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Articles 1 - 15 of 15
Full-Text Articles in Engineering
Overcoming Anaerobic Digestion Toxicity Of Aqueous Liquid From Wastewater Solids Pyrolysis, Seyedehfatemeh Seyedi
Overcoming Anaerobic Digestion Toxicity Of Aqueous Liquid From Wastewater Solids Pyrolysis, Seyedehfatemeh Seyedi
Dissertations (1934 -)
Pyrolysis treats and potentially recovers energy from wastewater solids (WWS). Aqueous pyrolysis liquid (APL), however, is produced and its management is a bottleneck to pyrolysis full-scale application. To overcome this bottleneck, anaerobic digestion (AD) may be a possible method to manage APL, but APL digestion has not been conclusively demonstrated. In AD, a select group of microorganisms convert organic chemicals to biogas containing methane that can be used as a fuel. In this dissertation work, APL derived from WWS pyrolysis was successfully converted into methane as the sole substrate and as a co-digestate with synthetic primary sludge in long-term, continuous …
Design Of Novel Experiments And Analyses For Head And Spine Trauma Biomechanics, John Robert Humm
Design Of Novel Experiments And Analyses For Head And Spine Trauma Biomechanics, John Robert Humm
Dissertations (1934 -)
Previous biomechanics research studies have used both whole-body and isolated postmortem human surrogate experiments to define human injury tolerances, advance safety in injury producing environments, and promulgate standards for design of injury mitigating systems. Recent developments in transportation and sports-related fields have led to an increasing need to determine tolerances for combined loading (multi-axis) scenarios. This dissertation demonstrates the efficacy of the novel experimental design and analysis to head and spine trauma in these modalities. The first topic was the design of a novel experiment to examine the effect oblique loading on the tension tolerance of the lumbar spine. To …
Stochastic Methods For Fine-Grained Image Segmentation And Uncertainty Estimation In Computer Vision, Philipe Ambrozio Dias
Stochastic Methods For Fine-Grained Image Segmentation And Uncertainty Estimation In Computer Vision, Philipe Ambrozio Dias
Dissertations (1934 -)
In this dissertation, we exploit concepts of probability theory, stochastic methods and machine learning to address three existing limitations of deep learning-based models for image understanding. First, although convolutional neural networks (CNN) have substantially improved the state of the art in image understanding, conventional CNNs provide segmentation masks that poorly adhere to object boundaries, a critical limitation for many potential applications. Second, training deep learning models requires large amounts of carefully selected and annotated data, but large-scale annotation of image segmentation datasets is often prohibitively expensive. And third, conventional deep learning models also lack the capability of uncertainty estimation, which …
Study Of Techniques To Enhance The Performance Of Concrete Members Strengthened By Externally Bonded Composite Materials, Zhao Wang
Dissertations (1934 -)
External bonding of fiber reinforced polymer (FRP) composite materials has been widely recognized as a popular technique for strengthening concrete structures. To find advanced strategies to improve the bond behavior of externally bonded composites strengthened concrete, three major tasks were conducted in this study: experimental work, finite element (FE) analysis, and reliability analysis. The mechanical properties and the deterioration due to water absorption of carbon nanofibers (CNFs) epoxy composites with different contents of CNFs were tested through uniaxial tensile test. According to the tensile test results, adding CNFs could significantly enhance the tensile behavior for epoxy resin. Because adding proper …
Analysis Of Bristle-Tip Impact Crater For Wire Impact Tool, Jian Zhang
Analysis Of Bristle-Tip Impact Crater For Wire Impact Tool, Jian Zhang
Dissertations (1934 -)
Bristle blasting is a novel method that is rapidly gaining widespread acceptance among engineers and practitioners in the surface preparation industry. This process contains the use of a specially designed wire bristle tool that is precisely tuned to the spindle speed of a power tool that rotates at approximately 2,500 rpm. That is, the principle of operation is based upon synchronized/repeated impact and rebound of bristle tips with the target surface, leading to a multitude of impact craters that remove corrosion, expose fresh substrate material, and generate anchor profile. Hence, it is important to develop a model to research the …
