-
Prospective Students
-
Faculty and Staff
-
Current Students
-
Alumni and Friends
The metropolitan areas suffer more traffic, the change in travel time is very complex as it can be influenced by various factors, many of which are also unpredictable. Random forest was applied in the travel time prediction application to overcome the overfitting problem. Furthermore, the attention mechanism is implemented by developing the neural network to capture the inner relationship within the traffic data. The proposed long short memory neural network with attention mechanism method achieves its superior capability for TTP longer than 15 minutes (30 min to 60 min), overcoming the performance issue through long temporal dependency and memory blocks. To validate the accuracy and reliability of proposed models, the proposed approaches are tested using a freeway corridor in Charlotte, North Carolina, using the probe vehicle-based traffic data. Detailed information about the input variables and data preprocessing was presented. The results indicate that all proposed TTP models predicting in 15 minutes show better prediction performance over the other time horizons. A comparison with other prediction methods validates that the proposed hybrid LSTM and RF method can achieve a better prediction performance in accuracy and efficiency, proving its deployment is one of the successful solutions to critical, real-world transportation challenges.
ABSTRACT
WILLIAM RAY LEACH. Ambiguous Loss and Parental Traumatic Brain Injury
(Under the direction of DR. DREW POLLY)
Parental traumatic brain injury (PTBI) and the effect it has on adolescents living in the home has been mostly avoided in the current literature. Even more rare in the literature is the idea of ambiguous loss, coined by Boss (1991). An ambiguous loss refers to a loss of someone who has not died, but who is also not the same person as before the injury, physically or mentally. Consequently, the loss is unclear and requires constant recalibration by the uninjured family members to accept their ever-changing injured family member. Together, no researcher has ever studied ambiguous loss as it relates to PTBI.
This study focused on three research questions:
Research Question 1: As it pertains to PTBI, what is the influence of ambiguous loss when experienced during adolescence?
Research Question 2: When PTBI is experienced in adolescence, how does the perception of ambiguous loss result in tangible consequences later in life?
Research Question 3: In what ways do adolescents experiencing ambiguous loss from PTBI describe their family, self, and situation?
Using a qualitative approach, this phenomenological dissertation found that ambiguous loss affects adolescents in different ways and at different times after the injury has occurred. Ambiguous loss can also result in tangible consequences later in their life. The time since the injury can affect the severity of feelings of ambiguous loss, however, this study also found that PTBI adolescents can exhibit traits of resilience through their experience.
Appropriate infant and child feeding practices and balanced nutrition can significantly reduce malnutrition and can contribute to optimal physical, mental, and developmental growth of children. Childhood obesity is a major public health concern in the United States and is associated with both physical and psychological consequences and decreased health-related quality of life. Early life feeding practices and nutrients intake starting from birth to 2 years can significantly contribute to the development of obesity. This dissertation aimed to develop three manuscripts to understand the association between infant feeding practices including bottle feeding practices, initiation of added sugar and added sugar intake, and children’s BMI-for-age percentile at 36 months old among Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) participants. First manuscript examined the association between added sugar consumption at young age and BMI-for-age percentile at 36 months old among WIC participants. Second manuscript examined factors associated with initiation of added sugar among WIC participants. Third manuscript examined the association between usual daily intake of added sugar at young age and BMI-for-age percentile at 36 months old among WIC participants. Data were from the WIC Infant and Toddler Feeding Practices Study-2 (ITFPS-2). The ITFPS-2, a longitudinal study of WIC participants (mothers and their children) began in 2013. First, Cox proportional hazards model was used to identify factors associated with bottle cessation, and multivariate linear regression to examine the association between age of bottle cessation and BMI. Second, Cox proportional hazards model examined factors associated with introducing added sugar. Third, bivariate analysis was used to examine the association between usual daily intake of added sugar before age 2 years old and BMI-for-age-percentile at 36 months old. The first research study indicates about 34% of children used a bottle longer than 12 months, and 13% longer than 18 months. Bottle cessation at older ages was associated with Hispanic ethnicity, multiparity, low income, low education, higher caregiver weight, and not initiating breastfeeding, and adjusted children’s BMI-for-age percentile at age 36 months increased by 0.47 for each additional month of bottle use. The second research study indicates about 25% of children initiated added sugar at or before 7 months. Contributing factors were caregiver’s race/ethnicity, education, employment, weight status, parity, child sex, and premature birth (all p<0.05). The third research study indicates the mean added sugar intake ≤7 months, 8-13 months, and 14-24 months were 0.23 teaspoon (tsp), 3.44 tsp, and 11 tsp, respectively. Bivariate analysis indicates added sugar intake before 2 years old is associated with children’s BMI-for-age-percentile at 36 months old. These research studies indicate a need for health care advocacy programs and intervention to educate the caregivers to practice appropriate feeding practices among infants and children aged 2 or younger.
