Engineering Commons^™

Quantitative Metrics For Mutation Testing, Amani M. Ayad

Dissertations

Program mutation is the process of generating versions of a base program by applying elementary syntactic modifications; this technique has been used in program testing in a variety of applications, most notably to assess the quality of a test data set. A good test set will discover the difference between the original program and mutant except if the mutant is semantically equivalent to the original program, despite being syntactically distinct.

Equivalent mutants are a major nuisance in the practice of mutation testing, because they introduce a significant amount of bias and uncertainty in the analysis of test results; indeed, mutants …

Customized Boron And Magnesium-Based Reactive Materials Prepared By High Energy Mechanical Milling, Xinhang Liu

Dissertations

New reactive materials need to be developed having biocidal combustion products. When ignited, such material can add chemical biocidal effects to the common effects of high temperature and pressure. Biocidal combustion products are capable of deactivating harmful spores or bacteria, which can be released by targets containing biological weapons of mass destruction. Research showed that halogens, especially iodine, are effective as biocidal components of reactive material formulations. Recently, magnesium combustion product MgO is also found to have a biocidal effect. Thus, advanced formulations containing both magnesium and iodine are of interest; such formulations are prepared and investigated here.

Reactive materials …

Perivascular Waste Metabolites Clearance In Central Nervous System (Cns), Yiming Cheng

Dissertations

Efficient clearance of interstitial waste metabolites is essential for normal brain homeostasis. Such effective clearance is hampered by the lack of a lymphatic system in the brain, and the cerebrospinal fluid (CSF) is unable to clear large size waste metabolites in the brain. Here, a novel idea that brain arterial endothelium and smooth muscle cells reactivity regulates the clearance of these water-insoluble large size waste metabolites through the perivascular dynamic exchange, and that low dose ethanol promotes this perivascular clearance is proposed.

In Aim 1, the biodistribution of a large size waste metabolite (Amyloid-β protein mimic) in rat perivascular space …

Bio-Inspired Learning And Hardware Acceleration With Emerging Memories, Shruti R. Kulkarni

Dissertations

Machine Learning has permeated many aspects of engineering, ranging from the Internet of Things (IoT) applications to big data analytics. While computing resources available to implement these algorithms have become more powerful, both in terms of the complexity of problems that can be solved and the overall computing speed, the huge energy costs involved remains a significant challenge. The human brain, which has evolved over millions of years, is widely accepted as the most efficient control and cognitive processing platform. Neuro-biological studies have established that information processing in the human brain relies on impulse like signals emitted by neurons called …

Cerebro-Vascular Disruption Mediated Initiation And Propagation Of Traumatic Brain Injury In A Fluid Percussion Injury Model, Xiaotang Ma

Dissertations

Traumatic brain injury (TBI) is a major health problem for over 3.17 million people in the US. There is no FDA-approved drug for the treatment because the injury mechanisms have not been clearly identified. The knowledge gap is addressed here by the lateral fluid percussion injury (FPI) rat model, through the understanding of layer-structured mechanisms from physical vascular rupture to acute necrosis, as well as biochemical changes in perivascular space as secondary events.

Firstly, the cerebrovascular hemorrhage and related infarct volume are investigated as the primary events in moderate FPI, which is found to be increased with injury severity in …

Using Machine Learning Classification Methods To Detect The Presence Of Heart Disease, Nestor Pereira

Dissertations

Cardiovascular disease (CVD) is the most common cause of death in Ireland, and probably, worldwide. According to the Health Service Executive (HSE) cardiovascular disease accounting for 36% of all deaths, and one important fact, 22% of premature deaths (under age 65) are from CVD.

Using data from the Heart Disease UCI Data Set (UCI Machine Learning), we use machine learning techniques to detect the presence or absence of heart disease in the patient according to 14 features provide for this dataset. The different results are compared based on accuracy performance, confusion matrix and area under the Receiver Operating Characteristics (ROC) …

Factor Analysis Of Mixed Data (Famd) And Multiple Linear Regression In R, Nestor Pereira

Dissertations

In the previous projects, it has been worked to statistically analysis of the factors to impact the score of the subjects of Mathematics and Portuguese for several groups of the student from secondary school from Portugal.

