Gas Chromatography (GC) is one of the most important and widely used tools in analytical chemistry. However, they are bulky, have a longer measurement cycle, and consume a high amount of power. Micro-Gas Chromatography (µGC) is portable and energy-efficient, which allows onsite, real-time biological, forensic, and environmental analyses. This thesis presents a ready-to-deploy implementation of microfabricated gas chromatography (µGC) system capable of separating complex samples. We describe robust, modular, and scalable hardware and software architecture based on Real-Time Operating System (RTOS) and Python Graphical User Interface (GUI) integrated with various microfabricated devices to realize a fully functional µGC system. A sample heater for headspace injection, microfabricated separation column (µSC), a Photoionization Detector (PI-D), and a flow controller unit are integrated with the modular hardware and software to realize a fully functional Vacuum Outlet µGC system. We have designed a novel auto-calibration method for temperature calibration of the microfabricated devices which does not require changing the electronic circuitry or reprogramming the device. The vacuum outlet µGC setup is tested with various mixture of analytes. For these experiments, an average relative standard deviation (RSD) for retention time repeatability of 2.5% is achieved. Data processing techniques for raw chromatograms, including baseline correction and peak detection, are implemented on a microcontroller board and tested extensively as a part of this work. A novel algorithm for multidimensional analysis for the identification of co-eluting compounds in complex samples is implemented with a prediction accuracy of 94%. / Master of Science / Toxic volatile organic compounds (VOCs) such as benzene and toluene found in gasoline and xylene used in ink, rubber, and leather industries are of concern as they are present at elevated concentrations due to their higher vapor pressure. Sufficient exposure to these toxicants, even at lower concentrations like 100 parts-per-billion-volume (ppbv), may cause adverse health effects. Gas Chromatography (GC) has been the established method for assessing the presence and concentration of VOCs in the environment. Traditional GC systems are bulky, power-hungry, expensive, and require expert supervision for analysis. Recent research in microelectromechanical systems (MEMS) has reduced the size of the GC components, also called micro-GC (µGC), while improving the performance. The majority of the research and development of µGC is aimed at advancing microfabricated components such as preconcentrators, separation columns, and gas detectors. However, the integration of these different components is an important topic that requires more investigation. In this thesis, we present a robust and scalable software and hardware architecture that can be used to develop a portable and modular µGC system. The thesis discusses different experiments to calibrate various microfabricated devices, which are then used to build a fully modular µGC system. We show the separation capacity of the modular µGC system by passing complex compounds like kerosene and diesel. As the chromatogram from the µGC system has noise, the second part of the thesis explores data analysis techniques such as baseline correction, peak detection. These data analysis tools are used to filter the noise, detect relevant peaks in the chromatograms, and identify the compounds in a complex sample.

The survey instrument was developed through a factor analysis based upon the original 42 VCCS Management by Objectives goals as identified and developed by the VCCS Task Force on Management by Objectives. The reliability was established through a test/retest within the Virginia Community College System which produced a correlation coefficient of .98 between the two administrations of the instrument. Face validity was established based upon the development of the Management by Objectives goals specifically for the Virginia Community College System institutions by the VCCS Task Force on Management by Objectives. The findings of this study indicated that no statistically significant difference existed for either of the eight null hypotheses tested utilizing the SAS REGR analysis of variance procedure. The program produced overall multivariate analyses of variance for all but one comparison. Univariate analyses of variance were concomitantly produced per goal statement for each comparison. Statistical tests of ‘significance were conducted utilizing the .01 level of significance. Based upon the results of the data analysis, it was concluded that goal consonance existed between and among college and campus administrative groups (college-wide/central office and campus administrators) of the five Virginia multi-campus community colleges. / Ed. D.