Stress wave propagation in granular materials subjected to dynamic loadings has attracted much attention for exploring new physical phenomena. One-dimensional (1D) granular systems, a type of artificially designed granular materials consisting of periodically aligned discrete particles, are demonstrated to produce unprecedented wave properties that are notably different from conventional engineering materials. By designing the critical characteristics of 1D granular systems, a remarkable tunability can be achieved, which yields various engineering applications. Therefore, it is of great significance to fundamentally investigate the stress wave propagation and tunability in 1D granular systems.
Firstly, the solitary wave propagation within 1D granular crystals based on composite cylinders is systematically investigated via experiments, numerical simulations, and theoretical analysis. Next, we investigate the properties of Nesterenko solitary wave supported by one-dimensional granular chains and achieve an equivalent wave transmission among various materials and dimensions. Furthermore, we develop efficient and controllable stress wave attenuation approaches by considering I. Strain-softening behaviors; II. Kirigami-based structures. Finally, we design a 1D cylindrical granular system and comprehensively investigate solitary wave tuning strategies based on the system through mass, modulus, and thickness mismatch. Results unlock the unique solitary wave tuning mechanism and provide design guidance for next-generation signal measurement and monitoring systems.
Historically, standard English language ideologies have been perpetually ingrained in American educational practices and policies (Smitherman, 2017; Wong & Teuben-Rowe, 1997). These practices are not limited to K-12 studies and maintain a position of dominance in higher education (Álvarez-Mosquera & Marín-Gutiérrez, 2020). Calls for diversity in curriculum and pedagogical practices currently involve increasing demands for linguistic inclusion that reflects the diversity of student populations (CCCC, 2020). This study explores how Black women students across the diaspora who use home and/or native languages, dialects, and accents navigate their identities in academic spaces of higher learning where standard English language ideologies are often the only acceptable language varieties that are valued or encouraged. Data was collected through the use of virtual semi-structured interviews using Seidman’s (2006) method of three 90-minute interviews. A single focus group interview with all three participants was conducted as well. All interviews took place during the summer of 2021. Data was analyzed using a qualitative, narrative-based approach that included emphasis on both small stories (De Fina and Georgakopoulou, 2012) and dominant narratives (Lyotard, 1984). This research suggests the experiences of Black women in college composition and communications include themes like feelings of rejection, inadequacies, pressure to conform, and a lack of linguistic agency.
Per- and polyfluoroalkyl substances (PFAS) are fluorinated organic compounds with broad applications in aqueous film-forming foams (AFFF) for firefighting, lubricants, waterproof and stain-resistant products. Perfluorooctanoic acid (PFOA), a legacy PFAS, is toxic and carcinogenic. Currently, PFOA is replaced by the ammonium salt of a perfluoroalkyl ether carboxylic acid known as GenX. Nevertheless, PFOA is expected to be present in the environment for an extended period after its phasing out due to its recalcitrant nature. In addition, GenX is predicted to have similar toxicity as PFOA. Various PFAS, including PFOA and GenX, have been widely detected in surface water and groundwater in the United States and worldwide. The current treatment practice for PFAS fails to provide a permanent solution and is likely to increase the risk of recontamination of surface water and groundwater.
Among various destructive methods, electrochemical mineralization, which uses electric power to transform PFAS into bicarbonate and fluoride, is a promising option. However, past studies on electrochemical mineralization of PFAS have limitations such as low PFAS mineralization and incomplete fluorine mass balance. Hence, this study proposes a sequential treatment with ion exchange to capture and concentrate PFAS in surface water and groundwater into a low volume of brine, followed by electrochemical treatment of the PFAS-containing brine. This study will focus on the electrochemical oxidation part of the treatment train and examine the treatment performance using PFOA, GenX, and AFFF waste streams as examples.
With the worldwide prevalence of obesity doubling over the past 30 years across a wide range of demographic and socioeconomic groups, the obesity epidemic is a major public health challenge today. Excessive food consumption and lack of exercise are two major contributors to obesity. In recent years, these two activities have been integrated into our daily lives together with social media. A growing body of literature delineated how social networks impact people's health-related behaviors and suggested social media has a role in affect people's obesity-related behaviors. This study aims to gain an insightful understanding of which online social factors are impacting users' obesogenic behaviors and explore computational methods to examine those behaviors using social media data.
