Engineering Commons^™

Electrochemically Reactive Membranes For Efficient Biomass Recovery, Pollutant Degradation And Commercialization, Likun Hua

Dissertations

Micropollution in natural waters such as rivers and groundwater aquifers is a widespread problem that prevents these potentially potable sources from being used as drinking water. In the United States, approximately two-thirds of the over 1,200 most serious hazardous waste sites in the nation are contaminated with trichloroethylene (TCE), a potentially carcinogenic compound. Other emerging and environmentally persistent organic micropollutants include polyromantic hydrocarbons (PAHs), organophosphate flame retardants, endocrine disrupting compounds (EDCs), pesticides, herbicides, pharmaceuticals and personal care products (PPCPs). Membrane filtration is one of the most efficient separation processes widely used for water treatment and pollutant removal. However, traditional membrane …

A Multimodal Approach To Investigate Brain Reorganization After Spinal Cord Injury Using Functional Magnetic Resonance Imaging And Functional Near-Infrared Spectroscopy, Keerthana Deepti Karunakaran

Dissertations

Traumatic Spinal Cord Injury (SCI) results in structural and functional neurological changes at both the brain and the level of the spinal cord. Anatomical studies indicate decreased grey matter volume in sensorimotor and non-sensorimotor regions of the cortex following SCI; whereas, neurophysiological findings mostly report altered functional activity in the sensorimotor nodes of the cortex, subcortex, and cerebellum. Therefore, it is currently unknown whether tissue atrophy observed in non-motor related areas has any concomitant functional consequences. Furthermore, the neural underpinnings of adaptive neuroplasticity after SCI is not well-defined in the current literature. Hence, this dissertation is a pioneer study investigating …

Supercapacitors With Gate Electrodes, Tazima Selim Chowdhury

Dissertations

A new approach to improve the capacitance of supercapacitors (SC) is proposed in this study. A typical SC is composed of an anode and a cathode; a separator in between them assures an unintentional discharge of the capacitor. The study focuses on a family of structured separators, either electronically active or passive which are called gates. An active structured separator layer has been fabricated and analyzed. The structured separator has characteristics of electrical diode and is fabricated out of functionalized carbon nanotubes (CNT). Improvement of the overall capacitance of SC, equipped with either active or passive structured separators demonstrated a …

Minimizing Vehicular Traffic Via Optimized Land Use Development For A Sustainable And Equitable Future, Babu Veeregowda

Dissertations

Mixed-use developments and transit-oriented developments are becoming very common in urban areas in an effort to reduce sprawl. Numerous studies have shown that such programs would not be successful unless the mix of land uses and sizes is well-balanced and integrated with the surrounding neighborhood. Developers often ignore this aspect in favor of immediate financial gain and do not realize that there are sustainable financial benefits in land use optimization. In addition, professionals often work with limited logistics, resources, and technical knowledge and therefore struggle in setting goals and suggesting land uses that have less auto dependency based on travel …

Dual Modality Optical Coherence Tomography : Technology Development And Biomedical Applications, Farzana Rahmat Zaki

Dissertations

Optical coherence tomography (OCT) is a cross-sectional imaging modality that is widely used in clinical ophthalmology and interventional cardiology. It is highly promising for in situ characterization of tumor tissues. OCT has high spatial resolution and high imaging speed to assist clinical decision making in real-time.

OCT can be used in both structural imaging and mechanical characterization. Malignant tumor tissue alters morphology. Additionally, structural OCT imaging has limited tissue differentiation capability because of the complex and noisy nature of the OCT signal. Moreover, the contrast of structural OCT signal derived from tissue’s light scattering properties has little chemical specificity. Hence, …

High-Performance Learning Systems Using Low-Precision Nanoscale Devices, Nandakumar Sasidharan Rajalekshmi

Dissertations

Brain-inspired computation promises a paradigm shift in information processing, both in terms of its parallel processing architecture and the ability to learn to tackle problems deemed unsolvable by traditional algorithmic approaches. The computational capability of the human brain is believed to stem from an interconnected network of 100 billion compute nodes (neurons) that interact with each other through approximately 10¹⁵ adjustable memory junctions (synapses). The conductance of synapses is modifiable allowing the network to learn and perform various cognitive functions. Artificial neural networks inspired by this architecture have demonstrated even super-human performance in many complex tasks.

