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Quantifying Contributions To The Variance Of Permeability And Porosity Within The Western Belt Sandstones Of The Cypress Formation, Illinois Basin, Nathaniel Frederick Dulaney Jan 2020

Quantifying Contributions To The Variance Of Permeability And Porosity Within The Western Belt Sandstones Of The Cypress Formation, Illinois Basin, Nathaniel Frederick Dulaney

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One of the strategies for reducing the emission of the greenhouse gas carbon dioxide (CO2) and mitigating its accumulation into the Earth’s atmosphere is geologic sequestration (GSCO2). This process might be paired with enhanced oil recovery (EOR) within depleted oil reservoirs to provide an economic incentive for GSCO2. Heterogeneity within reservoirs (e.g. spatial differences in entry pressure, permeability, and porosity) can exert significant influence on the dynamics of fluid flow during EOR and GSCO2, and thus on the ultimate success of GSCO2-EOR. The Western Belt sandstones of the Cypress Formation in the Illinois Basin are candidate reservoirs for GSCO2-EOR. Heterogeneity …

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Optimization Study Of A Combined Wind-Solar Farm For A Specified Demand, Venkat Siddhartha Rama Jan 2020

Optimization Study Of A Combined Wind-Solar Farm For A Specified Demand, Venkat Siddhartha Rama

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At the present time, using wind and solar energy for producing electricity in the United States is becoming cost competitive. According to Lazard’s 2019 [36] levelized cost of energy (LCOE) analysis of a number of energy sources used for producing electricity in the United States, wind and solar are cheaper than natural gas and coal. While capital, maintenance, operation, and fuel costs are included in LCOE numbers, energy source intermittency is not. Intermittency is an important issue with wind and solar energy sources, but not with natural gas or coal energy sources. Combining wind and solar energy sources into one …

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The Direct And Indirect Effects Of Mathematics Self-Efficacy On Intermediate Students’ Mathematics Growth, Susan Sipniewski Jan 2020

The Direct And Indirect Effects Of Mathematics Self-Efficacy On Intermediate Students’ Mathematics Growth, Susan Sipniewski

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In this study, the investigator sought to determine the extent to which mathematics self-efficacy affects mathematics growth among students in grades four and five. Included in this investigation is a hypothesized structural model that reflects Bandura’s (1977a, 1986, 1989) theory of self-efficacy. In part one of the investigation, each variable in the model (mathematics self-efficacy, self-regulation in mathematics, mathematics avoidance, mathematics anxiety, attitude toward mathematics, and mathematics growth) was analyzed to determine whether there were significant differences between genders in those specified variables. Findings revealed gender differences in two of the six variables, self-regulation in mathematics and mathematics avoidance. Females …

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Targeting Oncogenic K-Ras And Monoamine Oxidase B Utilizing Chalcones Bearing The 3,4,5-Trimethoxyphenyl Motif, Cody Fourman Jan 2020

Targeting Oncogenic K-Ras And Monoamine Oxidase B Utilizing Chalcones Bearing The 3,4,5-Trimethoxyphenyl Motif, Cody Fourman

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Oncogenic K-Ras is a driver protein found in specific cancers and was once thought to be “undruggable.” However, recent advances have suggested that mislocalizing K-Ras from the plasma membrane could be a viable strategy to target these cancers. The objective of this project was to identify a lead compound and determine a structure-activity relationship from chalcones bearing the 3,4,5-trimethoxy motif towards oncogenic K-Ras and MAO-B. This was accomplished by keeping the trimethoxy group consistent on one ring while varying the electron-donating or -withdrawing groups on the opposite ring. Previous work showed chalcones of this specific archetype exhibiting indiscriminate MAO inhibition, …

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An Adversarial Framework For Deep 3d Target Template Generation, Walter E. Waldow Jan 2020

An Adversarial Framework For Deep 3d Target Template Generation, Walter E. Waldow

