Thesis (Ph. D.)--University of North Texas, Aug., 2007. / Title from title page display. Includes bibliographical references.

In a typical response surface study, an experimenter will fit a first order model in the early stages of the study and obtain the path of steepest ascent. The path leads the experimenter out of this initial region of interest and into a new region of interest. The experimenter may fit another first order model here or, if curvature is believed to be present in the underlying system, a second order model. In the final stages of the study, the experimenter fits a second order model and typically contracts the region of interest as the levels of the factors that optimize the response are nearly determined. Due to the sequential nature of experimentation in a typical response surface study, the experimenter may find himself/herself wanting to augment some initial design with additional runs within the current region of interest. The little discussion that exists in the statistical literature suggests adding runs sequentially in a conditional D-optimal manner. Four prediction oriented criteria, I_IV, I_SV_r, I_SV_r^ADJ and G, and two estimation oriented criteria, A and E, are studied here as other possible sequential design augmentation optimality criteria. Analytical properties of I_IV, I_SV_r, and A are developed within the context of the design augmentation problem. I_SV_r is found to be somewhat ineffective in actual sequential design augmentation situations. A new more effective criterion,I_SV_r^ADJ is introduced and thoroughly developed. Software is developed which allows sequential design augmentation via these seven criteria. Unlike existing design augmentation software, all locations within the current region of interest are eligible for inclusion in the augmenting design (a continuous candidate list). Case studies were performed. For a first order model there was negligible difference in the prediction variance properties of the designs generated via sequential augmentation by D and the A best of the other criteria, I_IV, I_SV_r^ADJ, and A. For a second order model, however, the designs generated via sequential augmentation by D place too few runs too late in the interior of the region of interest. Thus, designs generated via sequential augmentation by D yield inferior prediction variance properties to the designs generated via I_IV, I_SV_r^ADJ, and A. The D-efficiencies of the designs generated via sequential augmentation by I_IV, I_SV_r^ADJ, and A range from the reasonable to fully D-optimum. Therefore, the I_IV, I_SV_r^ADJ, optimality criteria are recommended for sequential design augmentation when quality of prediction is more important than quality in estimation of coefficients. / Ph. D.

Statistical research can be more difficult to plan than other kinds of projects, since the research must adapt as knowledge is gained. This dissertation establishes a formal language and methodology for designing experimental research strategies with limited resources. It is a mathematically rigorous extension of a sequential and adaptive form of statistical research called response surface methodology. It uses sponsor-given information, conditions, and resource constraints to decompose an overall project into individual stages. At each stage, a "parent" decision-maker determines what design of experimentation to do for its stage of research, and adapts to the feedback from that research's potential "children", each of whom deal with a different possible state of knowledge resulting from the experimentation of the "parent". The research of this dissertation extends the real-world rigor of the statistical field of design of experiments to develop an deterministic, adaptive algorithm that produces deterministically generated, reproducible, testable, defendable, adaptive, resource-constrained multi-stage experimental schedules without having to spend physical resource.

Designers often look for inspiration in their environment when exploring possible solutions to a given problem. However, many studies have reported that external stimuli may constrain designers’ imagination and limit their exploration to similar solutions, a phenomenon described as design fixation. Inspiration and fixation effects are traditionally studied with a similar experimental paradigm, which has produced a complex web of findings and explanations. Yet, when analysing the experiments and their findings closely, it becomes clear that there is considerable variation in how studies are conducted and the results they produce. Such variation makes it difficult to formulate a general view of how external stimuli affect the design process, and to translate the research findings into education and practice. Moreover, it raises questions about the reliability and effectiveness of the traditional experimental method. This thesis reports on a collection of studies that examine how design inspiration and fixation research is done and how it can be improved. It explores the research area by reviewing the literature and analysing data from a workshop; describes the research method by scrutinising experiments and their procedures; and explains the variation in research findings by testing experimental procedures empirically and suggesting new interpretations. My main findings are that: abstract stimuli can inspire or fixate designers to different degrees depending on how explicitly the stimuli are represented; external stimuli can inhibit the exploration of ideas that would otherwise be explored; the effect of experimental instructions varies depending on how encouraging the instructions are; and the way participants represent and elaborate ideas can moderate fixation results. Whilst this thesis offers insights into design practice and education, its main contribution is to design research, where it represents a fundamental material for those who are new to inspiration and fixation research, and for those who are already expert.

Indiana University-Purdue University Indianapolis (IUPUI) / Non-invasive surface recording of bioelectric potentials continues to be an essential tool in a variety of research and medical diagnostic procedures. However, the integrity of these recordings, and hence the reliability of subsequent analysis, diagnosis, or recommendations based on the recordings, can be significantly compromised when various types of noise are allowed to penetrate the recording circuit and contaminate the signals. In particular, for bioelectric phenomena in which the amplitude of the biosignal is relatively low, such as muscle activity (typically on the order of millivolts) or neural traffic (microvolts), external noise may substantially contaminate or even completely overwhelm the signal. In such circumstances, the tissue-electrode interface is typically the primary point of signal contamination since its impedance is relatively high compared to the rest of the recording circuit. Therefore, in the recording of low-amplitude biological signals, it is of paramount importance to minimize the impedance of the tissue-electrode interface in order to consistently obtain low-noise recordings. The aims of the current work were (1) to complete the development of a set of tools for rapid, simple, and reliable full-spectrum characterization and analytical modeling of the complex impedance of the tissue-electrode interface, and (2) to characterize the interfacial impedance and signal-to-noise ratio (SNR) at the surface of the skin across a variety of preparation methods and determine a factor or set of factors that contribute most effectively to the reduction of tissue-electrode impedance and noise contamination during recording. Specifically, we desired to test an initial hypothesis that surface abrasion is the principal determining factor in skin preparation to achieve consistently low-impedance, low-noise recordings. During the course of this master’s study, (1) a system with portable, battery-powered hardware and robust acquisition/analysis software for broadband impedance characterization has been achieved, and (2) the effects of skin preparation methods on the impedance of the tissue-electrode interface and the SNR of surface electromyographic recordings have been systematically quantified and compared in human subjects. We found our hypothesis to be strongly supported by the results: the degree of surface abrasion was the only factor that could be correlated to significant differences in either the interfacial impedance or the SNR. Given these findings, we believe that abrasion holds the key to consistently obtaining a low-impedance contact interface and high-quality recordings and should thus be considered an essential component of proper skin preparation prior to attachment of electrodes for recording of small bioelectric surface potentials.