Computational systems based …

Speciation Of Gaseous Oxidized Mercury Molecules Relevant To Atmospheric And Combustion Environments, Francisco J. Guzman

Dissertations

Mercury is a pervasive and highly toxic environmental pollutant. Major anthropogenic sources of mercury emissions include artisanal gold mining, cement production, and combustion of coal. These sources release mostly gaseous elemental mercury (GEM), which upon entering the atmosphere can travel long distances before depositing to environmental waters and landforms. The deposition of GEM is relatively slow, but becomes greatly accelerated when GEM is converted to gaseous oxidized mercury (GOM) because the latter has significantly higher water solubility and lower volatility. Modeling GOM deposition requires the knowledge of its molecular identities, which are poorly known because ultra-trace (tens to hundreds part …

Interventions Of Waterjet Technology In Skin Incisions, Nadi Atalla

Dissertations

This research explores the use of waterjet (WJ) technology in performing skin incisions. The study defines the analytical relationships between the skin properties and the operating parameters of the WJ which include the skin thickness, its elastic modulus, the WJ pressure, the nozzle’s orifice diameter, its stand-off distance and the traverse speed of the WJ as well as the duration of applying the WJ pressure. An analytical model is developed to measure the depth incision of the skin, the water pressure and the water velocity, while using a WJ. Systemization and optimization models that determine the optimal operating parameters levels …

Epitaxial Growth Of Iii-Nitride Nanostructures And Their Optoelectronic Applications, Moab Rajan Philip

Dissertations

Light-emitting diodes (LEDs) using III-nitride nanowire heterostructures have been intensively studied as promising candidates for future phosphor-free solid-state lighting and full-color displays. Compared to conventional GaN-based planar LEDs, III-nitride nanowire LEDs exhibit numerous advantages including greatly reduced dislocation densities, polarization fields, and quantum-confined Stark effect due to the effective lateral stress relaxation, promising high efficiency full-color LEDs. Beside these advantages, however, several factors have been identified as the limiting factors for further enhancing the nanowire LED quantum efficiency and light output power. Some of the most probable causes have been identified as due to the lack of carrier confinement in …

N8- Polynitrogen Stabilized On Carbon-Based Supports As Metal-Free Electrocatalyst For Oxygen Reduction Reaction In Fuel Cells, Zhenhua Yao

Dissertations

The sluggish oxygen reduction reaction (ORR) kinetics at the cathode is one of the key factors limiting the performance of polymer electrolyte membrane fuel cell (PEMFC). Platinum-based materials are the most widely studied catalysts for this ORR reaction while their large-scale practical application in fuel cells is hindered due to their scarcity and low stability. Therefore, highly active, low cost and robust non-Pt catalysts are being developed to overcome the drawbacks. Recently, a novel polynitrogen N8- (PN) stabilized on multiwall carbon nanotube (MWNT) was synthesized under ambient condition for the first time by our group and demonstrated high ORR activities. …

Surface-Enhanced Raman Detection Of Glucose On Several Novel Substrates For Biosensing Applications, Laila Saad Alqarni

Dissertations

The small normal Raman cross-section of glucose is considered to be a major challenge for its detection by Surface Enhanced Raman Spectroscopy (SERS) for medical applications. These applications include blood glucose level monitoring of diabetic patients and evaluation of patients with other medical conditions, since glucose is a marker for many human diseases. This dissertation focuses on Surface-Enhanced Raman Scattering primarily for the detection of glucose. Some experiments also are carried out for the detection of the corresponding enzyme glucose oxidase that is used in electrochemical glucose sensors and in biofuel cells. This project explores the possibility of utilizing Surface …

Workload Allocation In Mobile Edge Computing Empowered Internet Of Things, Qiang Fan