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This paper presents a framework for the generation of 3D models. This is an important problem for many reasons. For example, 3D models are important for systems that are involved in target recognition. These systems use 3D models to train up accuracy on identifying real world object. Traditional means of gathering 3D models have limitations that the generation of 3D models can help overcome. The framework uses a novel generative adversarial network (GAN) that learns latent representations of two dimensional views of a model to bootstrap the network’s ability to learn to generate three dimensional objects. The novel architecture is …

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Additive Manufacturing Techniques To Enhance The Performance Of Electronics Created On Flexible And Rigid Substrates, Aamir Hamed Hamad Jan 2020

Additive Manufacturing Techniques To Enhance The Performance Of Electronics Created On Flexible And Rigid Substrates, Aamir Hamed Hamad

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Different additive manufacturing (AM) methods including fused deposition modeling (FDM) and piezoelectrical drop on demand (DOD) inkjet printing have been used in printed electronics for easy production, easy integration, better performance, and low cost. These methods have been used in producing everyday smart printed electronics such as conformal antennas (planner and non-planar antennas), sensors, actuators, and solar cells created on flexible and rigid substrates. The performance of printed electronics strongly depends on printing techniques and printing resolution that enhance their electrical and mechanical properties. In this dissertation, 3D and surface printing techniques were used to enhance the performance of printed …

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Adaptive Multi-Fidelity Modeling For Efficient Design Exploration Under Uncertainty, Atticus J. Beachy Jan 2020

Adaptive Multi-Fidelity Modeling For Efficient Design Exploration Under Uncertainty, Atticus J. Beachy

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This thesis work introduces a novel multi-fidelity modeling framework, which is designed to address the practical challenges encountered in Aerospace vehicle design when 1) multiple low-fidelity models exist, 2) each low-fidelity model may only be correlated with the high-fidelity model in part of the design domain, and 3) models may contain noise or uncertainty. The proposed approach approximates a high-fidelity model by consolidating multiple low-fidelity models using the localized Galerkin formulation. Also, two adaptive sampling methods are developed to efficiently construct an accurate model. The first acquisition formulation, expected effectiveness, searches for the global optimum and is useful for modeling …

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Comparing Dichotomous And Polytomous Items Using Item Response Trees, Daniel Jenkins Jan 2020

Comparing Dichotomous And Polytomous Items Using Item Response Trees, Daniel Jenkins

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Research on the optimal number of response options on graphic rating scales has yielded mixed results such as that more scale points are better; there is an optimal range; or that it does not matter. The present study compared the psychometric properties of dichotomous and polytomous personality items using several methods of scoring including summed scores, item response theory (IRT), and item response trees. It was found that regression models based on dichotomous items explained similar amounts of variance in careless responding as models based on polytomous items. In addition, scores from dichotomous models were more closely related to the …

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The Fate Of Anthropogenic Nitrogen Along Hydrologic Continuums: Patterns Of Transformation And Recycling In A Eutrophic Lake And Coastal Marine Sediments, Daniel K. Hoffman Jan 2020

The Fate Of Anthropogenic Nitrogen Along Hydrologic Continuums: Patterns Of Transformation And Recycling In A Eutrophic Lake And Coastal Marine Sediments, Daniel K. Hoffman

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Eutrophication of aquatic systems can have cascading effects along hydrological continua from watersheds to coasts that result in impaired ecosystem health. In freshwater systems, blooms of toxic, non-nitrogen (N) fixing cyanobacteria (cyanoHABs), such as Microcystis, proliferate due to external loading of chemically reduced forms of N (e.g., ammonium (NH4+) and urea), which promote growth and toxin production. In coastal marine systems, nutrient loading can promote harmful algae blooms and threaten vulnerable, native vegetation, such as seagrasses, which provide valuable ecosystem services but are under threat globally from anthropogenic stressors. This dissertation focuses on NH4+ cycling in the water column of …

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Degradation Of Trichloroethene By Radicals Produced By Oxygenation Of Various Reduced Iron Minerals, Jonathon Michael Deeter Jan 2020

