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Development And Feasibility Studies Of Ai-Powered Socially Assistive Robotics To Promote Wellbeing Of Persons With Alzheimer’S Disease And Related Dementias, Fengpei Yuan

Doctoral Dissertations

The number of persons living with Alzheimer's Disease and Related Dementias (PLWDs) has been keeping growing. In 2024, it is estimated that there will be approximately 6.7 million individuals living with Alzheimer's Dementia. This number will increase to about 14 million in 2060. Due to the damage in neurons, the capabilities of memory, thinking, and language will decline as the disease progress. As a result, persons with dementia will gradually withdraw from their social activities and become more dependent on others during their activities of daily living. Making it worse, our society is not ready for the increasing requirements of …

Uniting Cognitive Models And Ai: Early Alzheimer’S Screening Through Language Analysis, Ziming Liu

Doctoral Dissertations

Alzheimer's Disease (AD) and related dementias (PwADRD) often lead to memory issues, language difficulties, and cognitive impairments. These symptoms can cause social isolation, anxiety, depression, accelerating cognitive decline, and negatively impacting quality of life. Traditional diagnostic and rehabilitation methods, relying on Artificial Intelligence (AI) or clinical observations, sometimes lack transparency and explainability for the growing population affected by AD. My research aims to address these challenges by developing AI systems that analyze affective states and cognitive deficits in PwADRD interactions. This involves creating more precise diagnostic tools and rehabilitation methods, as well as trustworthy AI agents to improve PwADRD's quality …

Transportation System Performance And Traveler Behavior In The Context Of A Systemwide Shock: Applications Of Data Science Toward A Sustainable Future, A. Latif Patwary

Doctoral Dissertations

The COVID-19 pandemic, a systemwide shock, has left a long-lasting and significant impact on transportation systems. It has contributed to a shift in travel behavior, with many people turning to work from home (WFH) and online shopping. This shift has led to a reduction in vehicular travel. However, the pandemic witnessed increased crash fatalities despite a reduction in overall crashes, disproportionately affecting disadvantaged communities (DACs). The main question arising from these pandemic-related issues is what we can learn to improve transportation systems and shape future travel behavior. Therefore, this dissertation aims to investigate how the transportation system changed during COVID-19 …

Improving Mobility And Safety In Traditional And Intelligent Transportation Systems Using Computational And Mathematical Modeling, Shahrbanoo Rezaei

Doctoral Dissertations

In traditional transportation systems, park-and-ride (P&R) facilities have been introduced to mitigate the congestion problems and improve mobility. This study in the second chapter, develops a framework that integrates a demand model and an optimization model to study the optimal placement of P&R facilities. The results suggest that the optimal placement of P&R facilities has the potential to improve network performance, and reduce emission and vehicle kilometer traveled. In intelligent transportation systems, autonomous vehicles are expected to bring smart mobility to transportation systems, reduce traffic congestion, and improve safety of drivers and passengers by eliminating human errors. The safe operation …

Advanced Air Quality Management With Machine Learning, Cheng-Pin Kuo

Doctoral Dissertations

Air pollution has been a significant health risk factor at a regional and global scale. Although the present method can provide assessment indices like exposure risks or air pollutant concentrations for air quality management, the modeling estimations still remain non-negligible bias which could deviate from reality and limit the effectiveness of emission control strategies to reduce air pollution and derive health benefits. The current development in air quality management is still impeded by two major obstacles: (1) biased air quality concentrations from air quality models and (2) inaccurate exposure risk estimations

Inspired by more available and overwhelming data, machine learning …

A Machine Learning Approach For Predicting Clinical Trial Patient Enrollment In Drug Development Portfolio Demand Planning, Ahmed Shoieb

Masters Theses

One of the biggest challenges the clinical research industry currently faces is the accurate forecasting of patient enrollment (namely if and when a clinical trial will achieve full enrollment), as the stochastic behavior of enrollment can significantly contribute to delays in the development of new drugs, increases in duration and costs of clinical trials, and the over- or under- estimation of clinical supply. This study proposes a Machine Learning model using a Fully Convolutional Network (FCN) that is trained on a dataset of 100,000 patient enrollment data points including patient age, patient gender, patient disease, investigational product, study phase, blinded …

Evaluating Impacts Of Shared E-Scooters From The Lens Of Sustainable Transportation, Nitesh Shah

Doctoral Dissertations

As the popularity of shared micromobility is increasing worldwide, city governments are struggling to regulate and manage these innovative travel technologies that have several benefits, including increasing accessibility, reducing emissions, and providing affordable travel options. This dissertation evaluates the impacts of shared micromobility from the perspective of sustainable transportation to provide recommendations to decision-makers, planners, and engineers for improving these emerging travel technologies.

