The incidence of infectious diseases in livestock is a major concern for animal breeders as well as for consumers. As a alternative approach to the use of prophylactic measures or therapeutic agents, infectious diseases can be contended by increasing the disease resistance of animals by genetic improvement. Animals can be selected either on a measure of their resistance (indicator trait) or on the presence or absence of some specific resistance genes in their genotype. A prerequisite to the latter approach is the identification of the genes, or QTL for quantitative trait loci, underlying the trait of interest. By means of sophisticated statistical tools, the QTL mapping strategy combines the information from genetic markers and phenotypic values to dissect quantitative traits into their individual genetic components. Some of the methodological aspects of this strategy are studied in the present thesis in the context of disease resistance in livestock. Indicator traits of the resistance (such as bacteria or parasites counts) are not always satisfying the normality assumption underlying most of the QTL mapping methods. In this context, the ability of statistical tests to identify the underlying genes (i.e. the statistical power) can be considerably reduced. We show that compared to the use of a non-parametric method, the use of the least-squares-based parametric method on mathematically transformed phenotypes gives always the best results. In the context of high number of ties (equal values) as observed when measuring resistance to bacterial or parasitic diseases, the non-parametric test is a good alternative to this approach, as far as midranks are used for ties instead of random ranks. The efficiency of QTL mapping methods can also be increased by use of simple combinations of repeated measurements of the same trait. As a result of analyses performed on real data sets in chicken and sheep, we show that much attention should be paid to obtaining good quality measurements, reflecting at best differences in terms of resistance between animals, before performing a QTL search. The appropriate choice of resistance traits as well as of the time of their measurement are, beside the choice of the method and the quality of marker information, among the most preponderant factors to guarantee satisfying results.

Generally, a design process involves multiple modeling and analysis interaction iterations accommodating changes and verifications. It is convenient to develop generative programs to automate some tedious and repetitive processes in order to minimize cycle times and the engineer’s routine efforts associated with various design stages. The proposed process model incorporates embedded engineering knowledge and generative Computer Aided Design (CAD) and Computer Aided Engineering (CAE) analysis for partial automation of product development. For improved efficiency and ease of operation, the process used a CAD/CAE integration approach with smart program development mechanism for automated modeling and analysis. A CAD/CAE integration method using a Common Data Model (CDM) containing all the required parametric information for both CAD modelling and CAE analysis is implemented. The CDM is used as a parametric data model repository and the supply source of input for those associative entities of CAD and CAE models and thus maintaining the associative dependencies among them. The pro-recorded journal file from the modeling and analysis software tool are used for rapid and easy program development of generative CAD and CAE. / Engineering Design

The field of survival analysis has experienced tremendous growth during the latter half of the 20th century. The methodological developments of survival analysis that have had the most profound impact are the Kaplan-Meier method for estimating the survival function, the log-rank test for comparing the equality of two or more survival distributions, and the Cox proportional hazards (PH) model for examining the covariate effects on the hazard function. The accelerated failure time (AFT) model was proposed but seldom used. In this thesis, we present the basic concepts, nonparametric methods (the Kaplan-Meier method and the log-rank test), semiparametric methods (the Cox PH model, and Cox model with time-dependent covariates) and parametric methods (Parametric PH model and the AFT model) for analyzing survival data.<p> We apply these methods to a randomized placebo-controlled trial to prevent Tuberculosis (TB) in Ugandan adults infected with Human Immunodificiency Virus (HIV). The objective of the analysis is to determine whether TB preventive therapies affect the rate of AIDS progression and survival in HIV-infected adults. Our conclusion is that TB preventive therapies appear to have no effect on AIDS progression, death and combined event of AIDS progression and death. The major goal of this paper is to support an argument for the consideration of the AFT model as an alternative to the PH model in the analysis of some survival data by means of this real dataset. We critique the PH model and assess the lack of fit. To overcome the violation of proportional hazards, we use the Cox model with time-dependent covariates, the piecewise exponential model and the accelerated failure time model. After comparison of all the models and the assessment of goodness-of-fit, we find that the log-logistic AFT model fits better for this data set. We have seen that the AFT model is a more valuable and realistic alternative to the PH model in some situations. It can provide the predicted hazard functions, predicted survival functions, median survival times and time ratios. The AFT model can easily interpret the results into the effect upon the expected median duration of illness for a patient in a clinical setting. We suggest that the PH model may not be appropriate in some situations and that the AFT model could provide a more appropriate description of the data.