Deep Learning For Quantitative Susceptibility Mapping Reconstruction, Juan Liu
Deep Learning For Quantitative Susceptibility Mapping Reconstruction, Juan Liu
Dissertations (1934 -)
Quantitative susceptibility mapping (QSM) is a magnetic resonance imaging (MRI) technique that estimates tissue magnetic susceptibility from Larmor frequency offset measurements. The generation of QSM requires solving ill-posed background field removal (BFR) and field-to-source inversion problems. Incorrect BFR often introduces erroneous local field outputs and subsequently affects susceptibility quantification accuracy. Inaccurate field-to-source inversion often causes large susceptibility estimation errors that appear as streaking artifacts in the QSM, especially in massive hemorrhagic regions. Because current QSM techniques struggle to generate reliable QSM, the clinical translation of QSM is greatly hindered. Recently, deep learning (DL) has achieved state-of-the-art performance in many computer …
Determination Of Elevations For Excavation Operations Using Drone Technologies, Yuhan Jiang
Determination Of Elevations For Excavation Operations Using Drone Technologies, Yuhan Jiang
Dissertations (1934 -)
Using deep learning technology to rapidly estimate depth information from a single image has been studied in many situations, but it is new in construction site elevation determinations, and challenges are not limited to the lack of datasets. This dissertation presents the research results of utilizing drone ortho-imaging and deep learning to estimate construction site elevations for excavation operations. It provides two flexible options of fast elevation determination including a low-high-ortho-image-pair-based method and a single-frame-ortho-image-based method. The success of this research project advanced the ortho-imaging utilization in construction surveying, strengthened CNNs (convolutional neural networks) to work with large scale images, …
Shock Processes In Water: Multi-Scale Comparison And Experimental Results, Longhao Huang
Shock Processes In Water: Multi-Scale Comparison And Experimental Results, Longhao Huang
Dissertations (1934 -)
Water as the most common fluid on earth has extraordinary properties. The understanding of the dynamic response of water is important to planetary physics, biology and medicine. Inspired by the relationship between shockwave thicknesses and the intensity of property changes between pre-shock and post-shock states in gas medium, it is interesting to study the response of a liquid medium within shock process, such as liquid argon or water, from numerical and experimental methods, especially from different scales of simulations (continuum and molecular dynamics).Molecular Dynamics (MD) simulations of Hugoniot hydrostatic compression and shockwave propagation processes are performed via Large-Scale Atomic/Molecular Massively …
Contributions To The Theory And Application Of Multiple Model Estimation, Alia R. Strandt
Contributions To The Theory And Application Of Multiple Model Estimation, Alia R. Strandt
Dissertations (1934 -)
Multiple model estimation is a versatile technique that has been applied in a large variety of adaptive estimation problems. In this technique, several estimators, each designed around a possible model of the system, are used in parallel, and the estimator that most closely models the true system is determined using Bayes’ Rule. In this dissertation, convergence properties of the multiple model estimation algorithm are investigated, including a proof of convergence and factors that influence convergence time. In addition, the multiple model estimation algorithm is applied in two parameter estimation problems.The first half of the dissertation focuses on properties of the …
Eeg Characterization Of Sensorimotor Networks: Implications In Stroke, Dylan Blake Snyder
Eeg Characterization Of Sensorimotor Networks: Implications In Stroke, Dylan Blake Snyder
Dissertations (1934 -)
The purpose of this dissertation was to use electroencephalography (EEG) to characterize sensorimotor networks and examine the effects of stroke on sensorimotor networks. Sensorimotor networks play an essential role in completion of everyday tasks, and when damaged, as in stroke survivors, the successful completion of seemingly simple motor tasks becomes fantasy. When sensorimotor networks are impaired as a result of stroke, varying degrees of sensorimotor deficits emerge, most often including loss of sensation and difficulty generating upper extremity movements. Although sensory therapies, such as the application of tendon vibration, have been shown to reduce the sensorimotor deficits after stroke, the …