The dissertation focuses on four core aspects of shared micromobility as follows: 1) Safety: I evaluated police crash reports of motor vehicle involving e-scooter and bicycle crashes using the most recent PBCAT crash typology to provide a …

Emerging Trends In Bus Ridership In The United States, Abubakr Ziedan

Doctoral Dissertations

Public transit ridership in the United States was declining even before the COVID-19 pandemic. Many different factors affect transit ridership levels, and the recent declines in ridership across the country make it critical to assess which factors are causing declines and which may help to increase ridership. Therefore, this dissertation seeks to quantify the impact of three emerging factors on bus ridership: shared electric scooters (e-scooters), new fare payment technologies and policies, and the COVID-19 pandemic.

This dissertation analyzed the impacts of shared e-scooters on bus ridership. This was investigated at the route level in Louisville, KY, and Nashville, TN, …

Design And Development Of The Urban Population Health Observatory To Improve Disease Surveillance And Response, Whitney Brakefield

Doctoral Dissertations

Chronic and infectious diseases have a profound impact on the quality and length of life of populations that suffer from these conditions. Scientists, physicians, and health officials are seeking innovative approaches to decrease the morbidity and mortality of deadly diseases. Incorporating artificial intelligence and data science techniques across the health science domain could improve disease surveillance, intervention planning, and policymaking. In this dissertation, we describe the design and development of the Urban Population Health Observatory (UPHO), an explainable knowledge-based multimodal big data analytics platform. A common challenge for conducting multimodal big data analytics is integrating multidimensional heterogeneous data sources, which …

Nuclear Security Awareness Survey At A University, Marcia P. Robinson, Naomi German, Destiny B. White, Shraddha V. Rane, Jason Timothy Harris

International Journal of Nuclear Security

The concept of assessing safety culture in an organization emerged with its application at the nuclear power industry and has expanded since then. An assessment of nuclear security, on the contrary, is still under-developed, especially at non-nuclear facilities, such as academic institutions and medical facilities. To identify the level of the awareness and understanding of credible nuclear and radiological threats, response preparedness, security culture, and the integrity of nuclear security systems among non-radioactive material users at a university setting; a campus-wide survey was deployed. A total of 3,336 non-radioactive material users, including students, faculty, and staff participated in the survey. …

There From The Beginning: The Women Of Los Alamos National Laboratory Supporting National And International Nuclear Security, Olga Martin, Laura Mcclellan, Octavio Ramos, Heather Quinn

International Journal of Nuclear Security

From the beginning of the Manhattan Project in the early 1940s, the women of what would become Los Alamos National Laboratory (LANL) worked in technical positions alongside their male counterparts, played a key role as computers, and worked in administrative jobs as secretaries, phone operators, bookkeepers, and on behalf of the U.S. Army in the Women’s Army Corps.

Throughout the history of the Laboratory, women experts at LANL helped establish and lead important national and international security programs, with careers in science, technology, engineering, and mathematics. Over time, the women of Los Alamos have come together under various Employee Resource …

Women In Nuclear Science & Technology In India: Challenges & Opportunities, Arpita Datta, Dr. Alpana Goel, Ashok Kumar Jain

International Journal of Nuclear Security

Women have been actively contributing toward frontline research and development of various advanced technologies in the nuclear domain and playing a crucial role in key positions. However, proportional representation of women in various decision-making positions at higher levels in politics, diplomacy, military affairs, science, and technology remains low, and most of these positions remain male-dominated. We see that women often find it difficult to achieve leadership roles for several reasons, but often from an implicit bias in society. The stereotypical image of women in society is still propagated very discreetly. In recent times, Indian women have made big strides in …

Improving Reinforcement Learning Techniques For Medical Decision Making, Matthew Baucum

Doctoral Dissertations

Reinforcement learning (RL) is a powerful tool for developing personalized treatment regimens from healthcare data. In RL, an agent samples experiences from an environment (such as a model of patient health) to learn a policy that maximizes long-term reward. This dissertation proposes methodological and practical developments in the application of RL to treatment planning problems.

First, we develop a novel time series model for simulating patient health states from observed clinical data. We use a generative neural network architecture that learns a direct mapping between distributions over clinical measurements at adjacent time points. We show that this model produces realistic …

Using Survey Data To Understand Ridesourcing In Tennessee: Who, Where, When, And Why?, Cassidy Kilmer Crossland

Masters Theses

With companies like Uber and Lyft leading the way, ridesourcing has grown and continues to grow in popularity in the United States since its introduction just over ten years ago. While research on this new transportation mode has largely focused on national level trends and studies of large metropolitan areas, little has been written about its impacts in smaller and mid-sized cities and states. This paper aims to understand the socioeconomic characteristics and travel behavior trends of those using ridesourcing in less studied regions, using Tennessee as a case study. This thesis has three parts: a literature review of past …

Promoting Nuclear Security Education And Training Activities At Amity University, India, Arpita Datta, Dr. Alpana Goel

International Journal of Nuclear Security

In the present era of global nuclear governance, it is the responsibility of every individual not only the security personals to be accountable for the security of nuclear materials, facilities and radioactive materials. Amity university and other universities of India are the largest educational networks for young professionals who will enter the nuclear programme in India and will be involved in the management of nuclear and other radioactive materials in a wide variety of applications such as hospitals, industrial applications and nuclear facilities. Amity University Uttar Pradesh is taking leading part to sensitize the importance of nuclear security amongst the …

Ecocar Mobility Challenge Communications Plan, Whitney M. Brothers

Chancellor’s Honors Program Projects

No abstract provided.

