Theses and Dissertations from UMD

Permanent URI for this communityhttp://hdl.handle.net/1903/2

New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a give thesis/dissertation in DRUM

More information is available at Theses and Dissertations at University of Maryland Libraries.

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2006 - 200912010 - 20191

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    Semantic Foundations For Formalizing Brain Cancer Profiles
    (2019) Abraham, Joel; Austin, Mark; Celiku, Orieta; Systems Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    With the advent of whole-genome DNA sequencing technologies, tailoring of medical treatment to individual patients based on their genetic makeup has become the vanguard of modern medicine. One such area that can benefit from individualized medicine is that of brain and other Central Nervous System (CNS) cancers. The prognosis of malignant brain cancers is among the worst due to the heterogeneity and complexity of these tumors and their micro-environment. We present a framework that combines data mining and machine learning techniques with semantic approaches for building a clinically-relevant knowledge base of brain cancer profiles. We construct clusters of patients based on the similarity of their profiles using the k-means clustering algorithm and extract relevant molecular attributes of these clusters to classify instances of the clusters. We create a semantic model with ontologies, rule checking and reasoning, to enable rational therapeutic regimen selection. Finally, we lay the foundation to incorporate this framework into a digital twin architecture of a patient.
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    Debugging and Repair of OWL Ontologies
    (2006-07-26) Kalyanpur, Aditya Anand; Hendler, James; Computer Science; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    With the advent of Semantic Web languages such as OWL (Web Ontology Language), the expressive Description Logic SHOIN is exposed to a wider audience of ontology users and developers. As an increasingly large number of OWL ontologies become available on the Semantic Web and the descriptions in the ontologies become more complicated, finding the cause of errors becomes an extremely hard task even for experts. The problem is worse for newcomers to OWL who have little or no experience with DL-based knowledge representation. Existing ontology development environments, in conjunction with a reasoner, provide some limited debugging support, however this is restricted to merely reporting errors in the ontology, whereas bug diagnosis and resolution is usually left to the user. In this thesis, I present a complete end-to-end framework for explaining, pinpointing and repairing semantic defects in OWL-DL ontologies (or in other words, a SHOIN knowledge base). Semantic defects are logical contradictions that manifest as either inconsistent ontologies or unsatisfiable concepts. Where possible, I show extensions to handle related defects such as unsatisfiable roles, unintended entailments and non-entailments, or defects in OWL ontologies that fall outside the DL scope (OWL-Full). The main contributions of the thesis include: * Definition of three novel OWL-DL debugging/repair services: Axiom Pinpointing, Root Error Pinpointing and Ontology Repair. This includes formalizing the notion of precise justifications for arbitrary OWL entailments (used to identify the cause of the error), root/derived unsatisfiable concepts (used to prune the error space) and semantic/syntactic relevance of axioms (used to rank erroneous axioms). * Design and Analysis of decision procedures (both glass-box or reasoner dependent, and black-box or reasoner independent) for implementing the services * Performance and Usability evaluation of the services on realistic OWL-DL ontologies, which demonstrate it's practical use and significance for OWL ontology modelers and users