In this project will be interested in finding a model, hypothetically multiple linear regression, to predict the final score, dependent variable G3, of the student according to some features divide into two groups. One group, analyses the features or predictors which impact in the final score more related to the performance of the students, means variables like study time or past failures. The second …

A Reinforcement Learning Approach To Spacecraft Trajectory Optimization, Daniel S. Kolosa

Dissertations

This dissertation explores a novel method of solving low-thrust spacecraft targeting problems using reinforcement learning. A reinforcement learning algorithm based on Deep Deterministic Policy Gradients was developed to solve low-thrust trajectory optimization problems. The algorithm consists of two neural networks, an actor network and a critic network. The actor approximates a thrust magnitude given the current spacecraft state expressed as a set of orbital elements. The critic network evaluates the action taken by the actor based on the state and action taken. Three different types of trajectory problems were solved, a generalized orbit change maneuver, a semimajor axis change maneuver, …

Modelling And Fault Diagnosis Approach For Proton Exchange Membrane Fuel Cell Systems Incorporating Ambient Conditions, Saad Saleem Khan

Dissertations

Proton exchange membrane fuel cell (PEMFC), as a source of electrical power, provides numerous benefits such as zero carbon emission and high reliability as compared to wind and solar energy. PEMFC operates at very low temperature, high power density, and has very high durability as compared to other fuel cells. Being a non-linear power source with high sensitivity to ambient conditions variation, the prediction of PEMFC voltage and temperature is a complicated issue. The most common PEMFC models are classified as mechanistic models, semi-empirical models, and purely empirical methods. The mechanistic models are complex and require differential equations to predict …

Multiple Ssid Framework For Rss-Fingerprint Based Indoor Positioning Systems, Ahmed Kareem Abed

Dissertations

Location-Based Indoor positioning systems significance stems from the bloom of recent applications in various fields such as in tracking services for an elder or a patient within large living communities, mobile robot localization, and several other security applications. Currently, Global Positioning Systems (GPS) are the most widely used location-sensing technique. However, satellite-based GPS signals require line of sight (LOS) to work correctly, which is something cannot be achieved inside buildings. Fortunately, wireless LAN can be employed in indoor positioning systems (IPS), and since all large buildings such as malls, hospitals, airports, schools, and museums have hundreds of Wi-Fi access points, …

Analyzing Impacts Of Transportation And Non-Transportation Activities On Human Health With An Advanced Platform For Collecting Travel And Physical Activity Data, Raed Abdullah Hasan

Dissertations

Recently much attention is paid to the lack of physical activities that may cause the health problems in many counties. Travel activities provide a certain amount of physical activities, and the active transportation, such as walking and cycling, becomes more important as an essential element of transportation. The active transportation is expected to contribute to improving human health by reducing cardiovascular disease, obesity, and premature death. However, detailed relationship between the transportation choices and human health has not been well understood. Therefore, there is a need for investigating traveler behaviors and how their choices affect physical activities and public health. …

The Effect Of Precursor Design And Processing On The Semi-Crystalline Morphologies Of Polyacrylonitrile-Based Carbon Fiber, Katelyn Cordell

Dissertations

Basic research to control the morphology of polyacrylonitrile (PAN)-based carbon fiber is crucial for next generation composites as it determines their mechanical properties and final use. Poor molecular design of PAN-based precursors and fiber processing causes morphological defects and mechanical limitations.^1,2 This research focused on utilizing the controlled polymerization technique, reversible addition-fragmentation chain transfer (RAFT), of novel acrylamide comonomers to afford well-defined precursors with precisely controlled molecular design. This controlled RAFT technique improved the overall precursor graphitic structure as evident by the increased extent of stabilization and reduced activation energy as compared to precursors prepared by traditional free radical …

