Theses and Dissertations from UMD
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Item PROGNOSTICS AND SECURE HEALTH MANAGEMENT OF ANALOG CIRCUITS(2022) Khemani, Varun; Pecht, Michael G; Azarian, Michael H; Reliability Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Analog circuits are a critical part of industrial circuits and systems. Estimates in the literature show that, even though analog circuits comprise less than 20% of all circuits, they are responsible for more than 80% of faults. Hence, analog circuit Prognosis and Health Management (PHM) is critical to the health of industrial circuits. There are a multitude of ways that any analog circuit can fail, which leads to proportional scaling in the number of possible fault classes with number of circuit components. Therefore, this research presents an advanced Design Of Experiments-based (DOE) approach to account for components that degrade in an individual and interacting fashion, to narrow down the number of possible fault classes under consideration. A wavelet-based deep-learning approach is developed that can localize the circuit component that is the source of degradation and predict the exact value of the degraded component. This degraded value is used in conjunction with degradation models to predict when the circuit will fail based on the source of degradation. Increasing outsourcing in the fabrication of electronic circuits has made them susceptible to the insertion of hardware trojans by untrusted foundries. In many cases, hardware trojans are more destructive than software trojans as they cannot be remedied by a software patch and are impossible to repair. Process reliability trojans are a new class of hardware trojans that are inserted through modification of fabrication parameters and accelerate the aging of circuit components. They are challenging to detect through traditional trojan detection methods as they have zero area footprint i.e., require no insertion of additional circuitry. The PHM approach is modified to detect these hardware trojans in order to incorporate circuit security, resulting in the Prognosis and Secure Health Management (PSHM) framework. Deep neural networks achieve state-of-the-art performance on classification and regression applications but are a black-box approach, which is a concern for implementation. Wavelets are approximations of cells found in the human visual cortex and cochlea. They were used to develop wavelet scattering networks (WSNs), which were intended to be an interpretable alternative to deep neural networks. WSNs achieve state-of-the-art performance on low to moderately complex datasets but are inferior to deep neural networks for extremely complex datasets. Improvements are made to WSNs to overcome their shortcomings in terms of performance and learnability. Further applications of the research are highlighted for rotating machinery vibration analytics, functional safety online estimation etc.Item THE IMPACT OF DISEASE SEVERITY AND PHENOTYPE ON SMOKING AMONG ADULTS WITH CHRONIC OBSTRUCTIVE PULMONARY DISEASE(2019) Tilert, Timothy; Wang, Min Q; Public and Community Health; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Chronic Obstructive Pulmonary Disease (COPD) is estimated to be the third leading cause of death in the US. The most significant risk factor for COPD is long-term cigarette smoking. In spite of the myriad benefits of cessation, the proportion of adults with COPD who currently smoke is still nearly 50%. Little is known, however, about the characteristics of, and subsequent differences between, smokers with COPD, particularly at differing lung obstruction severity levels. The goals of this dissertation were to examine and compare the characteristics of smokers with diagnosed COPD as well as to explore the impact of disease severity and disease phenotype on smoking status among persons with COPD. This research utilized secondary data on 10,219 examined adults, aged 40-79 years, from the 2007-2012 National Health and Nutrition Examination Survey. In Study 1, adjusted logistic regression analyses revealed multiple factors that were associated with self-reported COPD diagnosis with those reporting three or more respiratory symptoms having the strongest association (AOR=22.1, 95% CI=12.0-40.5). In Study 2, it was shown that smoking status proportions did not differ by lung obstruction severity among those reporting a COPD diagnosis. In adjusted logistic regression analyses, multiple factors were associated with current smoking status among those with self-reported COPD with the presence of other smokers in the household having the strongest association with being a current smoker (AOR=19.5, 95% CI=10.2-37.5). In Study 3, three distinct phenotypes were found among the COPD population analyzed. In adjusted logistic regression analyses, COPD phenotype was differentially associated with continued smoking, above and beyond other predictors, with the older, heavy-smoking males with emphysema phenotype showing a significant positive