Degradation Of Trichloroethene By Radicals Produced By Oxygenation Of Various Reduced Iron Minerals, Jonathon Michael Deeter

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Fe(II)-containing minerals (often as oxides and sulfides) are commonly present in the shallow subsurface and aquifers. Recent studies have shown that Fe(II) can generate reactive oxygen species upon oxygenation. This bench-scale investigation examined the generation of radical species from [Fe(II)]-containing mineral phases when exposed to oxygen. The Fe(II)-minerals in this study were chemically-reduced hydrous ferric oxide (HFO) and goethite, magnetite, and mackinawite (FeS). This research demonstrated that trichloroethene (TCE) can rapidly degrade by radicals produced from Fe(II)-containing oxides if gaseous oxygen is introduced in reactors. In contrast, there was little or no TCE degradation from oxygenation of freshly-prepared ferrous sulfide …

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Marine Vertebrate Communities From The Cisuralian Epoch (Permian Period) Of Central North America, Ryan C. Shell Jan 2020

Marine Vertebrate Communities From The Cisuralian Epoch (Permian Period) Of Central North America, Ryan C. Shell

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Marine vertebrates from the Cisuralian Epoch early Permian Period) are rare in the global fossil record. In particular, species-rich faunas from individual localities are poorly represented, with single occurrence localities that do not fully capture faunal tends in marine vertebrate ecology across this interval. This dissertation helps to close this gap by reporting marine vertebrate fossils from five localities across central North America, containing four to 15 unequivocal vertebrate taxa, as well as a new single occurrence locality near the Carboniferous-Permian boundary. This survey includes representatives from the first three of the four Cisuralian faunal stages, and is the result …

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Anthrax Event Detection: Analysis Of Public Opinion Using Twitter During Anthrax Scares, The Mueller Investigation, And North Korean Threats, Michele E. Miller Jan 2020

Anthrax Event Detection: Analysis Of Public Opinion Using Twitter During Anthrax Scares, The Mueller Investigation, And North Korean Threats, Michele E. Miller

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When people allow fear to drive their decision making, they often make decisions that do more harm than good. Examples of this include stocking up on ciprofloxacin, flooding doctors’ offices and buying black market antibiotics after the anthrax attacks of 2001. Therefore, it is important to be able to address what people are saying when another anthrax attack occurs. Supervised and unsupervised machine learning methodologies can be utilized to detect an event, classify the tweets by event, and to determine the main topics of discussion. Over the period of data collection, twenty events were detected. Three of these events concerned …

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Quantitative Susceptibility Mapping (Qsm) Reconstruction From Mri Phase Data, Sara Gharabaghi Jan 2020

Quantitative Susceptibility Mapping (Qsm) Reconstruction From Mri Phase Data, Sara Gharabaghi

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Quantitative susceptibility mapping (QSM) is a powerful technique that reveals changes in the underlying tissue susceptibility distribution. It can be used to measure the concentrations of iron and calcium in the brain both of which are linked with numerous neurodegenerative diseases. However, reconstructing the QSM image from the MRI phase data is an ill-posed inverse problem. Different methods have been proposed to overcome this difficulty. Still, the reconstructed QSM images suffer from streaking artifacts and underestimate the measured susceptibility of deep gray matter, veins, and other high susceptibility regions. This thesis proposes a structurally constrained Susceptibility Weighted Imaging and Mapping …

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Hierarchical Structure, Properties And Bone Mechanics At Macro, Micro, And Nano Levels, Farah Mohammed Ridha Abdulateef Hamandi Jan 2020

Hierarchical Structure, Properties And Bone Mechanics At Macro, Micro, And Nano Levels, Farah Mohammed Ridha Abdulateef Hamandi

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This research focuses on the hierarchical structure of bone and associated mechanical properties at different scales to assess damage accumulation leading to premature failure, with or without instrumentation. In this work, an attempt was made to develop a framework of macro, micro, and nano damage accumulation models and implementing them to derive mechanical behavior of the bone. At macrolevel, retrospective evaluation of 313 subjects was conducted, and the damage of bone tissue was investigated with respect to subject demography including age, gender, race, body mass index (BMI), height and weight, and their role in initiating fracture. Experimental data utilized 28 …