Towards Completely Automated Glycan Synthesis, Matteo Panza

Dissertations

Carbohydrates are ubiquitous both in nature as biologically active compounds and in medicine as pharmaceuticals. Although there has been continued interest in the synthesis of carbohydrates, chemical methods require specialized knowledge and hence remain cumbersome. The need for development of rapid, efficient and operationally simple procedures has come to the fore. This dissertation focuses on the development of a fully automated platform that will enable both experts and non-specialists to perform the synthesis of glycans. Existing automated methods for the synthesis of oligosaccharides are highly sophisticated, operationally complex, and require significant user know-how. By contrast, high performance liquid chromatography (HPLC) …

Developmental And Sex Modulated Neurological Alterations In Autism Spectrum Disorder, Azeezat Azeez

Dissertations

Autism Spectrum Disorder (ASD) was first described in 1943 by Dr. Leo Kranner in a case study published in The Nervous Child. It is a neurodevelopment disorder, with a range of clinical symptoms. According to the Diagnostic and Statistical Manual of Mental Disorders (DSM-5), used by clinicians to diagnose mental disorders, a child needs to have persistent social deficits, language impairments, and repetitive behaviors, that cannot be explained by neurological damage or intellectual disability. It is known that children diagnosed with ASD are often are developmentally delayed therefore alterations in the typical developmental trajectory should be a major factor in …

Modulation Of Corticospinal Excitability Induced By Paired Associative Stimulation Combined With Movement, Ahmad O. Alokaily

Dissertations

An essential feature of the brain is its capacity to undergo long-lasting morphological or functional changes in response to experiences or trauma. Advances in noninvasive brain stimulation techniques have led to increased interest in understanding neural mechanisms of neuroplasticity at the network level. Paired associative stimulation (PAS) is one of the most commonly used applications for noninvasive brain stimulation because of its clinical potential as an adjuvant rehabilitative intervention. However, the optimal method for incorporating PAS into rehabilitative activities remains unknown. This dissertation explores different approaches to combining PAS with movement and investigates the enhancement of the specificity of conventional …

Modelling In Vitro Dissolution And Release Of Sumatriptan Succinate From Polyvinylpyrrolidone-Based Microneedles Aided By Iontophoresis, James Paul Ronnander

Dissertations

A novel dissolving microneedle array system is developed to investigate permeation of a sumatriptan succinate formulations through the skin aided by iontophoresis. Three formulations consisting of hydrophilic, positively charged drug molecules encapsulated in a water-soluble biologically suitable polymer, polyvinylpyrrolidone (PVP), have been accepted by the U.S. Food and Drug Administration (FDA). The microneedle systems are fabricated with 600 pyramid-shaped needles, each 500 µm tall, on a 0.785-cm² circular array. In vitro transdermal studies with minipig skin and vertical Franz diffusion cells show > 68% permeation of sumatriptan over a 24-hour period. A combination of microneedle and electrical current density ranging …

Effects Of Electro-Osmotic Consolidation Of Clays And Its Improvement Using Ion Exchange Membranes, Lucas Martin

Dissertations

Electro-osmosis is an established method of expediting consolidation of soft, saturated clayey soils compared to commonly used methods, such as preloading with wick drains. In electro-osmotic consolidation a direct current (DC) is applied via inserted electrodes. This causes hydrated ions in the interstitial fluid to migrate to oppositely charged electrodes. Because the clay particles have a negative surface charge, the majority of ions in the interstitial fluid are positively charged. Therefore, the net flow will be towards the negatively charged electrode (cathode), where the water can be removed and thus consolidation is achieved. Certain problems, such as pH changes in …

Improving Boron For Combustion Applications, Kerri-Lee Annique Chintersingh

Dissertations

Boron has received much attention as a potential additive to explosives and propellants due to its high theoretical gravimetric and volumetric heating values. The challenge, however, is that boron particles tend to agglomerate, have lengthy ignition delays and very low combustion rates. Prior research indicates that boron’s long ignition delays are due to its inhibiting naturally occurring oxide layer, impeding the diffusion of reactants for oxidation. For combustion, current studies report that boron particles have two consecutive stages, but the actual reaction mechanism is poorly understood. Despite many years of relevant research, quantitative combustion data on micron-sized boron particles are …

