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Canonical variate analysis (CVA) is a widely used method for analyzing group structure in multivariate data. It is mathematically equivalent to a one-way multivariate analysis of variance and often goes by the name of canonical discriminant analysis. Change over time is a central feature of many phenomena of interest to researchers. This dissertation extends CVA to longitudinal data. It develops models whose purpose is to determine what is changing and what is not changing in the group structure. Three approaches are taken: a maximum likelihood approach, a least squares approach, and a covariance structure analysis approach. All methods have in common that they hypothesize canonical variates which are stable over time. The maximum likelihood approach models the positions of the group means in the subspace of the canonical variates. It also requires modeling the structure of the within-groups covariance matrix, which is assumed to be constant or proportional over time. In addition to hypothesizing stable variates over time, one can also hypothesize canonical variates that change over time. Hypothesis tests and confidence intervals are developed. The least squares methods are exploratory. They are based on three-mode PCA methods such as the Tucker2 and parallel factor analysis. Graphical methods are developed to display the relationships between the variables over time. Stable variates over time imply a particular structure for the between-groups covariance matrix. This structure is modeled using covariance structure analysis, which is available in the SAS package Proc Calis. Methods related to CVA are also discussed. First, the least squares methods are extended to canonical correlation analysis, redundancy analysis, Procrustes rotation and correspondence analysis with longitudinal data. These least squares methods lend themselves equally well to data from multiple datasets. Lastly, a least squares method for the common principal components model is developed. / Ph. D.

Spatial analysis is of primary importance in forestry. Many factors that affect tree development have spatial components and can be sampled across geographic space. Some examples of spatially structured factors that affect tree growth include soil composition, water availability, and growing space. Our goals for this dissertation were to test the efficacy of spatial analysis tools in a forestry setting and make recommendations for their use. Reliable spatial analysis tools will lead to more effective statistical testing and can lead to useful mapping of spatial patterns. The data for this project is from simulated even aged loblolly pine stands (Pinus taeda L.). These simulated stands are grown at regular spacing and we impose a range of parameters on the stands to simulate many possible scenarios. In chapter 3 of this dissertation we perform a sensitivity analysis to determine if our methods are suitable for further research and applications. In chapter 4 we perform our analysis on more realistic data generated by a spatially-explicit stand simulator, PTAEDA 4.1. In chapter 3 we performed a statistical simulation of plantation stands without effects of competition and mortality. We used redundancy analysis (RDA) to quantify spatial variability, partial redundancy analysis (pRDA) to test for spatial dependence, and spatially constrained cluster analysis to map soil productivity. Our results indicated that RDA and pRDA are reliable methods and future evaluation is appropriate. The results from the spatially constrained cluster analysis were less clear. The success or failure of the clustering algorithm could not be disentangled from the success or failure of the selection criterion used to predict the number of clusters. Further investigations should address this concern. In chapter 4 we used PTAEDA 4.1, a loblolly stand simulator, to simulate a range of site conditions and produce data that we could use for analysis. The results showed that RDA and pRDA were not reliable methods and ready for the field. Spatially constrained cluster analysis performed poorly when more realistic data was used and because of this further use was uncertain. It was clear from the results that levels of variation and spatial pattern complexity of microsites influenced the success rate of the methods. Both RDA and pRDA were less successful with higher levels of variation in the data and with increased spatial pattern complexity. In chapter 5 we related the coefficient of variation from our simulations in (chapters 3 and 4) to two sets of real plot data, including a clonal set and open pollinated set. We then implemented a spatial analysis of the real plot data. Our spatial analysis results of the two comparable data sets were unaffected by genetic variability indicating that the primary source of variability across plots appears to be soil and other factors, not genetic related. / Ph. D.

Forest measurements are inherently spatial. Soil productivity varies spatially at fine scales and tree growth responds by changes in growth-age trajectories. Measuring spatial variability is a perquisite to more effective analysis and statistical testing. In this study, current techniques of partial redundancy analysis and constrained cluster analysis are used to explore how spatial variables determine structure in a managed regular spaced plantation. We will test for spatial relationships in the data and then explore how those spatial relationships are manifested into spatially recognizable structures. The objectives of this research are to measure, test, and map spatial variability in simulated forest plots. Partial redundancy analysis was found to be a good method for detecting the presence or absence of spatial relationships (~95% accuracy). We found that the Calinski-Harabasz method consistently performed better at detecting the correct number of clusters when compared to several other methods. While there is still more work that can be done we believe that constrained cluster analysis has promising applications in forestry and that the Calinski-Harabasz criterion will be most useful. / Master of Science

Novice Instructional Designers (IDs) often struggle to perform at the same level as experts. Specialized knowledge and experience are needed to discover the challenges and device appropriate solutions. Scaffold, guides, and heuristics can help novice when needing to perform tasks that require specialized knowledge. One common instructional design task requiring specialized knowledge is the development of instructional materials. Instructional message design (IMD) is a problem solving process to improve the quality of instructional materials through the application of research based principles. As this process is often not covered in novice IDs training, they will encounter more issues while attempting to address the challenges that come with creating instructional materials. Using a developmental study, a decision support tool was created to assist novice IDs with applying IMD, specifically the redundancy principle due to its ability to improve the communication within the materials. This study describes the operationalization of the principle, the design and development of the tool, expert review and revisions made based on their feedback, and the implications from the development of such a tool. / Doctor of Philosophy / Novices usually struggle to do tasks like experts. This is truer as the number of tasks and amount of specialized knowledge needed to do those tasks increases. Novices can perform these tasks if guides or tools are available. When creating courses, there are many tasks to accomplish like creating course materials. There are many rules to support the making of good, effective course materials. This study focused on designing and developing a tool to assist the novice when making course materials. The tool would help novices apply a rule to improve course materials so that students would have a better experience when using them.