Phosphate is one of the essential minerals for all living organisms. It has to be supplied to the soil in order for plant growth. In Turkey, most of the soils lack phosphate mineral. Although this can be overcome by the use of phosphate fertilizers, in Turkey there are no phosphate mines being utilized / and this brings about the need to import phosphate rock and phosphate fertilizers. The estimated phosphate rock reserve of Turkey is around 300 million tons, but it cannot be utilized since no economical method of upgrading has been proved to work yet. The aim of this study has been two-fold / to determine the effects of several parameters on the cell flotation of Mardin-Mazidagi phosphate rock and to increase the grade of the product above 30% P2O5 content with a reasonable recovery rate, so that it could be used commercially. Phosphate rock upgrading was made by using flotation in a cell. There are many factors affecting the recovery and grade of the product such as, particle size, pulp pH, collector volume, acid and collector conditioning times and temperature. Phosphate rock samples used contained 14% P2O5, 43% CaCO3 and 1% SiO2 with a CaO/P2O5 ratio of 3.1. Due to the low silica content, one-stage flotation was made. In the experiments, effects of the important parameters were tested at constant pulp density (10% solids by weight). Particle sizes were between 53 m and 150 m, while the pH values were kept between 5,0 - 6,5 using amounts of acid within the range of 6 - 19 kg H3PO4/ton of rock. The collector (mixture of kerosene and oleic acid in 1:3 volumetric ratio) was used in the range of 0,6 ml (0,96 kg collector/ton rock) and 5,4 ml (8,64 kg collector/ton rock). Acid and collector conditioning times were changed between 10-110 s and 10-80 s, respectively. The temperature range was between 15-35 &deg / C. At the end of the parametric studies a grade of 36% P2O5 with a recovery of 93% could be obtained.

This thesis addresses the need for flexible parametric design tools. It focuses on the implementation of a particular tool, Bentley Systems' Generative Components, by exploring features, strengths and weaknesses, and how features can be implemented in design. An exposition of Generative Components is introduced to bridge the gap between the potential and existing power of parametric tools. Through a case study of the Bahá'í Temple for South America this thesis explores the implementation of Generative Components. The exposition argues for the validity of parametric research, specifically its ability to streamline and enhance an architectural design process. <br /><br /> The topic of parametric design is further documented in a survey submitted to researchers and developers in the field of parametric research and design. The purpose of this documentation is to place the progression of parametric tools within the context of current development, initiating an open-ended discussion focusing on future research. <br /><br /> This thesis adds to the current development of parametric technology by making particular contributions to tools within the realm of parametric research. Primary contributions include array seeking scripts that search for and replace or duplicate objects, routines for nesting functions within scripts, ideological workflow development and conceptual training through practical application.

This thesis addresses the need for flexible parametric design tools. It focuses on the implementation of a particular tool, Bentley Systems' Generative Components, by exploring features, strengths and weaknesses, and how features can be implemented in design. An exposition of Generative Components is introduced to bridge the gap between the potential and existing power of parametric tools. Through a case study of the Bahá'í Temple for South America this thesis explores the implementation of Generative Components. The exposition argues for the validity of parametric research, specifically its ability to streamline and enhance an architectural design process. <br /><br /> The topic of parametric design is further documented in a survey submitted to researchers and developers in the field of parametric research and design. The purpose of this documentation is to place the progression of parametric tools within the context of current development, initiating an open-ended discussion focusing on future research. <br /><br /> This thesis adds to the current development of parametric technology by making particular contributions to tools within the realm of parametric research. Primary contributions include array seeking scripts that search for and replace or duplicate objects, routines for nesting functions within scripts, ideological workflow development and conceptual training through practical application.

