University of Maryland, Baltimore County
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Eight-times-twenty-five": Investigations of Colombia, from the individual experience to the archive
No full textThe artwork I made for my thesis exhibition is a passionate inquiry into the audiovisual materials found inside the National Archives in Washington, DC. I traveled to USA as a Fulbright scholar from Colombia in 2008. My research in the US archives followed the trail of the word "Colombia" in the entries of the archive's database. By researching my home country from outside its borders, this project also investigates America as the observing subject that collects information about the world around it. In so doing, my work locates the differences and similarities between the observer and the researcher. The concepts of memory, forgetting, perception and the task of archivists are explored in the context of the pieces, video installations that uses subtle optical effects based upon reflections, spot lights and modified translucent video displays. These installations transport the viewer from a reenactment of the Colombian battle of independence to the Caribbean Sea in a Colombian vessel around 1982. The silent montage of these images creates a dialogue between some of the materials found in this archive and others collected in Colombia during the course of these inquiries.Includes 2 video supplements
COVER MODEL PIVOT INDEXES FOR FLEXIBLE, ADAPTABLE, AND AGILE SYSTEMS
No full textTo support corporate business' competition on speed to market for product and service development, generically modeled data structures have been used in the development of vertical application software systems, and in storing XML and RDF data for its flexibility, adaptability, and agility. However, generic data models require multiple self-joins on a single table with a large volume of data, causing slow performance for business intelligence (BI) applications. Conversely, traditional specific data models have faster performance but are not flexible, adaptive, or agile for speed to market. A generic data model named the Class Object Value Element Relationship (COVER) model was developed for storing node-oriented tree data information, and is suitable for automated pivot index generation and distributed data processing. This approach utilizes pivot view with appropriate metadata constructs to expose the search predicate fields for indexing, leading to performance gains in data retrieval for queries on branches or leaves across multiple trees. It is beneficial for production support or data retrieval to feed business intelligence and data mining. A distributed COVER model with two different physical implementation variations was also developed for implementation on the distributed and parallel cloud computing platforms to take the scalability and performance advantages of the technology. Benchmark experiments for comparing the query performance on the COVER model against self-join and XPath/XQuery approaches using RDBMS were executed and proved that the COVER model outperforms the other two on the same sets of test data queries. Furthermore, benchmark experiments on distributed cloud computing environment were conducted using Hadoop HBase for comparing the RDBMS COVER and distributed COVER models. The results have shown that the distributed COVER models outperformed the RDBMS and demonstrated that the distributed COVER model is a viable data storage approach for flexible, adaptable, agile, and scalable systems
Manifest or Murky? A Reexamination of the Popularity of Manifest Destiny in the Antebellum Era
No full textManifest destiny is usually portrayed as an ideology that held immense sway in the United States from 1845-1854. Apart from the work of Frederick Merk in the 1960s, however, the popularity of manifest destiny in this period has never been measured. This thesis, therefore, is a reexamination of manifest destiny from 1846-1857. In this thesis, the phrase manifest destiny is traced in the pages of the Congressional Globe, newspapers, popular magazines, and works of literature. By comparing these sources, it is clear that the phrase manifest destiny was largely avoided by expansionists in the 1840s, became prominent in the 1850s, and was never embraced by the larger American public. The thesis reveals the need for the ideology of manifest destiny to be extricated from mere expansionism and for future research to reassess the popularity of this ideology in the Antebellum Era
Partial Volume Estimation of Magnetic Resonance Image Using Linear Spectral Mixing Analysis
No full textBecause of the strength in providing high contrasts of soft tissues Magnetic Resonance Imaging (MRI) has been an important medical modality in diagnosis of tissue characterization such as tissue classification and analysis as well as quantitative imaging such as partial volume estimation. Over the past years, numerous techniques have been developed for MRI and can be roughly categorized into two principal approaches. One is a structural approach which is primarily based on spatial correlation among MR image pixels, referred to as voxels. This type of approach is considered as a spatial domain-based clustering technique, examples include edge detection, region growing, segmentation etc. As a result, a structural approach is generally used for tissue characterization such as segmentation, classification, texture analysis. The other is a statistical approach which is essentially a parametric technique based on Finite Gaussian Mixture (FGM) models coupled with Markov Random Field (MRF) to capture intra-voxel correlation. Consequently, this approach is mainly used for partial volume estimation. Unfortunately, both approaches suffer from certain drawbacks, some of which are particularly severe, for example, computational complexity, invalid assumption such as Gaussianity and limited generalizability such as extension to tissue detection. In order to address these issues, this dissertation develops a rather different and completely new approach which is solely based on intra-voxel correlation without using an MRF model. It is derived from a hyperspectral imaging point of view where Linear Spectral Mixture Analysis (LSMA) is used to replace the FGM