Patient-Specific Modeling Of Altered Coronary Artery Hemodynamics To Predict Morbidity In Patients With Anomalous Origin Of A Coronary Artery, Atefeh Razavi
Dissertations (1934 -)
Anomalous aortic origin of a coronary artery (AAOCA) is a condition where a coronary artery arises from the opposite aortic sinus, often with acute angle of origin (AO). AAOCA is associated with ischemia.1 This is especially concerning when the anomalous coronary artery takes an intramural course within the aortic wall, creating the potential for distortion or compression. Unroofing surgery replaces a restrictive ostium and intramural segment with a large ostium from the appropriate sinus and aims to create a less acute AO. Although these anatomical features may alter coronary artery blood flow patterns, hemodynamic indices such as time averaged wall …
Reaching Performance In Heathy Individuals And Stroke Survivors Improves After Practice With Vibrotactile State Feedback, Valay A. Shah
Reaching Performance In Heathy Individuals And Stroke Survivors Improves After Practice With Vibrotactile State Feedback, Valay A. Shah
Dissertations (1934 -)
Stroke causes deficits of cognition, motor, and/or somatosensory functions. These deficits degrade the capability to perform activities of daily living (ADLs). Many research investigations have focused on mitigating the motor deficits of stroke through motor rehabilitation. However, somatosensory deficits are common and may contribute importantly to impairments in the control of functional arm movement. This dissertation advances the goal of promoting functional motor recovery after stroke by investigating the use of a vibrotactile feedback (VTF) body-machine interface (BMI). The VTF BMI is intended to improve control of the contralesional arm of stroke survivors by delivering supplemental limb-state feedback to the …
Characterization Of Neuroimage Coupling Between Eeg And Fmri Using Within-Subject Joint Independent Component Analysis, Nicholas Heugel
Characterization Of Neuroimage Coupling Between Eeg And Fmri Using Within-Subject Joint Independent Component Analysis, Nicholas Heugel
Dissertations (1934 -)
The purpose of this dissertation was to apply joint independent component analysis (jICA) to electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) to characterize the neuroimage coupling between the two modalities. EEG and fMRI are complimentary imaging techniques which have been used in conjunction to investigate neural activity. Understanding how these two imaging modalities relate to each other not only enables better multimodal analysis, but also has clinical implications as well. In particular, Alzheimer’s, Parkinson’s, hypertension, and ischemic stroke are all known to impact the cerebral blood flow, and by extension alter the relationship between EEG and fMRI. By characterizing …
Probabilistic Framework For Balancing Smart Grid's Performance Enhancement And Resilience To Cyber Threat, Rezoan Ahmed Shuvro
Probabilistic Framework For Balancing Smart Grid's Performance Enhancement And Resilience To Cyber Threat, Rezoan Ahmed Shuvro
Dissertations (1934 -)
Critical infrastructures such as smart grids rely heavily on the seamless interaction between the grid subcomponents, i.e., the communication networks which transfers information from and to the grid, and the human operators/AI agents for taking necessary control actions. Smart grids are prone to cascading failures, which trigger from a few initial the tripping of a few transmission lines or generators, creating a ripple effect in the entire network, which may, in turn, lead to a total blackout. Having additional information through the communication network increases the probability of taking better control actions (e.g., effective load shedding and other protection mechanisms), …
Indirect Structural Connectivity As A Biomarker For Stroke Motor Recovery, Miguel Renato Sotelo Munoz
Indirect Structural Connectivity As A Biomarker For Stroke Motor Recovery, Miguel Renato Sotelo Munoz
Dissertations (1934 -)
In this dissertation project, we demonstrated that diffusion magnetic resonance imaging and measures of indirect structural brain connectivity are sensitive to changes in fiber integrity and connectivity to remote regions in the brain after stroke. Our results revealed new insights into the effects local lesions have on global connectivity—in particular, the cerebellum—and how these changes in connectivity and integrity relate to motor impairment. We tested this methodology on two stroke groups—subacute and chronic—and were able to show that indirect connectivity is sensitive to differences in connectivity during stroke recovery. Our work can inform clinical methods for rehabilitating motor function in …