Dissertations

In the past few years, a tremendous number of smart devices and objects, such as smart phones, wearable devices, industrial and utility components, are equipped with sensors to sense the real-time physical information from the environment. Hence, Internet of Things (IoT) is introduced, where various smart devices are connected with each other via the internet and empowered with data analytics. Owing to the high volume and fast velocity of data streams generated by IoT devices, the cloud that can provision flexible and efficient computing resources is employed as a smart "brain" to process and store the big data generated from …

Fouling And Aging In Membrane Filtration : Hybrid Afm-Based Characterization, Modelling And Reactive Membrane Design, Wanyi Fu

Dissertations

Membrane filtration has been extensively used in water and wastewater treatment, desalination, dairy making, and biomass/water separation. However, membrane fouling, aging and insufficient removal efficiency for dissolved organic matters remain major challenges for wider industrial applications. In order to tackle these challenges, this doctoral dissertation investigates mechanisms of membrane fouling and development of antifouling membrane filtration technologies. Specifically, four major research areas are explored: (i) nanoscale physicochemical characterization of the chemically modified polymeric membranes; (ii) quantitative modelling between membrane properties and membrane fouling and defouling kinetics; (iii) development of quantitative structure-activity relationships for membranes that undergo thermal and chemical aging …

“Polysoaps” Via Raft Copolymerization To Form Well-Defined Micelles For Water Remediation And Targeted Drug Delivery Applications, Phillip Pickett

Dissertations

Amphiphilic copolymers have become increasingly important for environmental and biological applications due to their behavioral characteristics in aqueous solution. For example, structurally-tailored statistical amphiphilic copolymers or “polysoaps” can self-assemble into micelles or other architectures in water at various concentrations. Polysoaps may be differentiated from small molecule surfactant micelles in their capability to self-assemble into unimolecular associates (unimolecular micelles) with no dependence on concentration. Such micelles offer enormous potential for dispersion of hydrophobic species in water at high dilution. Importantly, each polymer chain forms its own micelle and upon dilution, these micelles remain intact and capable of dispersing hydrocarbon material in …

Engineering Multifunctional And Morphologically Diverse Polymer Brush Surfaces, Cassandra M. Reese

Dissertations

The combination of surface-initiated polymerization (SIP) and post-polymerization (PPM) serves as a powerful approach to fabricate complex, multifunctional polymer films, which can be precisely tuned for desired surface engineering applications. Careful manipulation of PPM parameters such as reaction conditions, the tethered brush parameters, and the physical properties of the unbound post-modifier greatly influence the depth of penetration of the post-modifier and the polymer brush compositional heterogeneity. This dissertation focuses on engineering polymer brush surfaces with multifunctional chemistries and tunable morphologies by investigating the PPM parameters that dictate the distribution of post-modifiers on grafted polymer brush surfaces.

The first chapter of …

Chemical And Physical Modification Of Thiol-Ene And Epoxy-Amine Networks For Advanced Control Of Gas Transport And Flame Retardant Behavior, Vivek Vasagar

Dissertations

Crosslinked polymers are widely used due to its several advantages not limited to high mechanical strength combined with the easy processability. Despite of its popular usage, the fundamental understanding of polymer structure affecting the desired properties is still lacking. This PhD thesis is in two parts, the first part is devoted to the design and developing a basic understanding of structure and chemical composition dependencies of gas transport, whereas in the second part a fundamental relationship between structure to the fire-retardant properties is established.

Membrane based gas separation technique has attracted interest of selective removal of carbon dioxide gas from …

Bioinspired Glycopolymers: Models To Investigate The Effect Of Saccharide Structure And Concentration On Amyloid Beta Aggregation, Pradipta Kumar Das

Dissertations

Aggregation and subsequent deposition of amyloid-β (Aβ) peptide on neuronal cell membranes have been implicated as a cause of Alzheimer’s disease. Gangliosides in their clustered form seed and promote the Aβ aggregation process. However, the effects of the structure and the concentration of ganglioside saccharides on Aβ aggregation are not well understood. We investigated how the specific structure of saccharides (β-D-galactose and β-D-glucose) affect the aggregation pathways, kinetics, and the aggregated structures of Aβ via in vitro experiments. The effects of the local concentration of saccharides on the Aβ aggregation were also investigated.

