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This thesis presents research aimed at elucidating neurophysiological and neuropsychological correlates of two psychiatric disorders, schizophrenia and PTSD. Although psychiatric disorders are not traditionally known for featuring cognitive deficits, research over the past three decades has revealed that deficits in many aspects of cognitive functioning are present across a wide range of disorders. Here, we aim to further our understanding of these deficits and provide evidence of the clinical utility of neurophysiological correlates of cognitive dysfunction. The cause and course of cognitive deficits in PTSD is poorly understood, and an investigation of one potential explanatory mechanism, dissociative symptomatology, is presented in the first part of this thesis. Our results suggest that dissociative symptomatology plays a role in cognitive dysfunction in PTSD, as among the clinical variables tested (including PTSD symptomatology, dissociative symptoms, depressive symptoms, and anxiety symptoms) dissociative symptoms were the only significantly correlated variables to cognitive dysfunction in a sample of combat-trauma exposed veterans with and without PTSD. In the second part of this thesis, we investigate the potential clinical utility of a neurophysiological biomarker for semantic processing deficits, the N400, in schizophrenia. Our results indicate that N400 measures are stable over a one week period and therefore may be clinically useful as a neurophysiological biomarker for semantic processing abnormalities in schizophrenia. Overall, these two studies contribute to our knowledge of cognitive deficits in psychiatric disorders and demonstrate their complexity as well as their potential to provide clinically useful tools to aid in the identification of novel treatments targeted at ameliorating cognitive deficits in schizophrenia and PTSD. / Thesis / Master of Science (MSc)

The Semantic Web was introduced to bring structure to the Web. The goal is to allow computer agents to be able to traverse the web and carry out tasks for human users. In the Semantic Web, data is stored using the RDF data model. The purpose of this study is to explore the possibility of exposing GraphQL data to the Semantic Web using a data-to-data translation inspired by Ontology Based Data Access (OBDA). This was done by introducing GraphQL2RDF, a proof-of-concept method to materialize GraphQL data as RDF triples. GraphQL2RDF uses two mapping schemas: a GraphQL-mapping schema annotated with directives to filter and select GraphQL data and an RDF-mapping schema to specify which RDF triples to create. GraphQL2RDF supports directives for filtering based on the SQL where-clause used for filtering in SQL. The approach is demonstrated in a library use-case, in which library data exposed in a GraphQL endpoint is mapped into RDF. GraphQL2RDF demonstrates a method for exposing GraphQL data as RDF, while imposing a minimal set of requirements on the GraphQL endpoint. Future work includes improvements of the model and exploring extensions of this translation method towards an OBDA approach that does not require full materialization of the RDF data.

The Abstract Data Model (ADM) was developed by Sanderson [19] to model and predict semantic loss in data translation between computer languages. In this work, the ADM was applied to eight languages that were not considered as part of the original work. Some of the languages were found to support semantic features, such as the restriction semantics for inheritance found in languages like XML Schemas and Java, which could not be represented in the ADM. A proposal was made to extend the ADM to support these semantic features, and the requirements and implications of implementing that proposal were considered.

With the onset of the semantic web, the problem of making semantic content effectively searchable for the general public emerges. Demanding an understanding of ontologies or familiarity with a new query language would likely frustrate semantic web users and prevent widespread success. Given this need, this thesis describes AskOntos, which is a system that uses extraction ontologies to convert conjunctive, free-form queries into structured queries for semantically annotated web pages. AskOntos then executes these structured queries and provides answers as tables of extracted values. In experiments conducted AskOntos was able to translate queries with a precision of 88% and a recall of 81%.

Semantic role labeling has become a popular natural language processing task in recent years. A number of conferences have addressed this task for the English language and many different approaches have been applied to the task. In particular, some have used a memory-based learning approach. This thesis further develops the memory-based learning approach to semantic role labeling through the use of analogical modeling of language. Data for this task were taken from a previous conference (CoNLL-2005) so that a direct comparison could be made with other algorithms that attempted to solve this task. It will be shown here that the current approach is able to closely compare to other memory-based learning systems on the same task. Future work is also addressed.

Historical topographic maps are valuable resources for studying past landscapes, but two-dimensional cartographic features are unsuitable for geospatial analysis. They must be extracted and converted into digital formats. This has been accomplished by researchers using sophisticated image processing and pattern recognition techniques, and more recently, artificial intelligence. While these methods are sometimes successful, they require a high level of technical expertise, limiting their accessibility. This research presents a straightforward method practitioners can use to create digital representations of historical topographic data within commercially available Geographic Information Systems (GIS) software. This study uses convolutional neural networks to extract elevation contour lines from a 1940 United States Geological Survey (USGS) topographic map in Sevier County, TN, ultimately producing a Digital Elevation Model (DEM). The topographically derived DEM (TOPO-DEM) is compared to a modern LiDAR-derived DEM to analyze its quality and utility. GIS-capable historians, archaeologists, geographers, and others can use this method in their research and land management practices.

The present investigation modeled the expectancy memory organization and likely memory activation patterns of marijuana expectancies of children across age and marijuana use. The first phase of the study surveyed 142 children to obtain their first associate to marijuana use. From their responses, the Marijuana Expectancy Inventory for Children and Adolescents (MEICA) was developed. The second phase of the study administered the MEICA to a second sample of 392 children to model marijuana expectancy organization and probable memory activation paths of marijuana users versus never-users. Results indicated that irrespective of age, adolescents who have used marijuana tend to emphasize positive-negative effects, whereas adolescents who have never used marijuana tend to emphasize psychological-physiological effects. Memory activation patterns also differed by marijuana use history such that users are more likely to begin their paths with short-term positive effects of marijuana, versus non-users who access long-term cognitive and physiological effects with more likelihood. This study is the first to examine specific marijuana outcome expectancies of children and adolescents as they relate to marijuana-using behavior. Implications for marijuana prevention and intervention programs, future research, and limitations of the current investigation are discussed.

<p> The focus of this thesis is the importance of metaphor to an understanding of Isa 1:2-9. The argument depends on an understanding of metaphor as an imaginative structuring mechanism of cognitive linguistic behaviour, and a concrete mediator of meaning. The work proceeds from the observation that within contemporary scholarship readings of Isa 1 have failed to give sufficient attention to the occasion of its metaphors. The thesis argues that metaphor is essential to the text, and therefore a critical analysis of metaphor is central to its understanding. Using a Frame Semantic approach to contemporary Metaphor Theory, the interpretation of metaphors in Isa 1:2-9 is informed by insight offered from the historical and literary frames of the Ancient Near East and Hebrew Bible. Root metaphors of kinship, body, and land and their conceptual integration are discussed, and rich layers of meaning are revealed.</p> / Thesis / Master of Theological Studies (MTS)