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Developing Equivalent Solid Model For Lattice Cell Structure Using Numerical Approaches, Tahseen Abdulridha Ali Al-Wattar Jan 2020

Developing Equivalent Solid Model For Lattice Cell Structure Using Numerical Approaches, Tahseen Abdulridha Ali Al-Wattar

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Lattice cell structures (LCS) are the engineered porous structures that are composed of periodic unit cells in three dimensions. Such structures have many scientific and engineering applications, such as in vessel gas technology, thermal systems, mechanical and aerospace structures, etc. for which lightweight, high strength, and energy absorption capabilities are essential properties. To have an optimized design, finite element analysis (FEA) based computational approach can be used for detailed analysis of such structures, sometime in full scale. However, developing a large-scale model for a lattice-based structure is computationally expensive. If an equivalent solid FE model can be developed using the …

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Characterization Of A Novel Terahertz Chemical Sensor, Daniel J. Tyree Jan 2020

Characterization Of A Novel Terahertz Chemical Sensor, Daniel J. Tyree

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A recently constructed novel analytical tabletop terahertz (THz) chemical sensor capable of detecting a wide range of gases with high sensitivity and specificity was characterized to assess its performance over a range of operational parameters. The sensor was designed with an objective of quantifying composition of exhaled human breath, where target concentrations span part per trillion (ppt) to part per billion (ppb) level of dilutions. The sensor utilizes terahertz rotational spectroscopy of sampled gases for quantification of dilutions. The sensor occupies a volume of ~ 2 ft3 and incorporates a coiled absorption cell, thermal desorption tubes, and all necessary electronic …

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Online Clustering With Bayesian Nonparametrics, Matthew D. Scherreik Jan 2020

Online Clustering With Bayesian Nonparametrics, Matthew D. Scherreik

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Clustering algorithms, such as Gaussian mixture models and K-means, often require the number of clusters to be specified a priori. Bayesian nonparametric (BNP) methods avoid this problem by specifying a prior distribution over the cluster assignments that allows the number of clusters to be inferred from the data. This can be especially useful for online clustering tasks, where data arrives in a continuous stream and the number of clusters may dynamically change over time. Classical BNP priors often overestimate the number of clusters, however, leading researchers to develop new priors with more control over this tendency. To date, BNP algorithms …

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Development Of Real-Time Systems For Supporting Collaborations In Distributed Human And Machine Teams, Aishwarya Bositty Jan 2020

Development Of Real-Time Systems For Supporting Collaborations In Distributed Human And Machine Teams, Aishwarya Bositty

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Real-time distributed systems constitute computing nodes that are connected by a network and coordinate with one another to accomplish a cooperative task, combining the responsiveness, fault-tolerance and geographic independence to support time-constrained collaborative applications, including distributed Human-Machine Teaming. In this thesis research the viability of real-time distributed collaborative technologies is demonstrated through the design, development and validation of prototype systems that support two human-machine teaming scenarios namely, ACE-IMS (Affirmation Cue based Interruption Management Systems) and ReadMI (Real-time Assessment of Dialogue in Motivational Interview). ACE-IMS demonstrates how a combination of AI capabilities and the cloud and mobile computing infrastructure can be …

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Development Of Tetrathiafulvalene Fused N-Heterocyclic Carbene Compounds, William J. Robinson Iii Jan 2020

Development Of Tetrathiafulvalene Fused N-Heterocyclic Carbene Compounds, William J. Robinson Iii

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Separately, N-Heterocyclic carbene and Tetrathiafulvalene compounds show great promise for a variety of applications. N-heterocyclic carbenes exhibit desirable metal bonding characteristics which allow for modulation of the metal center via back-bonding interactions. Additionally, this creates a system of increased bonding strength creating stable complexes. Tetrathiafulvalene exhibits strong redox-active and optical characteristics. These are owed to an increased aromaticity as oxidation of the compound occurs and thus, is stable through a multitude of oxidative states. The marriage of these two functionalization creates a unique opportunity for a “cure-all” compound, able to address many problems the world faces today including, but not …