association with continued smoking (AOR=3.7, 95% CI=1.3-10.9). Understanding how differences in disease severity and disease phenotypes impact smoking status among persons with diagnosed COPD could help inform more targeted, and effective, interventions to reduce smoking rates in this high-risk population. These findings potentially provide guidance for current smoking cessation interventions aimed at smokers with COPD as well as provide the foundation for further exploration of the association between COPD phenotype and continued smoking.Item PARENT PERSPECTIVES ON DIAGNOSIS OF AND SERVICES FOR CHILDREN WITH CORTICAL VISUAL IMPAIRMENT(2019) Kempler, Sara Kathleen; Beckman, Paula J; Special Education; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Medical advances in recent years have increased survival rates of infants born prematurely and/or infants and children that present with life-threatening conditions (Good et al., 1994; Khetpal & Donahue, 2007; Murphy & Carbone, 2011). These increased survival rates are associated with an increase in the number of children who have severe and/or multiple disabilities, including those conditions that are associated with cortical visual impairment. Children with typical or nearly typical eye exams, but having observable visual impairment are those generally diagnosed with cortical visual impairment, or CVI (Jan, Groenveld, Sykanda, & Hoyt, 1987). Delayed or lack of diagnosis of CVI can lead to missed opportunities for learning, and especially missed sensitive periods during which recovery can occur faster (Hubel & Wiesel, 1970; Roman-Lantzy, 2018). Without diagnosis, children may not be eligible for funding assistance for educational materials (American Printing House for the Blind, n.d.b). The purpose of this study was to explore parents’ experiences in getting a diagnosis of CVI for their children. For example, whether there were lapses in time between suspected vision difficulties and diagnosis, and what information was provided when diagnosis was obtained. The research questions guiding this investigation included: What are parents’ experiences in seeking a diagnosis for their child’s suspected vision challenges? What needs do parents recall related to information and supports while seeking a diagnosis for their child’s suspected vision challenges? What kind of information is offered or readily available to parents upon diagnosis of CVI? The primary data source for this study was interviews with parents of children having diagnosed CVI. Secondary data sources included interviews with ophthalmologists, teachers of the visually impaired, and records review.Item Novel surface proteins in the pathogenesis and diagnosis of Lyme disease(2010) Coleman, Adam Steven; Pal, Utpal; Animal Sciences; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Lyme disease is caused by an infection with the spirochete Borrelia burgdorferi. Transmitted between mammal reservoirs by the bite of an Ixodes tick, the pathogen exists in a complex life cycle that requires long-term persistence in arthropod and mammal hosts. The mechanisms responsible for persistence and the pathogenesis of Lyme disease are not well understood, but may involve interactions between bacterial surface proteins and the host. Previous experiments have shown that differential gene expression of surface proteins assists the pathogen in adaptation and persistence in a new host. Most B. burgdorferi surface proteins have no homology to known proteins, making the identification of virulence factors difficult. Gene expression analyses can be used to identify potentially important gene products for further study, based on the conditions under which they are expressed. To this end, the B. burgdorferi in vivo transcriptome of selected potential surface proteins was analyzed to identify promising targets for further study. Based on these analyses and other observations from the literature, the lipoproteins BbCRASP-2 and BBK07 were selected for further characterization. My hypothesis is that these proteins are important for B. burgdorferi virulence and persistence in the murine host. The surface exposure of each protein was assessed, as well as a detailed transcriptional profile of each gene. Using specific antibody-mediated interference and gene inactivation, I show that neither BbCRASP-2 nor BBK07 is essential for infectivity or pathogenesis in the murine model of Lyme disease. My results also indicate that BBK07 is a novel immunodominant antigen of B. burgdorferi that could be used as a serodiagnostic marker for human Lyme disease. Using a peptide library, the most immunodominant epitopes of BBK07 were identified, and shown to improve the diagnostic accuracy over that of the full-length recombinant BBK07. Finally, I show that BBK07-based diagnosis was sensitive even in the early stages of Lyme disease, and that the addition of BBK07 epitopes to current serodiagnostic assays could improve their sensitivity.Item 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