To mimic the multivalent effect of the …

Dual-Battery Empowered Green Cellular Networks, Xilong Liu

Dissertations

With awareness of the potential harmful effects to the environment and climate change, on-grid brown energy consumption of information and communications technology (ICT) has drawn much attention. Cellular base stations (BSs) are among the major energy guzzlers in ICT, and their contributions to the global carbon emissions increase sustainedly. It is essential to leverage green energy to power BSs to reduce their on-grid brown energy consumption. However, in order to furthest save on-grid brown energy and decrease the on-grid brown energy electricity expenses, most existing green energy related works only pursue to maximize the green energy utilization while compromising the …

Hardware/Software Co-Design Of A Reconfigurable Accelerator Platform For Fuzzy Logic-Based Spatial Image Processing Filters, Aous Hammad Kurdi

Dissertations

Rapid development in the architecture and fabrication technology of field programmable gate array (FPGA) and system on a chip (SoC) in the last two decades is dramatically increasing the reliability of those devices as a cost-effective alternative for traditional real-time image processing systems. Module reusability nature of FPGA and SoC development decreases design and implementation time noticeably. On-site reconfigurability allows for intensive design alterations to occur at a small cost. This study is presenting the design and implementation of a new hardware accelerator for an edge detector on Xilinx 7 series FPGA devices based on a fuzzy logic approach. The …

Parameter Determination And Modeling Of Transformer Windings For Fast Transients Including Frequency Dependent Effects, Yazid Al-Kraimeen

Dissertations

Power transformers are static devices capable of transferring energy from one electrical circuit to another by means of electromagnetic induction at the same frequency. The most common application of transformers in an electric power system is to step up or down the voltage level of an electric grid. This is essential for the efficient transmission and distribution of electricity from generating plants to different types of consumers. Electrical energy used in residential, commercial and industrial settings is delivered to consumers by means of transformers, which normally operate 24 hours a day, 365 days a year. Therefore, design improvements that result …

Network Equivalents Applied To Transient Analysis Of Large Distribution Systems, Ghassan Abdul-Hussein Bilal

Dissertations

Frequency domain (FD) methods for electromagnetic transient analysis of electric power systems offer outstanding simplicity and accuracy when dealing with distributed parameter elements and components that exhibit frequency-dependent behavior. However, the use of FD methods is usually restricted to the simulation of small and simple networks, since it is commonly believed that their application implies a very large computational burden when compared to time domain methods. This study demonstrates that FD methods can accommodate the detailed simulation of large distribution networks within acceptable computer times and in a very straightforward manner, thus offering an attractive complement or alternative to common …

Embedded Fault Class Detection Methodology For Condition-Based Machine Monitoring And Predictive Maintenance, Nagdev Amruthnath

Dissertations

Ever since the Second Industrial Revolution, manufacturing firms have continuously been working on minimizing the inefficiencies and maximizing the productivity of their system. This objective led to the creation of the Toyota Production System which follows the motto of “making [the] highest quality products at the least cost in the shortest lead time. (Ohno, 1988)” This philosophy is widely recognized and is utilized by various industries today.

Currently, we are going through the Fourth Industrial Revolution (also called, Industry 4.0) where internet technologies are utilized to additionally maximize the productivity in the production processes. Process synchronization is one of the …

Development Of Piezoelectric Sensors And Methodology For Noninvasive Simultaneous Detection Of Multiple Vital Signs, Areen Abdallah Romi Allataifeh

Dissertations

The activity of piezoelectric material linked the applied electric field with the strain generated that can be translated into geometrical variations. Flexible steel substrate exhibits fascinating mechanical properties which enable their integration into the emerging field of flexible microelectronics. This work presents an extended technique based on capacitance-voltage dependency to extract the geometrical variations in thin-film piezoelectric materials deposited on a flexible steel. A 50 μm flexible steel sheet has been sandwiched by two PZT film layers, each of 2.4 μm in thickness deposited by sputtering. An aluminum layer of 370 nm has been deposited above each PZT layer to …