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Stream Clustering And Visualization Of Geotagged Text Data For Crisis Management, Nathaniel C. Crossman Jan 2020

Stream Clustering And Visualization Of Geotagged Text Data For Crisis Management, Nathaniel C. Crossman

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In the last decade, the advent of social media and microblogging services have inevitably changed our world. These services produce vast amounts of streaming data, and one of the most important ways of analyzing and discovering interesting trends in the streaming data is through clustering. In clustering streaming data, it is desirable to perform a single pass over incoming data, such that we do not need to process old data again, and the clustering model should evolve over time not to lose any important feature statistics of the data. In this research, we have developed a new clustering system that …

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Small-Signal Analysis Of Non-Isolated Ćuk Dc-Dc Converter, Lokesh Kathi Jan 2020

Small-Signal Analysis Of Non-Isolated Ćuk Dc-Dc Converter, Lokesh Kathi

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In the future, renewable energy sources will be the primary energy sources due to non-renewable energy resources depletion. Having a sustainable energy source as an input voltage source for the electrical system is essential. Its applications can be widely used in hybrid solar-wind energy systems, electric vehicles, etc. This converter is invented and named after by Slobodan Cuk. An analysis describing a detailed steady-state operation of the non-isolated Cuk converter operating in continuous-conduction mode (CCM) is provided. The expected steady-state current and voltage waveforms across different components of the converter are analytically derived. Design equations for the converter are provided. …

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Variation In Available Habitat Impacts The Spatiotemporal Interactions Of A Great Lakes Carnivore Community, Mackenzie E. Rich Jan 2020

Variation In Available Habitat Impacts The Spatiotemporal Interactions Of A Great Lakes Carnivore Community, Mackenzie E. Rich

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Interactions between carnivores play a crucial role in regulating lower trophic levels. In order to examine interspecific interactions among Great Lakes carnivores, I used occupancy models to examine habitat selection patterns and quantify interactions between species. I determined temporal patterns of activity for each species and quantified interspecific activity overlap using kernel density estimates. To generate these models and analyze the patterns displayed, I placed 25 cameras across 25 km2 of diverse northern Wisconsin forest. I extracted habitat data from the National Landcover Database using GIS to inform my occurrence models for each detected carnivore species. The only significant influence …

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The Development Of Pet Imaging Agents For Neurodegenerative Disorders, Christine Morgan Kinstedt Jan 2020

The Development Of Pet Imaging Agents For Neurodegenerative Disorders, Christine Morgan Kinstedt

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With the intent to synthesize a potent and viable PET imaging agent for Alzheimer’s disease and/or Parkinson’s disease utilizing tau protein aggregates or alpha-synuclein aggregates as the ailments’ respective targets, researchers in this investigation synthesized derivatives of the chalcone scaffold in order to determine a lead molecule for further drug development. This molecular structure, which due to its ability to cross the blood brain barrier (BBB), has demonstrated efficiency in a number of neurodegenerative diseases and constitutes a convenient starting point for the development of potential imaging agents for Alzheimer’s and Parkinson’s diseases. Since simple chalcones have been demonstrated to …

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Scalable, Pluggable, And Fault Tolerant Multi-Modal Situational Awareness Data Stream Management Systems, Michael Partin Jan 2020

Scalable, Pluggable, And Fault Tolerant Multi-Modal Situational Awareness Data Stream Management Systems, Michael Partin

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Features and attributes that describe an event (disasters, social movements, etc.) are heterogeneous in nature. For virtually all events that impact humans, technology enables us to capture a large amount and variety of data from many sources, including humans (i.e., social media) and sensors/internet of things (IoTs). The corresponding modalities of data include text, imagery, voice and video, along with structured data such as gazetteers (i.e., location-based data) and government and statistical data. However, even though there is often an abundance of information produced, this information is fragmented across the various modalities and sources. The DisasterRecord system aims to provide …