Analyzing Evolution Of Rare Events Through Social Media Data, Xiaoyu Lu

Dissertations

Recently, some researchers have attempted to find a relationship between the evolution of rare events and temporal-spatial patterns of social media activities. Their studies verify that the relationship exists in both time and spatial domains. However, few of those studies can accurately deduce a time point when social media activities are most highly affected by a rare event because producing an accurate temporal pattern of social media during the evolution of a rare event is very difficult. This work expands the current studies along three directions. Firstly, we focus on the intensity of information volume and propose an innovative clustering …

Optimal Sampling Paths For Autonomous Vehicles In Uncertain Ocean Flows, Andrew J. De Stefan

Dissertations

Despite an extensive history of oceanic observation, researchers have only begun to build a complete picture of oceanic currents. Sparsity of instrumentation has created the need to maximize the information extracted from every source of data in building this picture. Within the last few decades, autonomous vehicles, or AVs, have been employed as tools to aid in this research initiative. Unmanned and self-propelled, AVs are capable of spending weeks, if not months, exploring and monitoring the oceans. However, the quality of data acquired by these vehicles is highly dependent on the paths along which they collect their observational data. The …

Roles Of Surfactant And Binary Polymers On Dissolution Enhancement Of Bcs Ii Drugs From Nanocomposites And Amorphous Solid Dispersions, Md Mahbubur Rahman

Dissertations

Drug nanocomposites and amorphous solid dispersions (ASDs) are two major formulation platforms used for the bioavailability enhancement of BCS Class II drugs. The major drawback of nanocomposites is their inability to attain high drug supersaturation during in vitro (<50% relative supersaturation) and in vivo dissolution. On the other hand, formulating an amorphous solid dispersion (ASD) with high drug loading (>20%) that releases drug rapidly, while generating and maintaining high supersaturation over at least three hours is challenging. The goal of this thesis is to develop a fundamental understanding of the impact of anionic surfactants–polymers on in vitro drug release from nanocomposites and ASDs, while addressing the above challenges. To achieve this goal, the following objectives are set: (1) compare griseofulvin …

Enzymatic Biofuel Cells In A Sandwich Geometry With Compressed Carbon Nanotubes/Enzyme Electrodes & Hybrid Patch Applications, Biao Leng

Dissertations

Enzymatic biofuel cells (EBFCs) convert the chemical energy of biofuels, such as glucose and methanol, into electrical energy by employing enzymes as catalysts. In contrast to conventional fuel cells, EBFCs have a simple membrane-free fuel cell design due to the high catalytic specificity of the enzymes, but the power densities obtained are lower. Although the primary goal of research on EBFCs has been to develop a sustainable power source that can be directly implanted in the human body to power bio-devices, other applications such as the use of a flexible film or fuel cell patch as a wearable power source …

Measurement Of Stresses And Their Effect On Transport In Thin Film Battery Electrodes, Subhajit Rakshit

Dissertations

At the moment, there is a significant push towards environmentally friendly energy production and gasoline-free transportation technologies. As a result, there is a renewed interest in energy storage devices such as lithium-ion batteries which will play a key role in providing energy storage capability for these applications. However, the current battery technology is reaching its limits and may not meet future energy storage demands. The increased demand and the limited lithium reserves in geographically remote areas of the earth will lead to higher cost of Li. The alternative battery technologies, such as sodium-ion batteries, are promising due to their low …

Evaluation Of Data Collection Operations For Real-Time Influenza Surveillance During An Emergency, Yuwen Gu

Dissertations

It is unclear how data collection operations for surveillance alter the disease portrayal that influenza reported trends attempt to provide during an emergency. This study developed a model that simulates the collection and testing of influenza specimens after an outbreak is declared in Michigan. It performed simulation based optimization to understand which operational factors affect the biases between the growth rates of original and observed influenza incidence trends, and to quantify the predictive power of the influenza incidence trends at different points of data collection. The results show that emergency driven high risk perception increases the reporting, which leads to …

Fatigue Performance Of Rc Beams Strengthened With Near Surface Mounted Cfrp Composites, Tamer Ghaith Mousa Eljufout

Dissertations

Bridges have a fundamental role in improving the effectiveness of highways and providing an expedient and express traffic system. Over time, Reinforced Concrete (RC) bridges degrade due to gradually increased traffic loads and environmental deteriorations. Subsequently, service loads might cause higher stresses in concrete and steel reinforcement than stresses considered in the design stage. This affects the structural performance of RC beams and leads to sudden fatigue failure. As such, there is an essential need for rehabilitation to avoid hazards and tragedies.