An Investigation Of Three Subjective Rating Scales Of Mental Workload In Third Level Education, Nha Vu Thanh Nguyen

Dissertations

Mental Workload assessment in educational settings is still recognized as an open research problem. Although its application is useful for instructional design, it is still unclear how it can be formally shaped and which factors compose it. This paper is aimed at investigating a set of features believed to shape the construct of mental workload and aggregating them together in models trained with supervised machine learning techniques. In detail, multiple linear regression and decision trees have been chosen for training models with features extracted respectively from the NASA Task Load Index and the Workload Profile, well-known self-reporting instruments for assessing …

Forecasting Anomalous Events And Performance Correlation Analysis In Event Data, Sonya Leech [Thesis]

Dissertations

Classical and Deep Learning methods are quite common approaches for anomaly detection. Extensive research has been conducted on single point anomalies. Collective anomalies that occur over a set of two or more durations are less likely to happen by chance than that of a single point anomaly. Being able to observe and predict these anomalous events may reduce the risk of a server’s performance. This paper presents a comparative analysis into time-series forecasting of collective anomalous events using two procedures. One is a classical SARIMA model and the other is a deep learning Long-Short Term Memory (LSTM) model. It then …

An Investigation Into The Predictive Capability Of Customer Spending In Modelling Mortgage Default, Donal Finn [Thesis]

Dissertations

The mortgage arrears crisis in Ireland was and is among the most severe experienced on record and although there has been a decreasing trend in the number of mortgages in default in the past four years, it still continues to cause distress to borrowers and vulnerabilities to lenders. There are indications that one of the main factors associated with mortgage default is loan affordability, of which the level of disposable income is a driver. Additionally, guidelines set out by the European Central Bank instructed financial institutions to adopt measures to further reduce and prevent loans defaulting, including the implementation and …

Predicting Customer Retention Of An App-Based Business Using Supervised Machine Learning, Jeswin Jose

Dissertations

Identification of retainable customers is very essential for the functioning and growth of any business. An effective identification of retainable customers can help the business to identify the reasons of retention and plan their marketing strategies accordingly. This research is aimed at developing a machine learning model that can precisely predict the retainable customers from the total customer data of an e-learning business. Building predictive models that can efficiently classify imbalanced data is a major challenge in data mining and machine learning. Most of the machine learning algorithms deliver a suboptimal performance when introduced to an imbalanced dataset. A variety …

An Evaluation Of The Information Security Awareness Of University Students, Alan Pike

Dissertations

Between January 2017 and March 2018, it is estimated that more than 1.9 billion personal and sensitive data records were compromised online. The average cost of a data breach in 2018 was reported to be in the region of US$3.62 million. These figures alone highlight the need for computer users to have a high level of information security awareness (ISA). This research was conducted to establish the ISA of students in a university. There were three aspects to this piece of research. The first was to review and analyse the security habits of students in terms of their own personal …

Noise Reduction In Eeg Signals Using Convolutional Autoencoding Techniques, Conor Hanrahan

Dissertations

The presence of noise in electroencephalography (EEG) signals can significantly reduce the accuracy of the analysis of the signal. This study assesses to what extent stacked autoencoders designed using one-dimensional convolutional neural network layers can reduce noise in EEG signals. The EEG signals, obtained from 81 people, were processed by a two-layer one-dimensional convolutional autoencoder (CAE), whom performed 3 independent button pressing tasks. The signal-to-noise ratios (SNRs) of the signals before and after processing were calculated and the distributions of the SNRs were compared. The performance of the model was compared to noise reduction performance of Principal Component Analysis, with …

Predicting Violent Crime Reports From Geospatial And Temporal Attributes Of Us 911 Emergency Call Data, Vincent Corcoran

Dissertations

The aim of this study is to create a model to predict which 911 calls will result in crime reports of a violent nature. Such a prediction model could be used by the police to prioritise calls which are most likely to lead to violent crime reports. The model will use geospatial and temporal attributes of the call to predict whether a crime report will be generated. To create this model, a dataset of characteristics relating to the neighbourhood where the 911 call originated will be created and combined with characteristics related to the time of the 911 call. Geospatial …