Thesis (Ph. D.)--University of Wisconsin--Madison, 1970. / Vita. Typescript. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references.

Thesis (M.S.)--University of Wisconsin--Madison, 1965. / eContent provider-neutral record in process. Description based on print version record. Bibliography: l. 71-73.

Thesis (Ph. D.)--University of Wisconsin--Madison, 1966. / Typescript. Vita. Description based on print version record. Includes bibliographical references.

Thesis (Ph.D.)--Ohio University, March, 2005. / Title from PDF t.p. Includes bibliographical references (162-166)

In the present study, the author tested the validity of certain variables and paths from a model of eating disorder (ED) symptomatology (T. L. Tylka & L. M. Subich, 2004) along with several alternative models (i.e., including poor interoceptive awareness, ethnic identity, and body mass) within a sample of U.S. University women of South Asian origin. The original sample included 440 women, but responses differed based on graduate and international status. Therefore, path analytic procedures focused on 255 undergraduate, non-international women. Results indicated excellent fit for 5 models and adequate fit for the 6th model. Exploratory analyses did not support self-esteem as a moderator but did support the role of internalization of beauty standards in the ED symptomatology of South Asian American women (c.f., Reddy & Crowther, 2007). The results are discussed in light of their contributions, implications, and limitations.

No description available.

A thesis submitted to the Faculty of Science, University of the Witwatersrand, in fulfilment of the requirements for the degree of Master of Science, 2018 / Path replanning in high dimensional dynamic environments is critical to the success of interactive and reactive robotic agents. State of the art replanning algorithms typically extend sampling-based methods such as rapidly-exploring random trees (RRT) or probabilistic roadmaps (PRM). However, the speed of replanning in complex configuration spaces is relatively slow, which limits the effectiveness of robotic agents in highly dynamic environments. This thesis proposes DRM-connect, a novel generalisation of the PRM and RRT-connect algorithms, which carries out replanning in dynamic environments by executing graph searches over an underlying graph G, using lazy collision checking. If a path through the graph is not found, DRM-connect will repair the graph using a novel extension to RRT-connect, which we call PRM-connect. Additionally, we investigate using an approximate Reeb graph as the underlying graph G, which attempts to capture the underlying topology of the task manifold from prior experience. DRM-connect is tested with both a Reeb graph and na¨ıve graph in a 2-D domain and compared to RRT, while DRMconnect with a Reeb graph is tested in three 7-D domains, and compared to RRT-connect. Through simulation we show that the combination of DRM-connect and a Reeb graph typically outperforms both RRT/RRT-connect and DRM-connect with a na¨ıve graph in terms of replanning times, with minimal impact on the length of the solution path. / XL2019

Diagnostic tests are designed to detect and isolate faults in sequential systems. The problem is to evaluate the effectiveness of the design. For stuck faults a diagnostic model can be used. A fault simulation strategy is presented for generating this model. First, definitions, for identifying critical inputs are derived. A definition is a statement of the conditions to sensitize an input. Then a fault free simulation is used to generate a critical value array. A critical path is traced through the sensitized inputs marked in the array using a critical value array tracing algorithm that is developed. This algorithm traces a path back in time, as required for a sequential system, to identify detectable faults for the model.

No description available.

Software is often large, complicated and expensive to build and maintain. Redundant code can make these applications even more costly and difficult to maintain. Duplicated code is often introduced into these systems for a variety of reasons. Some of which include developer churn, deficient developer application comprehension and lack of adherence to proper development practices. Code redundancy has several adverse effects on a software application including an increased size of the codebase and inconsistent developer changes due to elevated program comprehension needs. A code clone is defined as multiple code fragments that produce similar results when given the same input. There are generally four types of clones that are recognized. They range from simple type-1 and 2 clones, to the more complicated type-3 and 4 clones. Numerous clone detection mechanisms are able to identify the simpler types of code clone candidates, but far fewer claim the ability to find the more difficult type-3 clones. Before CCCD, MeCC and FCD were the only clone detection techniques capable of finding type-4 clones. A drawback of MeCC is the excessive time required to detect clones and the likely exploration of an unreasonably large number of possible paths. FCD requires extensive amounts of random data and a significant period of time in order to discover clones. This dissertation presents a new process for discovering code clones known as Concolic Code Clone Discovery (CCCD). This technique discovers code clone candidates based on the functionality of the application, not its syntactical nature. This means that things like naming conventions and comments in the source code have no effect on the proposed clone detection process. CCCD finds clones by first performing concolic analysis on the targeted source code. Concolic analysis combines concrete and symbolic execution in order to traverse all possible paths of the targeted program. These paths are represented by the generated concolic output. A diff tool is then used to determine if the concolic output for a method is identical to the output produced for another method. Duplicated output is indicative of a code clone. CCCD was validated against several open source applications along with clones of all four types as defined by previous research. The results demonstrate that CCCD was able to detect all types of clone candidates with a high level of accuracy. In the future, CCCD will be used to examine how software developers work with type-3 and type-4 clones. CCCD will also be applied to various areas of security research, including intrusion detection mechanisms.