No description available.

Thesis (PhD)--University of South Australia, 2000

Report (M.S.)--Virginia Polytechnic Institute and State University. M.S. 1992. / Abstract. Includes bibliographical references (leaves 94-97). Also available via the Internet.

University, Diss., 2006--Würzburg.

Thesis (M. Phil.)--University of Hong Kong, 2006. / Title proper from title frame. Also available in printed format.

Techn. University, Diss., 2003--Chemnitz.

In this thesis, we propose a methodology for choosing optimal mixed-level fractional factorial robust parameter designs when experiments involve both qualitative factors and quantitative factors. At the beginning, a brief review of fractional factorial designs and two-level robust parameter designs is given to help understanding our method. The minimum aberration criterion, one of the most commonly used criterion for design selection, is introduced. We modify this criterion and develop two generalized minimum aberration criteria for selecting optimal mixed-level fractional factorial robust parameter designs. Finally, we implement an effective computer program. A catalogue of 18-run optimal designs is constructed and some results are given. / February 2016

Road pricing has emerged as an effective means of managing road traffic demand while simultaneously raising additional revenues to transportation agencies. Research on the factors that govern travel decisions has shown that user preferences may be a function of the demographic characteristics of the individuals and the perceived trip attributes. However, it is not clear what are the actual trip attributes considered in the travel decision- making process, how these attributes are perceived by travelers, and how the set of trip attributes change as a function of the time of the day or from day to day. In this study, operational Intelligent Transportation Systems (ITS) archives are mined and the aggregated preferences for a priced system are extracted at a fine time aggregation level for an extended number of days. The resulting information is related to corresponding time-varying trip attributes such as travel time, travel time reliability, charged toll, and other parameters. The time-varying user preferences and trip attributes are linked together by means of a binary choice model (Logit) with a linear utility function on trip attributes. The trip attributes weights in the utility function are then dynamically estimated for each time of day by means of an adaptive, limited-memory discrete Kalman filter (ALMF). The relationship between traveler choices and travel time is assessed using different rules to capture the logic that best represents the traveler perception and the effect of the real-time information on the observed preferences. The impact of travel time reliability on traveler choices is investigated considering its multiple definitions. It can be concluded based on the results that using the ALMF algorithm allows a robust estimation of time-varying weights in the utility function at fine time aggregation levels. The high correlations among the trip attributes severely constrain the simultaneous estimation of their weights in the utility function. Despite the data limitations, it is found that, the ALMF algorithm can provide stable estimates of the choice parameters for some periods of the day. Finally, it is found that the daily variation of the user sensitivities for different periods of the day resembles a well-defined normal distribution.

The objectives were to determine the association of hair shedding to performance in beef cattle and estimate genetic parameters for hair shedding scores. Dams were observed for shedding and given a score of 1 to 5. The month of first shedding (MFS) was determined when a female reached an average shedding score of 3.25 or less. Performance data included calf bw and d205wt and were considered as a trait of the dam. Hereford dams with a MFS of March weaned calves 18.37 + or - 8.85 kg heavier than dams with a MFS of June (P < 0.01). Angus dams with a MFS of March had calves with bw 7.75 + or - 1.64 kg greater than dams with a June MFS (P < 0.001). The heritability estimate for MFS was 0.11 + or - 0.06. Timing of hair shedding may have an influence on growth performance for certain breeds.

Ecologists try to understand how changing habitats alter the populations of organisms living within them, and how, in turn, these changing populations alter the environment. By linking individual or cellular (physiological) processes to system level responses, mechanistic models can help describe the feedback loops between organisms and the environment. Aquatic systems have long used mechanistic models, but increasing model complexity over the last 50 years has led to difficulty in parameterization. In fact, it is often unclear how researchers are choosing parameters at all, even though small changes in parameters can change qualitative predictions. I explore the challenges in parameter estimation present in even an ideal situation. Specifically, I conduct individual experiments for all of the needed parameters to describe a simple lab-based, aquatic system; estimate those parameters using the results from these experiments supplemented with literature data; and run a large experiment designed to test how well the lab-estimated parameters predict actual zooplankton populations and nutrient changes over time. I document best practices for finding and reporting parameter choices and show whole ecosystem level consequences of a variety of decisions. To get the best predictions I find that a mix of parameter estimation methods are necessary. Trait-based approaches are another method to understand species-environment interactions. Trait-based methods aggregate species into functional traits, perhaps making qualitative predictions easier. Theory suggests that more functionally diverse systems will be more resilient. I test this prediction in a simple aquatic system but am unable to find consistent support for this hypothesis, and instead finding that results are highly dependent on what measures of ecosystem recovery are used. Overall, more species-specific information is critical to building better models for both mechanistic and trait-based approaches. I expand species-specific data by providing new information, and collating information from literature on a small, tropical Cladocera. / Thesis / Doctor of Philosophy (PhD) / Predicting what will happen to a habitat after a disturbance is critical for conservation and management. Species specific information is useful for building a mechanistic understanding of ecology. Predictions that include underlying processes (mechanisms) may be more robust to a changing environment than predictions based on correlations. Eutrophication, the addition of excess nutrients, is a common problem in freshwater habitats. Being able to predict the effects of nutrient addition is critical for ensuring the health of freshwater ecosystems. By using species-specific life history and morphological information and a simple lab system, I test different methods of predicting and understanding the consequences of eutrophication. I find that the ramifications of eutrophication are not easily predicted by species' categorizations or with a more detailed mechanistic model.