Cases of brittle fractures in major bridges prompted AASHTO to publish its first fracture control plan in 1978. It focused on material and fabrication standards, and required periodic 24-month hands-on inspection of bridges with fracture critical members. The practical result of this plan was to significantly increase the life cycle cost of these bridges, rendering them uneconomical. Apart from the Point Pleasant Bridge that failed in 1967, no other bridge has collapsed in the USA following a fracture, even though large fractures have been observed in many other bridges. All these bridges showed some degree of redundancy and therefore could be reclassified as non-fracture critical if detailed analyses are carried out. The goal of this study is to provide guidance on redundancy evaluation of fracture critical bridges, specifically three girder bridges and twin box-girder bridges. The effect of various loading, analysis and geometric parameters on the post fracture response and the remaining load carrying capacity of the damaged bridge is evaluated through nonlinear finite element analysis of two well-documented structures: the Hoan Bridge and the twin box-girder bridge. Parameters such as damping definition, modelling of composite action, modelling of secondary elements, boundary conditions, and rate dependent material properties are found to be crucial in capturing the bridge response. A two-step methodology for system redundancy analysis of fracture critical bridges is proposed, leading to a reclassification of these elements as non-fracture critical for in-service inspection. The first step evaluates bridge capacity to withstand collapse following fracture based on whether the residual deformation is perceivable to people on or off the bridge. If the bridge satisfies the first step requirements, then the reserve load carrying capacity of the damaged bridge is evaluated in the second step. The Hoan Bridge failed to satisfy the proposed requirements in the first step and therefore its girders could not be reclassified as non-fracture critical. The twin box-girder bridge successfully resisted the collapse in two out three loading scenarios and displayed reserve load carrying capacity following full depth fracture in the exterior girder, and therefore can be reclassified as non-fracture critical for in-service inspection. / Ph. D.

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No / This article explores the importance of class and collectivism to personal identity, and the role this played during a period of personal and collective crisis created by mass redundancy in the Welsh steel industry. The research findings demonstrate the importance of occupational identity to individual and collective identity formation. The apparent desire to maintain this collective identity acted as a form of resistance to the increased individualization of the post-redundancy experience, but rather than leading to excessive particularism, it served as a mechanism through which class-based thinking and class identity were articulated. It is argued that the continued concern for class identity reflected efforts to avoid submergence in an existence akin to Beck¿s (1992) vision of a class-free `individualized society of employees¿.These findings therefore challenge the notion of the pervasiveness of individualism and the dismissal of class and collective orientations as important influences on identity formation.

Three different time-dependent optimal reliability design models with a series-parallel system are formulated. An efficient heuristic procedure for each problem is elucidated, and the results are described. The redundancy optimization problem using the time-dependent reliability function is solved so that the system reliability exceeds the target reliability over a time period at a minimum cost. The number of the redundancies in the system is obtained to ensure that the target reliability can be matched with the system reliability, which is time-dependent, as closely as possible without violating a cost constraints. The system configuration is optimized so that the system reliability matches the target reliability as much as possible while maintaining the system reliability at certain level under a cost constraint. Various applications of simple and efficient heuristic algorithms for solving time-dependent redundancy optimization problems are also provided. These techniques are used and tested in systems containing a substantial number of subsystems. The heuristic approaches appear more successful than other optimization techniques in solving these problems, and can be applied to any constrained redundancy optimization problems without any tedious formulation and computation. / Master of Science

Propõe-se, com este trabalho, estudar numericamente se a redundância cinemática e a redundância de atuação podem ser boas alternativas para que manipuladores planares de cinemática paralela atinjam altas acelerações. Sabe-se que estes tipos de redundância promovem uma redução de singularidades do sistema robótico entre outros benefícios. No entanto, a avaliação comparativa do desempenho dinâmico de manipuladores redundantes ainda é pouco estudada. Este estudo não é trivial pois a redundância significa não somente o aumento do torque disponível, mas também que a inércia do sistema foi aumentada. A avaliação numérica deste trabalho se dará por meio do desenvolvimento de modelos cinemáticos e dinâmicos das possíveis configurações de manipuladores paralelos planares com redundância cinemática e redundância de atuação. Esta avaliação pode ser feita pela comparação entre os manipuladores redundantes e o não-redundante para desenvolver uma mesma trajetória do end-effector. Entretanto, esta avaliação é dependente da trajetória, logo esse trabalho também propõe uma avaliação através de um índice dinâmico em toda a área de trabalho dos manipuladores. / The aim of this work is to study numerically if the kinematic redundancy and the actuation redundancy can be good alternatives for parallel planar manipulators to achieve high accelerations. It is known that types of redundancy promote, among other benefits, a significant reduction in the singularities. However, the evaluation of the redundancy as a good solution to increase the dynamic performance was not studied. This study is not trivial because the redundancy means not only that there is more torque available, but also that the inertia of the system has been considerably increased. Different configurations of the redundant manipulator will be evaluated numerically through kinematic and dynamic models. This evaluation can be performed by the comparison among the non redundant manipulator and the redundant manipulators to execute the same task. This evaluation is task dependent, so this work proposes a dynamic index to desing dynamic maps over the workspace.