Engineering Commons^™

Crash Injury Severity Prediction With Artificial Neural Networks, Rima Abisaad

Dissertations

Motor vehicle crashes are one of our nation's most serious social, economic and health issues. They are the leading cause of death among children and young adults, killing approximately 1.35 million people each year. Providing a safe and efficient transportation system is the primary goal of transportation engineering and planning. To help reduce traffic fatalities and injuries on roadways, crash prediction models are used to forecast the injury severity of potential crashes and apply precautionary countermeasures accordingly. Most of these models are reactive as they use historical crash data to categorize crash-related factors. Recently, advancements have been made in developing …

Analysis Of Container Throughput: Demand Forecast And Seaport Competitiveness Assessment, Hussain Talat Sulaimani

Dissertations

Seaports play a crucial role in the container industry, where they act as important nodes in the transport chain to facilitate international trade. In a competitive market, port capacity plays a significant role in defining its competitive position to attract demand and avoid congestion. Failing to provide suitable capacity results in the loss of market share. Therefore, port decision-makers face the challenge of maintaining and developing suitable port facilities to provide efficient services to port users. One of the aspects that decision-makers consider in the planning and development process is analyzing container demand. The analysis of container demand can be …

Selective Neural Stimulation By Leveraging Electrophysiological Diversity And Using Alternative Stimulus Waveforms, Bemin Ghobreal

Dissertations

Efforts on finding the principle mechanism for selective neural stimulation have concentrated on segregating the neurons based on their size and other geometric factors. However, neuronal subtypes found in different parts of the nervous system also differ in their electrophysiological properties. The primary objective of this study is to investigate the feasibility of selective activation of neurons by leveraging the diversity seen in passive and active membrane properties.

Using both a local membrane model and an axon model based on the CRRSS, the diversity of electrophysiological properties is simulated by varying four model parameters (membrane leakage-Gleak and capacitance-Cm, temperature coefficient-Ktemp, …

Private Sound Environments In Public Space: Use Of Headphones In Public Parks And Public Transit, Chathurthi S. De Silva

Dissertations

The use of headphones is now so commonplace that it is almost second nature for many people to use them. Not only do these people use headphones all the time, but they use them nearly everywhere, including in urban public spaces. In using headphones, people create their own “private sound environments” in public space. This phenomenon merits attention from researchers since the creation of private sound environments may well alter people’s experiences of public space.

This study answers five research questions about the use of headphones in parks and on transit: why people use them, when they begin using headphones …

Using Fnirs As An Objective Measure Of Susceptibility To Informational Masking, Min Zhang

Dissertations

Resolving complicated auditory scenes is crucial for daily communication where background sound is often present. However, most hearing aid (HA) and cochlear implant (CI) users have difficulties understanding speech when competing sound sources are present, resulting in reduced job opportunities and increased risk for social isolation. Perceptual interference from background sound is called auditory masking. At least two distinct masking phenomena exist, called energetic and informational masking (EM and IM).

In the first masking phenomenon, EM, target and masker energies coincide at the same time and frequency. Computational and physiological models of cochlear auditory processing can reliably predict listeners' performances …

Drone-Assisted Emergency Communications, Di Wu

Dissertations

Drone-mounted base stations (DBSs) have been proposed to extend coverage and improve communications between mobile users (MUs) and their corresponding macro base stations (MBSs). Different from the base stations on the ground, DBSs can flexibly fly over and close to MUs to establish a better vantage for communications. Thus, the pathloss between a DBS and an MU can be much smaller than that between the MU and MBS. In addition, by hovering in the air, the DBS can likely establish a Line-of-Sight link to the MBS. DBSs can be leveraged to recover communications in a large natural disaster struck area …

Investigating The Combined Effects Of Whole Body Vibration And Vestibular Stimulation On Spasticity And Dystonia In Cerebral Palsy, Peter A. Michael

Dissertations

This study identifies and addresses three voids and potential shortcomings associated with the classification, assessment and management of Cerebral Palsy (CP). These concerns should not undermine the significant advancement that has been made in this specific branch of rehabilitation, but addressing them is necessary. Cerebral Palsy is a group of motor impairments due to hypoxic-ischemic brain damage around the time of birth and very commonly manifests as excessive muscle tone and poor motor control. There are classifications within CP including spasticity and dystonia.

First, a level of discrepancy is present in the classification of CP between the clinical and research …

Subspace Portfolios: Design And Performance Comparison, Anqi Xiong

Dissertations

Data processing and engineering techniques enable people to observe and better understand the natural and human-made systems and processes that generate huge amounts of various data types. Data engineers collect data created in almost all fields and formats, such as images, audio, and text streams, biological and financial signals, sensing and many others. They develop and implement state-of-the art machine learning (ML) and artificial intelligence (AI) algorithms using big data to infer valuable information with social and economic value. Furthermore, ML/AI methodologies lead to automate many decision making processes with real-time applications serving people and businesses. As an example, mathematical …

Neurobiological Markers For Remission And Persistence Of Childhood Attention-Deficit/Hyperactivity Disorder, Yuyang Luo

Dissertations

Attention-deficit/hyperactivity disorder (ADHD) is one of the most prevalent neurodevelopmental disorders in children. Symptoms of childhood ADHD persist into adulthood in around 65% of patients, which elevates the risk for a number of adverse outcomes, resulting in substantial individual and societal burden. A neurodevelopmental double dissociation model is proposed based on existing studies in which the early onset of childhood ADHD is suggested to associate with dysfunctional subcortical structures that remain static throughout the lifetime; while diminution of symptoms over development could link to optimal development of prefrontal cortex. Current existing studies only assess basic measures including regional brain activation …

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-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 …

Estimating Vehicles Emissions At Signalized Intersections In The Highway Capacity Manual, Yuanyuan Fan

Dissertations

Over the past decades, motor vehicle volumes have continued to increase at a high rate. As a result, engineers in the transportation field not only need more robust knowledge of traffic operation control and transportation planning, but more attention is also needed to understand and estimate the influences that this increasing volume of vehicles has on the environment, especially the influence on air quality. The EPA has stated that reducing carbon monoxide (CO) from vehicle emissions is the most significant way to control air pollution from the transportation sector.

The Highway Capacity Manual is a national and international resource that …