Thesis PlanA (M.S.)--University of Wisconsin--Stout, 2008. / Includes bibliographical references.

Thesis (Ph. D.)--Rutgers University, 2007. / "Graduate Program in Computer Science." Includes bibliographical references (p. 284-290).

Thesis (Ed. D.)--West Virginia University, 2000. / Title from document title page. Document formatted into pages; contains xvi, 183 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 160-173).

Thesis (Ph. D.)--University of Notre Dame, 2006. / Thesis directed by John G. Borkowski for the Department of Psychology. "April 2006." Includes bibliographical references (leaves 67-72).

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

Thesis (Ph. D.)--University of Missouri-Columbia, 2006. / The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file viewed on (May 2, 2007) Vita. Includes bibliographical references.

AN ABSTRACT OF THE THESIS OF CHARLES ALAN PAYNE II, for the Masters of Arts degree in Criminology and Criminal Justice, presented on April 29, 2016, at Southern Illinois University Carbondale. TITLE: DOES SOCIAL LEARNING THEORY PREDICT DELINQUNECY DIFFERENTLY ACROSS URBAN, RURAL, AND SUBURBAN AREAS? MAJOR PROFESSOR: Dr. GEORGE BURRUSS The purpose of this study is to examine whether social learning theory predicts delinquency differently across urban, rural, and suburban areas. The lack of research in this area is problematic because while there are known differences between urban, rural, and suburban offending patterns, there is a lack of evidence to suggest why these patterns occur. The results of the study show that differential association, definitions, and differential reinforcement were significant across all three geographic locations. However, when analyzed by geographic location, differential reinforcement was only significant in suburban areas. In fact, differential reinforcement was the strongest predictor of delinquency in suburban areas, when differential association was the strongest in urban and rural.

Modeling the dynamics of complex multibody systems, such as those representing the motion of animals, can be accomplished through well-established geometric methods. In these formulations, motions take values in certain types of smooth manifolds which are coordinate-free and intrinsic. However, the dimension of the full configuration manifold can be large. The first study in this dissertation aims to build low-dimensional models models from motion capture data. This study also expands on the so-called learning problem from statistical learning theory over Euclidean spaces to estimating functions over manifolds. Experimental results are presented for estimating reptilian motion using motion capture data. The second study in this dissertation utilizes reproducing kernel Hilbert space (RKHS) formulations and Koopman theory, to achieve some of the advantages of learning theory for IID discrete systems to estimates generated over dynamical systems. Specifically, rates of convergence are determined for estimates generated via extended dynamic mode decomposition (EDMD) by relating them to estimates generated by distribution-free learning theory. Some analytical examples illustrate the qualitative behavior of the estimates. Additionally, a examination of the numerical stability of the estimates is also provided in this study. The approximation methods are then implemented to estimate forward kinematics using motion capture data of a human running along a treadmill. The final study of this dissertation contains an examination of the continuous time regression problem over subsets and manifolds. Rates of convergence are determined using a new notion of Persistency of Excitation over flows of manifolds. For practical considerations, two approximation methods of the exact solution to the continuous regression problem are introduced. Characteristics of these approximation methods are analyzed using numerical simulations. Implementations of the approximation schemes are also performed on experimentally collected motion capture data. / Doctor of Philosophy / Modeling the dynamics of complex multibody systems, such as those representing the motion of animals, can be accomplished through well-established geometric methods. However, many real-world systems, including those representing animal motion, are difficult to model from first principles. Machine learning, on the other hand, has proven to be extremely powerful in its ability to leverage "big data" to generate estimates from typically independent and identically distributed (IID) data. This dissertation expands on the so-called learning problem from statistical learning theory over Euclidean spaces to those over manifolds. This dissertation consists of three studies, the first of which aims to build low-dimensional models models from motion capture data. Using the distribution-free learning theory, estimates discussed in this dissertation minimize a proxy of the expected error, which cannot be calculated in closed form. This dissertation also includes a study into approximations of the so-called Koopman operator. This study determined that the rate of convergence of the estimate to the true operator depends on the reduced dimensionality of the embedded submanifold in the high-dimensional ambient input space. While most of the current work on machine learning focuses on cases where the samples used for learning or regression are generated from an IID, stochastic, discrete measurement process, this dissertation also contains a study of the regression problem in continuous time over subsets and manifolds. Additionally, two approximation methods of the exact solution to the continuous regression problem are introduced. Each of the aforementioned studies also includes several analytical results to illustrate the qualitative behavior of the approximations and, in each study, implementations of the estimation schemes are performed on experimentally collected motion capture data.

The dissertation focuses on understanding the mothering experience of three internal organizational development consultant/managers who perceive that their experience informed their professional functioning. The questions that guided the study were: (a) What is the mothering experience of the internal organizational development consultant/manager who perceives that her experience informed her professional functioning? and (b) How does the mothering experience inform the professional functioning of the internal organizational development consultant/manager? A case study method using the grounded theory method of data analysis produced three narratives that suggested how the mothering experience influenced consulting and managerial functioning. Three themes emerged; namely: "being fully present," "protecting by fighting for trust and safety / Ph. D.

The purpose of the study was to investigate the application of cognitive load theory to the design of online instruction. Students in three different courses (N = 146) were measured on both learning performance and perceptions of mental effort to see if there were any statistically significant differences. The study utilized a quasi-experimental posttest-only control group design contrasting modified and unmodified instructional lessons. Both groups were given a posttest to measure knowledge gained from the lesson (cognitive domain of learning) and perceptions of mental effort involved. Independent samples t-tests were used to compare the mean performance scores of the treatment groups (i.e. the sections using redesigned materials) versus the control groups for all three courses. Cohen's d was also computed to determine effect size. Mental effort scores were similarly compared for each group on the overall cognitive load score, for a total of six data points in the study. Of the four hypotheses examined, three (H1, H2, H4) found no statistically significant difference between the experimental and control groups. Negative significance was found between the experimental and control group on the effect of modality (H3). On measures of cognitive load, no statistically significant differences were found.