Organizations have recognized usability engineering as a needed step in the development process to ensure the success of any product. As is the case in all competitive settings areas for improvement are scouted and always welcomed. In the case of usability engineering a lot of time, money, equipment, and other resources are spent to gather usability data to identify and resolve usability problems in order to improve their product. The usability data gained from the expenditure of resources is often only applied to the development effort at hand and not reused across projects and across different development groups within the organization. More over, the usability data are often used at a level that forces the organization to only apply the data to that specific development effort. However, if usability data can be abstracted from the specific development effort and analyzed in relation to the process that created and identified the data; the data can then be used and applied over multiple development efforts. The User Action Framework (UAF) is a hierarchical framework of usability concepts that ensures consistency through completeness and precision. The UAF by its nature classifies usability problems at a high level. This high level classification affords usability engineers to not only apply the knowledge gained to the current development effort but to apply the knowledge across multiple development efforts. This author presents a mechanism and a process to allow usability engineers to find insights in their usability data to identify both strengths and weaknesses in their process. In return usability practitioners and companies can increase their return on investment by extending the usefulness of usability data over multiple development efforts. / Master of Science

The exploration of complex systems is a fundamental pursuit in various scientific disciplines, includingphysics, biology, finance and engineering. The inherent complexity and dynamics within these systemspose significant challenges for traditional analytical methods. In recent years, the emergence of Topological Data Analysis (TDA) has provided a promising framework for uncovering hidden structures andpatterns in dynamic data sets. This thesis investigates the application of Topological Data Analysis to analyze system dynamics,aiming to enhance our understanding of their behavior. Through a detailed review of existing literature,we examine the theoretical foundations of TDA and its relevance to discrete and continuous processes.We discuss conceptual underpinnings of persistent homology, a key technique in TDA, and its potentialfor capturing essential features of system dynamics. By applying TDA to two distinct models, thestochastic ODE and the discrete logistic equation, we demonstrate its effectiveness in revealing underlyingstructures that traditional methods might overlook, thereby offering new insights into the analysis ofstochastic and discrete dynamical systems.

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Stormwater retention ponds, constructed primarily for services such as flood control, are abundant in urban landscapes and documented hotspots of aquatic biodiversity. A previous study completed in our lab measured benthic community structure in several stormwater retention ponds in North Central Texas along an urban gradient. Results showed that larval chironomids (Diptera: Chironomidae) were the dominant macroinvertebrates in all of the ponds. It was also determined that differences in pond conditions associated with urban development could only be determined when chironomids were identified to the genus-level. However, collection and identification of chironomid larvae is often time-consuming. The objective of this current study is to evaluate the efficacy of the Chironomidae pupal exuviae technique (CPET) to detect changes in water quality in the same series of urban ponds in North Central Texas over one year. Based on results, CPET is an effective method of analyzing chironomid community response to environmental changes associated with anthropogenic impact. A total of 16,635 pupal exuviae were collected during this study representing 80 chironomid taxa, which included 40 genera across three subfamilies. The chironomid communities differed between ponds in proportion to the intensity of the urban development within their watersheds. Additionally, CPET provided the emergence phenology of a highly diverse chironomid assemblage. Results indicated that urban ponds in North Central Texas can provide refuge for biodiversity in a semi-arid region. As urbanization is projected to increase globally, it is critical to monitor how rapid urban expansion affects biodiversity and freshwater ecosystem conditions.

The Gemini Near Infrared Spectrograph - Distant Quasar Survey (GNIRS-DQS) is the largest uniform, homogeneous survey of its kind, covering 260 quasars at 1.5 ≤ z ≤ 3.5. This unique survey, coupled with data from the Sloan Digital Sky Survey (SDSS), enables new investigations into redshifts, supermassive black hole masses (MBH), and accretion rates at high redshift through spectroscopic coverage of important rest-frame UV-optical emission lines. The importance of this survey is highlighted in the fact that the optical emission lines provide more reliable measurements of these quasar parameters than their UV counterpart. With such a unique sample compiled here, I construct prescriptions to calibrate these quasar parameters derived from rest-frame UV emission lines to those derived from rest-frame optical emission lines. These prescriptions provide important insight into how these parameters depend on redshift and are potentially biased as we look out further into the universe. Additionally, all the work completed with this sample will help shape our understanding of how these quasars and their host galaxies co-evolve over cosmic time.

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