The field of survival analysis has experienced tremendous growth during the latter half of the 20th century. The methodological developments of survival analysis that have had the most profound impact are the Kaplan-Meier method for estimating the survival function, the log-rank test for comparing the equality of two or more survival distributions, and the Cox proportional hazards (PH) model for examining the covariate effects on the hazard function. The accelerated failure time (AFT) model was proposed but seldom used. In this thesis, we present the basic concepts, nonparametric methods (the Kaplan-Meier method and the log-rank test), semiparametric methods (the Cox PH model, and Cox model with time-dependent covariates) and parametric methods (Parametric PH model and the AFT model) for analyzing survival data.<p> We apply these methods to a randomized placebo-controlled trial to prevent Tuberculosis (TB) in Ugandan adults infected with Human Immunodificiency Virus (HIV). The objective of the analysis is to determine whether TB preventive therapies affect the rate of AIDS progression and survival in HIV-infected adults. Our conclusion is that TB preventive therapies appear to have no effect on AIDS progression, death and combined event of AIDS progression and death. The major goal of this paper is to support an argument for the consideration of the AFT model as an alternative to the PH model in the analysis of some survival data by means of this real dataset. We critique the PH model and assess the lack of fit. To overcome the violation of proportional hazards, we use the Cox model with time-dependent covariates, the piecewise exponential model and the accelerated failure time model. After comparison of all the models and the assessment of goodness-of-fit, we find that the log-logistic AFT model fits better for this data set. We have seen that the AFT model is a more valuable and realistic alternative to the PH model in some situations. It can provide the predicted hazard functions, predicted survival functions, median survival times and time ratios. The AFT model can easily interpret the results into the effect upon the expected median duration of illness for a patient in a clinical setting. We suggest that the PH model may not be appropriate in some situations and that the AFT model could provide a more appropriate description of the data.

Recent hurricanes in the Gulf of Mexico (e.g., Ivan, Dennis, Katrina, Rita and Ike) were observed to develop wave conditions that were near or exceeded the predicted 100-year conditions. As a result, many offshore facilities, as well as coastal infrastructure, which were designed to withstand the 100-year condition, were damaged. New estimates of extreme conditions, which incorporate recently observed maxima, are needed to provide better guidelines for design of coastal and offshore structures. Berek et al. (2007) have used modeled data to develop new criteria, but these estimates can be very sensitive to the data and to the statistical methods used in the development. Berek's estimates also do not cover the entire Gulf of Mexico. We have developed updated estimates of the 100-year extreme wave conditions for the entire Gulf of Mexico using a more comprehensive approach. First, the applicability of standard parametric wind models was examined and appropriate adjustments to the Rankine vortex model were developed to reduce the wind field errors during hurricane conditions. The adjusted winds reduced the error by up to 25 percent compared to the original Rankine vortex model. To obtain reliable wave data, merged wind fields were generated using the NCEP/NCAR Reanalysis 1 project modeled wind data for background wind and the parametric wind model for hurricane conditions. Next, the SWAN wave model was used for the 51-year period from 1958 to 2008 along with multiple statistical methods (Gumbel, Weibull and GEV-Generalized Extreme Value distribution). The effect of the recent hurricane season (2004-2008) shows that maximum 100-year wave height values and their distribution changes. A resampling technique (bootstrap) is used to evaluate and select the optimum statistical method to estimate more appropriate extreme wave conditions.

System level parametric design of hybrid electric vehicles involves estimation of the power ratings as well as the values of certain parameters of the components, given the values of the performance parameters. The design is based on certain mathematical equations or ‘design rules’, which relate the component parameters and the performance parameters. The flow of the design algorithm is uni-directional and fixed, and cannot be altered. This thesis proposes a new method for such parametric design, called omni- directional design, which does not have a fixed sequence like the conventional design, but can start with any parameters of the designer’s choice. The designer is also able to specify the input parameters over a range, instead of a point (one, fixed value) input. Scenarios having a point input, but values of an output which can vary over a range for the point input, can also be studied.

The purpose of the study is to better understand the factors that affect melt-wear in the armature-to-rail contact interface of an electromagnetic launcher (EML). In order to investigate the factors, the study uses finite element analysis (FEA) to vary parameters of a lab-scale EML at the Georgia Institute of Technology. FEA is used due to the complex nature of the system, which includes the geometry and various engineering aspects that the EML incorporates. The study focuses on an uncoupled analysis of the structural, electromagnetic (EMAG), thermal, and modal aspects. The reason for the uncoupled analysis was because the system was complex and there were computational limits. Also, by uncoupling the analysis fields, the way the parameters affected melt-wear could be viewed separately. The study varied the geometry of the armature, the stiffness of the rail system (compliance layer), and the material of the armature. The structural analysis was for the initial contact of the rail to the armature and found the von Mises stresses, contact area, and contact pressure. The EMAG analysis found the Lorentz forces in the system based on a current curve used in the lab-scale EML. The thermal analysis consisted of friction heating and Joule heating. The modal analysis was for the unstressed and pre-stressed armature. Based on the study conducted, it was found that aluminum would provide the best speeds due to its lighter mass, but lacked in the thermal resistance area. Tungsten provided the better thermal resistance, but lacked in the potential speed due to its heavier mass.