Carbon Fiber Reinforced Polymer (CFRP) composites are becoming widely used to strengthen RC bridges. Near Surface Mounted (NSM) …

Development Of Heat Transfer Correlations For Low-Reynolds Numbers, Flows In Horizontal Circular Pipes, Latif Eyada Ibraheem

Dissertations

Turbulent flows are intrinsic to most fluid-based engineering systems, including internal combustion engines. In these devices, mixing, scalar transport and heat transfer are both critical for proper operation and challenging to model. In previous work, Kreun et al. [1] modeled a pre-heated intake manifold of a Diesel engine for cold-start simulations. Accurately predicting the heat transfer at the intake port proved to be a challenging task. Existing heat transfer correlations yielded predictions which were (at best) within 20% of the measured values. The discrepancy was attributed to a mismatch between the range of applicability of existing heat transfer models and …

Assessing Infrastructure Elements Using Automated Object Detection Technique In Smart City Applications, Majid Mastali

Dissertations

Nowadays, road features are becoming more complex leading to more complicated complaints regarding urban environments. Point Cloud Data (PCD) processing is an essential element for detecting objects and analysing human driving behavior to identify the variables defining challenging objects and maneuvers in smart cities. PCDs include a range of processing, including indirect processing (e.g., data converting, cleaning process) and direct process (e.g., pass through elevation filter, statistical outlier removal, normal estimation as well as classification). Static and dynamic object detection and analysis are typically considered the most sophisticated options subsumed under PCDs. They involve direct evaluation of both static and …

Methodology To Qualify And Monitor A Chemically Bonded Sand System Used In Foundries, Prayag Pravinbhai Patel

Dissertations

The goal of this dissertation is to establish a new quality control framework that combines a statistical process control (SPC) approach to casting quality for chemically bonded sand systems used in foundries. Foundries in the United States use the American Foundry Society standardized sand testing to monitor chemically bonded sand systems. These standardized tests are inefficient for two reasons. Firstly, standard tests are based on mechanical, physical, chemical and thermal properties of a sand system that do not consider interaction between these properties, but sand casting processes are inherently thermo-mechanical, thermo-chemical and thermo-physical. Secondly, these tests can only detect large …

Blind Separation For Intermittent Sources Via Sparse Dictionary Learning, Annan Dong

Dissertations

Radio frequency sources are observed at a fusion center via sensor measurements made over slow flat-fading channels. The number of sources may be larger than the number of sensors, but their activity is sparse and intermittent with bursty transmission patterns. To account for this, sources are modeled as hidden Markov models with known or unknown parameters. The problem of blind source estimation in the absence of channel state information is tackled via a novel algorithm, consisting of a dictionary learning (DL) stage and a per-source stochastic filtering (PSF) stage. The two stages work in tandem, with the latter operating on …

Probabilistic Spiking Neural Networks : Supervised, Unsupervised And Adversarial Trainings, Alireza Bagheri

Dissertations

Spiking Neural Networks (SNNs), or third-generation neural networks, are networks of computation units, called neurons, in which each neuron with internal analogue dynamics receives as input and produces as output spiking, that is, binary sparse, signals. In contrast, second-generation neural networks, termed as Artificial Neural Networks (ANNs), rely on simple static non-linear neurons that are known to be energy-intensive, hindering their implementations on energy-limited processors such as mobile devices. The sparse event-based characteristics of SNNs for information transmission and encoding have made them more feasible for highly energy-efficient neuromorphic computing architectures. The most existing training algorithms for SNNs are based …