Increasing Engineering Retention With Mobile Technology: Using Ux/Ui For Us, James H. Cate Jr., Andrey Karnauch, Dakota Sanders, Matt Matto

Chancellor’s Honors Program Projects

No abstract provided.

Irradiation Experiment For Living Insect-Based Radiological Dispersal Device, Braden Goddard, Walid Metwally, Ahmad Ababneh

International Journal of Nuclear Security

People generally associate fear with “nuclear”, “radioactive” and “insects”. It is speculated that a release of radioactive living insects would instill more fear into the general public than a “traditional” style radiological dispersion device (RDD). This paper evaluates the potential threat of an insect-based RDD using experimental data. The results of this project found that insect-based RDDs are an insignificant threat due to the challenges in making insects radioactive enough to pose any danger to humans without killing the insects.

Modeling Root Causes Of Construction Site Fatalities Using Social Network Analysis, Seifeldeen Omar Eteifa

Masters Theses

In spite of the continuing decrease in accident rates in the US Construction industry, accidents are one of the key factors constraining construction industry in terms of cost and time. Fatality rates in the US are more than other developed countries. Research into accident causation included accident occurrence mechanisms, different levels and types of accident causes as and best practices for accident prevention. These efforts, however, did not focus particularly on fatal accidents and did not prioritize the relationships amongst root causes for accidents. Accordingly, this research’s goal is to quantitatively analyze relationships between fatal accident root causes as well …

Analysis Of Nfirs Data For Sensitivity To Foreclosure And Other Select Features, Alexander Meadows Asbury

Masters Theses

Arson is a grave threat to life and property. In the United States, fire information is collected and disseminated through the National Fire Incident Reporting System (NFIRS). Fire records obtained from NFIRS contain a full range of available information. This information includes the initial incident details in addition to investigative information regarding the cause of ignition and factors contributing to ignition. Combating the arson problem is accomplished in large part by understanding the motives and opportunities of those who commit arson. A common motive for arson is financial gain through insurance fraud. By connecting NFIRS data with mortgage and foreclosure …

Developing A Platform For Integrating Disability Issues Into City Municipality Decisions; Case Study: City Of Knoxville, Sravanthi Pamu

Masters Theses

The People with Disabilities (PWD) & Senior Citizen (SC) are isolated from the mainstream society, and they face several barriers in everyday life. There is no communication platform for them to express their concerns, in turn, participate in the city municipality policy decisions related to PWD- & SC-friendly city development. The purpose of this research is to integrate disability and senior citizen issues in the city of Knoxville to the city council decisions. The comprehensive literature search is done to identify the frequently mentioned disability and age-friendly city factors. An effective survey was designed to identify the issues in collaboration …

Evaluation Of Increased Targeted Enforcement And Community-Based Outreach And Education Programs To Increase Nighttime Seatbelt Use In East Tennessee, Kwaku Frimpong Boakye

Doctoral Dissertations

According to the National Highway Traffic Safety Administration (NHTSA), motor vehicle crashes are the leading cause of death among people aged 1-54 in the United Sates. In 2015, the number of motor-vehicle deaths on U.S. roadways totaled 35,092, a 7% increase from 2014 (32,744). Though lower gas prices and increased vehicle mileage combined with risky driving behaviors (e.g. speeding, driving while texting) account for the increased fatality rate, seatbelt non-use has been a significant contributory factor. It is estimated that nearly half (48%) of passenger vehicle occupants involved in fatal crashes each year are unrestrained.

In a recent 2014 report …

Modeling The Consumer Acceptance Of Retail Service Robots, So Young Song

Doctoral Dissertations

This study uses the Computers Are Social Actors (CASA) and domestication theories as the underlying framework of an acceptance model of retail service robots (RSRs). The model illustrates the relationships among facilitators, attitudes toward Human-Robot Interaction (HRI), anxiety toward robots, anticipated service quality, and the acceptance of RSRs. Specifically, the researcher investigates the extent to which the facilitators of usefulness, social capability, the appearance of RSRs, and the attitudes toward HRI affect acceptance and increase the anticipation of service quality. The researcher also tests the inhibiting role of pre-existing anxiety toward robots on the relationship between these facilitators and attitudes …

Learning Multimodal Structures In Computer Vision, Ali Taalimi

Doctoral Dissertations

A phenomenon or event can be received from various kinds of detectors or under different conditions. Each such acquisition framework is a modality of the phenomenon. Due to the relation between the modalities of multimodal phenomena, a single modality cannot fully describe the event of interest. Since several modalities report on the same event introduces new challenges comparing to the case of exploiting each modality separately.