model-based analysis to perform spectral unmixing where LSMA-unmixed abundance fractions can be interpreted as partial volume estimates. Such an LSMA-based approach can be considered as a third approach and is believed to be the first of its kind which has never been explored in terms of LSMA's framework in the literature. However, in order for a hyperspectral imaging technique to be applicable to MRI, a key issue needed to be addressed is the limited spectral information provided by a voxel using only a small number of image sequences, namely, T1, T2 and PD (photon density). To resolve this issue two major techniques are developed to expand spectral information in this dissertation. One is to use Band Expansion Process (BEP) to expand spectral dimensionality via a nonlinear function so that an original (T1,T2,PD)-voxel can be expanded to a multi-dimensional pixel vector with its dimensionality greater than 3 with which LSMA can work more effectively. The other is to introduce a nonlinear kernel into LSMA, referred to as kernel-based LSMA (K-LSMA) which can make nonlinear decisions to cope with linear non-separability problems caused by insufficient spectral information. Furthermore, in order to further extend LSMA's unmixed capability, a kernel-based unsupervised LSMA (K-ULSMA) is also developed for tissue detection which generally cannot be accomplished by structural and statistical approaches. Finally, in order to perform quantitative analysis, two evaluation tools are further developed in this dissertation, 3D Receiver Operating Characteristics (3D ROC) analysis for partial volume estimation and 2D Tanimoto Index Curve (2D TIC) for soft-decision made classification. Specifically, 2D TIC is a newly developed concept and has never been explored and reported in the literature
Advances in the molecular genetic analyses of Volvox carteri
No full textVolvox carteri is a multicellular green alga comprised of two distinct cell types: ~16 large reproductive cells called gonidia and ~ 2000 small motile somatic cells. The cells of a V. carteri individual are arranged spherically, with the somatic cells distributed at the surface of the spheroid, and the gonidia positioned slightly below. Since V. carteri possesses a basic 3-dimensional morphology and exhibits the simplest type of complete division of labor, it is an ideal system to study fundamental developmental mechanisms. Since V. carteri is haploid, it is relatively easy to find developmental mutants which disrupt asymmetric division, spheroid morphology, and somatic cell fate. Previously Jordan and Idaten, two cold-inducible transposons, were used to tag and clone several genes from these developmental mutant classes. Unfortunately, extensive efforts to tag and clone certain types of developmental genes with these transposons have failed. Though it is relatively easy to obtain developmental mutants in V. carteri, it is particularly difficult to conduct antisense or gene knockdown studies because of low transformation efficiency. Other knockdown approaches such as antisense technology have also been used in V. carteri, but are cumbersome and sometimes cause off targets effects. Knockdown studies are valuable for reverse genetic analyses on candidate genes suspected of playing important developmental roles. Presently, gene knockdown approaches are more routinely achieved by highly specific artificial microRNA technologies. The goal of this dissertation has been two fold, first, to identify and characterize additional class II transposons for gene tagging and second, to develop a more robust gene knockdown system in V. carteri. Here, we report the characterization and classification of 14 novel V. carteri class II transposon families and have identified members with the potential for transposon tagging experiments to identify and clone other important genes in V. carteri. Additionally, we have demonstrated that V. carteri possesses an endogenous miRNA system and present the first V. carteri amiRNA vectors that facilitate stable and specific knockdowns of target genes
Enabling Reproducibility of Scientific Data Flows Through Tracking and Representation of Provenance
No full textReproducibility of results is a key tenet of science. Some modern scientific domains, such as Earth Science, have become computationally complicated and, particularly with the advent of higher resolution space based remote sensing platforms, tremendously data intensive. Over the last few decades, these complexities along with the the rapid advancement of the state of the art confound the goal of scientific transparency. This thesis explores concepts of data identification, organization, equivalence and reproducibility for such data intensive scientific processing. It presents a conceptual model useful for describing and representing data provenance suitable for very precise data and processing identification. It presents algorithms for creating and maintaining precise dataset membership and provenance equivalence at various degrees of granularity and data aggregation. This model will be described and demonstrated first with a simple example, then in a more complicated example based on the real-world operational scenario of NASA Ozone Monitoring Instrument data processing system. Application of the model will allow more specific data citations in scientific literature based on large datasets and the data provenance equivalence. Our provenance representations will enable independent reproducibility required by scientific transparency. Increasing transparency will contribute to understanding, and ultimately, credibility of scientific results
INTELLIGENT INFORMATION DISCOVERY FROM DATA REPOSITORIES USING CONTEXT AND SEMANTIC TECHNIQUES
