Thesis (Ph. D.)--University of Iowa, 2007. / Supervisor: John Geweke. Includes bibliographical references (leaves 138-140).

D.Litt. et Phil. (Communication Studies) / Public relations as the active outwards and inwards communication process in the functioning of the organisation is seldom evaluated. In most cases, evaluation is limited to the measurement of media and message exposures. Although the importance of evaluation is emphasized by various researchers, limited research has been done on the evaluation process, a lack of systems methodology exists and no theoretical model has been developed or proposed to date. These problems led to the central aims of this study: to identify systems methodology for the evaluation process; and to develop an integrated communication evaluation model to redefine existing evaluation methods and techniques. Two methods were followed to address these aims. First an extensive theoretical study wasdone in terms of the systems theory to identify the systems methodology on which the evaluation process is based. Secondly, the concepts, methods and techniques for evaluation were identified and integrated into a theoretical framework for the evaluation process. A further purpose of this study was to explore evaluation to determine the role it fulfils in the functioning of the organisation, the communication process and the public relations process. Furthermore, an overview of developments in evaluation research is given. The aim was to draw from these findings to formulate directives for the development of an integrated communication evaluation model. To achieve this purpose, the concept evaluation was conceptualised and the main streams of thought were highlighted in terms of an integrated communication approach to evaluation. An integrated communication approach to evaluation suggests that public relations should not be evaluated in isolation, but that it should be integrated with other communication processes. The emphasis of an integrated communication process to evaluation is on information, a consumer/employee orientation, the use of both qualitative and quantitative evaluation in terms of three methods (attitude and behavior changes, effect studies and content analysis), and four new criteria for evaluation (the four C's: consumer/employee perceptions, communication of service/product qualities, cost to the consumer/employee and convenience).

The thesis deals with a procedure for developing mathematical models of hydraulic components for hydroelectric power generating units. Hydraulic system components modelled are the penstock, reservoir, surge tank, Francis turbine and the wicket gate actuator. A modelling philosophy is suggested. The thesis proposes that for a generator experiencing a sharp transient, such as line breaker reclosing, its capacity to maintain synchronism can be enhanced by taking advantage of waterhammer to sharply reduce the turbine's hydraulic torque input to the generator during the first few swings of the tie-line. Results of computer simulations included support this claim. / Applied Science, Faculty of / Electrical and Computer Engineering, Department of / Graduate

An exploited single-species population model with a density dependent reproductive function is constructed, in which recruitment to the adult breeding population may occur in one of several possible age classes. The parent is assumed capable of giving birth only once. It is also assumed that all density dependence is concentrated in the first year of life. A linearized stability analysis of the multiply-delayed difference equation model is carried out and a sufficient condition for stability is derived for the general case, while necessary and sufficient conditions are found in specific examples. Some indication of the complicated bifurcation structure of the model is given by a series of computer simulation plots. Finally, the method of Lagrange multipliers is used to find the optimal equilibrium escapement level for the original exploited population model. / Science, Faculty of / Mathematics, Department of / Graduate

Model selection criteria are used in many contexts in economics. The issue of determining an appropriate criterion, or alternative method, for model selection is a topic of much interest for applied econometricians. These criteria are used when formal testing methods are difficult due to a large number of models being compared, or when a sequential modelling strategy is being used. In econometrics, we are familiar with the use of model selection criteria for determining the order of an ARMA process and the number of dependent variable lags in Augmented Dickey-Fuller equations. The latter application is examined as an interesting example of the sensitivity of results to the choice of criterion. An application of model selection criteria to spline fitting is also considered, introducing a new, flexible, modelling strategy for technical progress in a production economy and for returns to scale in a resource economics context. In this latter context we have a system of estimating equations. Two of the criteria which are compared are the Cross-Validation score (CV) and the Generalized Cross- Validation Criterion (GCV), which until now have only had single equation context expressions. Multiple equation expressions for these criteria are introduced, and are used in the two applications. Comparison of the models selected by the different criteria in each context reveals that results can differ greatly with the choice of criterion. In the unit root test application, the choice of criterion influences the number of times the false hypothesis is not rejected. In the production economy and resource applications, measures of technical progress and returns to scale differ greatly, as do own and cross price elasticities, depending on which criterion is used for selecting the appropriate spline structure. An overview of the literature on model selection is given, with new expressions and interpretations for some model selection criteria, and historical notes. / Arts, Faculty of / Vancouver School of Economics / Graduate

