus on the evaluation of our physical surroundings to a broader, more inclusive view of 'environment' such that its 'reach' can be shown to have ethical import, for example, in issues concerning biotechnological practices.

The objective of this programme of research is to produce a method for assessing and optimising the performance of advanced gas turbine power plants for electricity generation within the Brazilian electric sector. With the privatisation of the Brazilian electric sector, interest has been given to the thermal plants and studies have been carried out along with the use of other alternative fuels rather than fossil fuels. Biomass is a fuel of increasing interest for power generation systems since it is clean and renewable. Essentially all biomass power plants in the Brazilian market today operate on a steam Rankine cycle, which has a poor efficiency. The Brazilian electricity market has paid attention on Biomass integrated gasification gas turbine (BIG/GT) combined cycle plants where solid biomass is gasified. A simple chemical model for representing the gasifier in the power plant is presented and optimisation of the gasification process has been applied. The method for assessing the performance of power plants takes into account not only energy, but it applies the exergy method, which uses the second law of thermodynamics and works out the destruction of energy inside plant components and energy losses rejected to atmosphere. A thermoeconomic model for assessing the power plant has also been described. The optimisation of the assessment method of power plants using exergy and thermoeconomics has been proposed based on genetic algorithms. This new technique has been fairly successful at solving optimisation problems and is easy to implement. The decision of applying genetic algorithms is due to the complexity of the mathematical model applied in the performance assessment of power plants. The assessment of combined cycles like gas / steam cycle, gas / air cycle, gas / steam / freon cycle, gas / air / freon cycle and chemically recuperated gas turbine have been investigated. The application of the overall assessment method helps to understand different and very expensive choices of power plants before making final decisions.