No full textThe increase in the amount of data generated by modern technologies has resulted in an increasing need for context awareness. Context provides the boundaries within which we can transition from data to relevant information although context may not be explicitly present in the data itself. The interpretation of data which leads to the extraction of information, changes or varies when the context changes. In this thesis we examine data and create a contextual model that seamlessly combines data elements of a domain in order to effectively locate and provide the most appropriate information for the user according to his or her needs. Much of this contextual information becomes specialized or tailored to one special domain or environment and hence becomes completely unusable for other domains or environments. We propose a generic system design for modeling and representing any contextual model for any domain. We also propose and implement an automatic solution for creating contextual models for a particular domain or a business environment. We demonstrate the use of contextual information and semantic techniques with the implementation of a prototype in the application domain of identifying potential threats associated with the shipments from the perspective of U.S. Federal agencies. We implemented a set of tools and technologies to assist in the process of creation of a contextual model as well as semantic networks. The experimental evaluation of our methodology shows that our techniques are promising and they produce better precision results compared to the scenario when these techniques are not considered
The Use of Classification Trees to Determine Criteria Leading to a Total Joint Replacement Recommendation for Patients with Knee or Hip Osteoarthritis
No full textThere is a need for a nonacceptable symptom state to indicate when a patient with knee or hip osteoarthritis exhibits symptoms severe enough to warrant total joint replacement (TJR). A previous study using logistic regression and ROC curve analysis was unable to determine pain and functional disability cut points leading to a TJR recommendation. Using the datasets from the previous study, classification trees were used to identify predictors and cut points of those predictors leading to a TJR recommendation. From the analysis, a patient's quality of life and joint space narrowing appeared to be the most important predictors, out of those included in the analysis, of a surgeon's recommendation for TJR. Further research and analysis is needed to determine if the generated classification trees accurately predict a surgeon's recommendation for TJR
The Development of The Communication Questionnaire: Measuring Hispanic immigrant parents' perception of communication barriers with teachers
No full textParent-teacher communication is an important aspect of parental involvement in education. Research suggests that because Hispanic immigrant parents encounter communication barriers, they tend to be less involved at school than other parents. Currently there are no instruments that measure communication barriers. The present study developed a questionnaire, The Communication Questionnaire, designed to measure communication barriers and examined aspects of construct validity. A literature review and feedback from professionals support aspects of content validity. Cognitive interviews provide evidence that support aspects of substantive validity: questionnaire items were interpreted as intended. Cronbach's alpha supports aspects of structural validity: high internal consistency was observed. Aspects of external validity were supported: there was a moderate correlation with a related measure and a weak correlation with an unrelated measure. These results provide evidence for the validity of the use of the scores on The Communication Questionnaire
Tipping the Scales: Can CHIP and Medicaid Expansions Trim Obesity Rates Among Lower Income Children and Adolescents?
No full textProblem Studied: The numbers of overweight people in the United States have more than doubled since the 1980's. According to the National Health and Nutrition Examination Survey (NHANES), the percentage of overweight and obese Americans between the ages of 20 and 74 has increased from 15% of the population in 1980 to 32.9% of the population in 2004. This trend seems to hold true for children and adolescents, as well. In 2004, 17.1% of U.S. children and adolescents were overweight (Ogden, et al., 2004). Among these, Hispanic children and adolescents had the highest rates of being overweight. According to a recent study 38.2% of Hispanic children and adolescent aged 2 to 19 are overweight or obese (Ogden, et.al. 2010). Compared to their normal weight counterparts, overweight or obese children and adolescents have higher risks for developing high blood pressure, sleep apnea, and type 2 diabetes in addition to psychological problems associated with alienation, eating disorders, mental health problems, and discrimination. These conditions can be expensive to treat and manage. However, perhaps the most important consequence of childhood obesity is that children do not simply outgrow the weight, and they are more likely to grow up to be overweight adults if the weight problem is not addressed at a younger age. Researchers have been studying causes and consequences of overweight and obesity during childhood and adulthood as well as ways to alter or improve childhood overweight trends in the U.S. It is possible that greater access to health care, including health insurance coverage and access to a usual source of care (i.e. periodic well child visits) can improve this problem. However, to date, research in the possible causal relationship between health insurance status and the use of a usual source of care and childhood overweight is limited. Results: Based on the results from previous studies, we divided our study population into three different age groups (2-6 yrs., 7-11 yrs., and 12-17 yrs.) and estimated the effects for each age group separately. The overall results indicate that USC and health insurance coverage was not endogenous in the overweight and obesity outcomes of lower income children and adolescents. Our LPM and probit results showed that CHIP eligibility significantly reduced the overweight and obesity probabilities of 2-6 year old Hispanic children, excepting those at the lowest income levels. In contrast to the results for the youngest age group, we did not see a significant reduction in overweight or obesity probabilities of lower income 7-11 year old children or adolescents. Although among adolescents CHIP eligibility had no significant effects on overweight and obesity outcomes, the LPM results indicate that CHIP eligibility significantly increased the health insurance coverage for non-Hispanic adolescents