The variability of chemical parameters over the landscape was examined in this research. A terrain hierarchy based on genetic geo-morphological unit concepts was developed in two Quaternary landscapes in the Fraser Valley and in the Peace River area in British Columbia. The relative variability within and betueen different hierarchical units ranging from "sites" to "landform units" to "landform unit types" was compared. The variability was large in all units but was smaller at the site scale than at the landform unit scale, within single landform units chemical parameters were shown to be closely related to type of drainage. Available Ca, Mg, Na, H, and Si were found to be the most important differentiating parameters for all units. Site categories which reflected units of similar parent material, form, and inferred genesis were determined by application of a cluster analysis procedure. Sites grouped by this method were not coextensive with individual land-form units, thus suggesting that the environmental imprint on the.chemical conditions was not as strong as that of the genesis. The best grouping was obtained with the Peace River data where more natural conditions prevailed. A data screening through factor analysis prior to the grouping improved the landform unit type classification in the Fraser Valley where the chemical conditions were complicated by a more complex and intensive land use pattern. Multispectral remote sensing techniques were used to assess the potential of predicting chemical ground conditions from spectral measurements. Multispectral photography combined with density slicing and additive color viewing techniques were used to quantify chemical ground conditions on the photographic image. Areas'of different soil moisture and percent Carbon content could readily be identified and quantified by this means. Exchangeable Ca, Mg, and Na could partially be differentiated probably as a result of direct correlation with Carbon. The wider band photography (color k00-700 nm and color IR 500-900 nm wavelength range) produced better results than the narrow band black and white images (50D-6QD nm and 6DD-7DD nm wavelength range). The trends in detecting chemicals were consistent for both vegetated and non-vegetated surfaces; the sliced color film image was slightly more useful for analyzing exposed soil surfaces, while the sliced color IR image proved to be more useful for the interpretation of vegetated surfaces. Direct digital reflection measurements were made with a multichannel spectrometer from the air, and Dn soil samples on the ground and in the laboratory. In the field the A-DO-1000 nm spectral wavelength range was used and the laboratory analysis was extended to the 35D-25D0 nm wavelength range. Only bare soil surfaces were investigated. Correlation and regression analysis revealed that % Carbon, % Fe, exchangeable Mg, and exchangeable K could be predicted from spectral reflection values. There is evidence thattthe spectral-chemical relationship follows a curvilinear function, but adequate predictions were obtained with linear relationships at low chemical concentration levels. Despite differences in measuring techniques similar regression trends were obtained for all three methods and the 50D-11D0 nm wavelength range was found to be most useful in this analysis. The total spectral reflectance curve was found to be of importance since soils from similar parent materials produced characteristic curves which could readily be differentiated by all three types of measurements. / Arts, Faculty of / Geography, Department of / Graduate

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The media’s effects on children have been frequently discussed, but the effects that childhood media has when individuals reach adulthood is not fully understood. Current research in this area has mostly focused on present day media figures, not past role models. Studying media role models retroactively shows the power of messages that people receive when they are children. This study used data collected from 18 undergraduate students through interviews (6 males, 12 females) to investigate three research questions regarding gender’s role in choosing a media role model, the articulation of gender identity during discussion of media role models, and how assessments of childhood media role models change over time. Findings that could lead to potential future research include the underlying hegemonic masculinity, where men are accessing their power in society through fictional characters’ masculine traits, and the influence of shared experience of media when choosing a childhood media role model.

Climate models are software tools that simulate the climate system and require evaluation to assess their skill, guide their development, and assist in selecting model simulations from among the many different ones available. There are a variety of methods and approaches that can be used to evaluate models. But there is no one best method and many possible and valid approaches exist. Models contain inherent uncertainties which complicate their evaluation, and include limitations in the knowledge of climate process dynamics and structural errors in constructing the models. Similar to the multiplicity of methods for the evaluation of model simulations, there also exist many possible approaches to addressing these sources of uncertainty. The challenge with uncertainty, is the difficulty in disaggregating it from the underlying element of legitimate chaotic behaviour in complex systems. In response, this dissertation is primarily one of methodological development to contribute to new ways of addressing the model evaluation challenge. The work defines and demonstrates a new evaluation method which complements the existing toolset. Specifically, the method defines a model performance metric that focuses on the extent to which a model is able to simulate global modes of climate variability (modes, e.g.: ENSO) evident in the observed climate data. Modes are one aspect of the climate that can be evaluated and are fundamental to model skill. Therefore their credible simulation is a necessary (but not sufficient) condition to ensuring that models are producing the right result (appropriate variability on the range of spatial and temporal scales) for the right reason. By ranking models by this metric of their skill in capturing fundamental global modes, poorly performing model simulations can be identified for potential exclusion (discounted). This metric therefore serves as a potential method to assist in the management of uncertainty when assessing multi-model data. The method develops a novel application of Independent Component Analysis (ICA). ICA is used to find representations of modes in a record of the present day climate (represented by reanalysis data), and then their degree of manifestation in global models is assessed. Recognising the large volume of model data (highly autocorrelated in space and time) the technique includes a data reduction technique to facilitate the evaluation of multiple model simulations. The technique also includes a novel measure of variance to differentiate it from a similar technique (Principal Component Analysis), and offers an approach to improve the consistency of results (signals) when using an unmixing matrix initialized with random values. As reanalysis data is itself a model product (constrained by observations), the performance metric is tested for its strength in discriminating modes by using two different reanalysis datasets and a dataset containing only Gaussian noise. The metric is found to perform predictably, and clearly demonstrates the ability to discriminate signal from noise when using geopotential height (GHT, 700mb and 500mb) and near surface air temperature data (TAS). The dependency of model performance on the variable measured by any metric can be a problem for model evaluation, as it introduces the choice of which variable should be measured to assess model performance. The ICA-based metric is found to be slightly less sensitive to a change in model rank between GHT (700mb) and TAS, compared to a similar novel variance metric (Fourier Distance) and a mean climate metric (bias). The ICA application is also found to produce plausible representations of modes (static maps), while a direct association to known modes is left for future work due to inherit complexities. The plausibility, consistency, and rank sensitivity of the novel application of ICA, suggests it has value in assisting the evaluation of multi-model datasets and the ensemble members for any one model.

Bibliography: pages 190-209. / This research proposed to identify the most accurate method of pricing rights using option pricing models, including the Black Scholes model, the Cox constant elasticity of variance model and the Merton jump diffusion model, and to determine the set of input parameters that lead to the most optimal results. The empirical results indicated that on average all of the models are able to estimate the actual rights trading prices relatively well. Some models performed better than others did and these findings were consistent with the original reasonings. The market was shown to not account for the effect of dilution. The best model prices were obtained when calculating volatility over a one year historical period that included the actual rights trading period. The hypothesis regarding trading volume showed that there is a significant impact of trading volume on the estimation of accurate option prices. The filter rule of rejecting rights prices below 10 cents and 100 cents also improved the results thus showing a bias for lower priced rights to be incorrectly valued and possibly some inefficiency in this sector of the market.