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Towards Interpretable And Reliable Deep Neural Networks For Visual Intelligence, Ning Xie Jan 2020

Towards Interpretable And Reliable Deep Neural Networks For Visual Intelligence, Ning Xie

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Deep Neural Networks (DNNs) are powerful tools blossomed in a variety of successful real-life applications. While the performance of DNNs is outstanding, their opaque nature raises a growing concern in the community, causing suspicions on the reliability and trustworthiness of decisions made by DNNs. In order to release such concerns and towards building reliable deep learning systems, research efforts are actively made in diverse aspects such as model interpretation, model fairness and bias, adversarial attacks and defenses, and so on. In this dissertation, we focus on the research topic of DNN interpretations for visual intelligence, aiming to unfold the black-box …

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The Guardian, Week Of December 16, 2019, Wright State Student Body Dec 2019

The Guardian, Week Of December 16, 2019, Wright State Student Body

The Guardian Student Newspaper

News articles from The Guardian for the week of December 16, 2019. The Guardian is the official student-run newspaper for Wright State University. It has been published regularly since March of 1965.

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Joyce Howes, Former Assistant Dean Of College Of Mathematics And Science, Wright State University, Joyce Howes, Kathy Morris Dec 2019

Joyce Howes, Former Assistant Dean Of College Of Mathematics And Science, Wright State University, Joyce Howes, Kathy Morris

Wright State University Retirees Association Oral History Project

On December 6, 2019, Kathy Morris interviewed Joyce Howes about her 35-year career at Wright State University as student, instructor, and Assistant Dean of the College of Science and Mathematics . Howes discusses student success initiatives, Banner implementation, faculty mentorship, and institutional change from the late 1960s through 2015. The interview also highlights her continued teaching after retirement and her decision to become a living kidney donor to a fellow Wright State employee.

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Investigation Of Retrieved Cardiac Devices, Anmar Salih, Iosif Papadakis Ktistakis, Spyridon Manganas, Abdul Wase, Tarun Goswami Dec 2019

Investigation Of Retrieved Cardiac Devices, Anmar Salih, Iosif Papadakis Ktistakis, Spyridon Manganas, Abdul Wase, Tarun Goswami

Biomedical, Industrial & Human Factors Engineering Faculty Publications

Damage assessment of lead and pulse generator with various exposure times is important in the development of cardiac devices. Approximately, 92.1 million patients in the US suffer from cardiovascular diseases with an estimated healthcare cost of over $300 billion and at least one million with implantable cardiac devices. These devices are complex and composed on multiple levels and present challenges while assessing the damage. However, the study on the analysis of cardiac devices may lend insight into common damage patterns and improve future cardiac devices design. The objective of this work is to perform a thorough in vivo damage assessment …

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Board Of Trustees Meeting Minutes, December 5, 2019 Dec 2019

Board Of Trustees Meeting Minutes, December 5, 2019

Board of Trustees Minutes

Minutes from the Wright State University Board of Trustees Meeting held on December 5, 2019.

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Deep Brain Stimulation: Prediction Model For Volume Of Tissue Stimulated, Melissa Jones, Tarun Goswami Nov 2019

Deep Brain Stimulation: Prediction Model For Volume Of Tissue Stimulated, Melissa Jones, Tarun Goswami

Biomedical, Industrial & Human Factors Engineering Faculty Publications

An attempt has been made to understand deep brain stimulation in humans via marketable devices that are approved by the US Food and Drug Administration. The electrode characteristics were presented to influence the volume of tissue stimulated. Experimental data were digitized and VTS data were presented a function of electrode diameter, aspect ratio, applied current, pulse duration, voltage and frequency. Amongst other trends voltage and VTS were found to exhibit a three-stage relation, where Stage II characteristics were represented by a linear equation. It is in this stage, the VTS was found to be stable and where the most effective …

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