We are interested in designing new algorithmic tools to apply sensor fusion techniques in the particular signal representation of sparse coding which is a favorite methodology in signal processing, machine learning and statistics to …

Using Naturalistic Data For Bicycle Safety Analysis: An Application Of Cyclephilly Data To Assess Wrong-Way Riding, Nirbesh Dhakal

Masters Theses

This study focuses on wrong-way riding and associated route-choice determinants of wrong-way riding. I present this application as a case study of the many types of analysis that are possible with emerging naturalistic datasets that are not limited to conventional methods (e.g., vehicle counters). I used a dataset generated from a smartphone application, CyclePhilly, that measures rider location second-by-second in Philadelphia. The dataset covers 12,202 trips by 300 unique CyclePhilly users collected from May 2014 through April 2016. The data also includes information on socio-economics of the rider, as well as cycling experience. I merged this dataset with complementary network …

Musculoskeletal Loads During Stationary Cycling And The Effects Of Pedal Modifications For Knee Osteoarthritis, Rachel Lynn Thompson

Doctoral Dissertations

Knee OA is a deteriorating joint disease affecting 27 million people in the US and current exercise prescriptions may be improved with new knowledge of their effects on muscle forces and joint contact loads. Cycling rather than other exercise modalities is generally considered an alternative for people with knee OA. If these research objectives were achieved, clinicians would have additional tools related to joint contact loads for treating people with OA with an cycling exercise while controlling progression of OA. The long-term goal of this research is to provide a scientific basis for planning, evaluation and improvement of subject-specific rehabilitation …

Exploring A Semi-Virtual Reality System Impacting Learning Curves Of College Students, Hongbiao Yang

Doctoral Dissertations

Virtual reality (VR) is a trending technology used in a broad range of fields including education and has become one of the most promising directions for educators. In this research, the investigation focuses on how the semi-immersive VR application can be used for educational purposes by exploring the VR factors and the interactions between these factors. A theoretical learning framework is also proposed to offer an explanation for the beneficial effects of education brought by VR at a high level.

This research consists of three parts. First, this research will introduce the development of Walk-in-Place Learning System (WIPLS), a semi-immersive …

Scheduling For Timely Passenger Delivery In A Large Scale Ride Sharing System, Yang Zhang

Masters Theses

Taxi ride sharing is one of the most promising solutions to urban transportation issues, such as traffic congestion, gas insufficiency, air pollution, limited parking space and unaffordable parking charge, taxi shortage in peak hours, etc. Despite the enormous demands of such service and its exciting social benefits, there is still a shortage of successful automated operations of ride sharing systems around the world. Two of the bottlenecks are: (1) on-time delivery is not guaranteed; (2) matching and scheduling drivers and passengers is a NP-hard problem, and optimization based models do not support real time scheduling on large scale systems.

This …

Forecasting Employee Turnover In Large Organizations, Xiaojuan Zhu

Doctoral Dissertations

Researchers and human resource departments have focused on employee turnover for decades. This study developed a methodology forecasting employee turnover at organizational and departmental levels to shorten lead time for hiring employees. Various time series modeling techniques were used to identify optimal models for effective employee-turnover prediction based on a large U.S organization's 11-year monthly turnover data. A dynamic regression model with additive trend, seasonality, interventions, and a very important economic indicator efficiently predicted turnover. Another turnover model predicted both retirement and quitting, including early retirement incentives, demographics, and external economic indicators using the Cox proportional hazard model. A variety …

Adaptive Kernel Estimation For Enhanced Filtering And Pattern Classification Of Magnetic Resonance Imaging: Novel Techniques For Evaluating The Biomechanics And Pathologic Conditions Of The Lumbar Spine, Nicholas Vincent Battaglia

Doctoral Dissertations

This dissertation investigates the contribution the lumbar spine musculature has on etiological and pathogenic characteristics of low back pain and lumbar spondylosis. This endeavor necessarily required a two-step process: 1) design of an accurate post-processing method for extracting relevant information via magnetic resonance images and 2) determine pathological trends by elucidating high-dimensional datasets through multivariate pattern classification. The lumbar musculature was initially evaluated by post-processing and segmentation of magnetic resonance (MR) images of the lumbar spine, which characteristically suffer from nonlinear corruption of the signal intensity. This so called intensity inhomogeneity degrades the efficacy of traditional intensity-based segmentation algorithms. Proposed …