Our work consists of three overall research aims. In the first aim, a systematic review was conducted to examine online social factors concerning obesity. A total of 1,608 studies that related to obesity and social media were collected from the three most popular electronic databases for the field. After close inspection, 50 studies were further examined and ten types of online social factors were identified within four-level social-ecological model, which was used to explain each factors' potential impact on an individual from varying levels of online social structure to user's connection to the real world. In the second aim, we learned how the local food environment influences state level obesity rate using social media data. Publicly available Yelp and MyFitnessPal data were collected via a novel approach to characterize the local food environment. A statistically significant correlation between the state's food environment and state obesity rate was observed. We further built a computational model to predict the state-level obesity rate using aforementioned data, in which we achieved a Pearson correlation of 0.791 across US states and the District of Columbia. In the third aim, we studied how a major social disrupting event, COVID-19 shutdown, affects users' dietary behavior using social media data. Tweets relating to people's dietary behavior with images from April to June of 2019, 2020, and 2021 were collected. An observational study of behavior patterns was conducted by using image classification models, visualization tools, and text analysis methods. People are found eating more healthier food during complete and partial shutdowns than before Covid-19. Results of this dissertation could help the public health agencies, policymakers, organizations and health researchers to better utilize social media to carry out obesity-related education, obesity surveillance, and develop public health policy to address this challenge.
Optimally modulating a vehicle's speed profile through highway, urban, and suburban environments can result in pronounced fuel savings, particularly with heavy-duty vehicles. However, existing strategies for speed profile optimization traditionally rely on aspirational and often deterministic assumptions, which cease to be accurate in the presence of real-world features such as non-deterministic traffic and actuated signalized intersections. The research in this dissertation establishes a hierarchical Green-Light Approach Speed (h-GLAS) strategy for controlling vehicles traveling through non-deterministic highway, urban, and suburban environments. The h-GLAS strategy utilizes vehicle-to-infrastructure (V2I) communication to receive information about the route's topology, speed limits, and signal phase and timing (SPaT). For suburban environments that employ semi- and fully-actuated signalized intersections, past signal timing information is used forecast the future values of the signal phase lengths. This information is used to construct a desired velocity profile to be tracked by a semi-economic model predictive controller (MPC), which computes the optimal wheel force command for the vehicle. When traveling through highway environments, the desired velocity profile represents a globally optimal dynamic program solution, computed offline before the beginning of a trip. For urban and suburban environments, however, the velocity profile is constructed to allow the vehicle to arrive at upcoming intersections when the probability of a green signal is maximized. The semi-economic MPC minimizes a quadratic objective function, which reflects a trade-off between minimizing mechanical energy expenditure and braking effort, with tracking the supplied desired velocity profile. This MPC is unable to maintain vehicle following constraints without changing its convex nature, so a command governor (CG) is located downstream to maintain vehicle-following constraints efficiently. The CG modifies the MPC's control action by the minimal amount necessary to maintain safe vehicle following. Using the simulation packages from PTV VISSIM, the h-GLAS is validated against real signal timing algorithms within a stochastic traffic environment parameterized by real-world data. Simulation results show that the h-GLAS controller is capable of significantly reducing a vehicle's fuel consumption by 16%-26% when compared to a baseline control strategy traveling through the same suburban environment.
Light is an essential element of building design that influences human health, comfort, performance, and well-being. Humans' daily rhythms in behavior and physiology, such as wake/sleep patterns, have evolved under natural light-dark cycles over millions of years. Nowadays, as we spend a large proportion of our time in the built environment, we are exposed to less light during daytime hours and more light during nighttime hours than what we would have naturally received across day and night. Thus, inappropriate and insufficient personal light exposure during the day and night can negatively affect this standard rhythm and is associated with a range of psychological, physical, and mental health issues. While most lighting design recommendations and standards have been limited to addressing the energy and visual aspects of light, this trend has been criticized, and current standards acknowledge the link between light and human health. Moreover, lack of low-cost and reliable tool to track and monitor the characteristics of light exposure as a stimulus that affects the human circadian system is evident.
This dissertation proposed a novel user-centric lighting assist tool consisting of a low-cost and wearable spectrometer to measure light spectrum and an interactive dashboard to visualize the collected data in meaningful and easy to understand quantities. Three studies covering the proposed tool are presented to 1) develop a low-cost and wearable spectrometer using Artificial Neural Networks (ANNs); 2) examine practical applicability of wearable spectrometer in the real-world environment ; and 3) develop and test the usability of an interactive dashboard for continuous tracking of personal lighting conditions. The first study examines the performance, accuracy, and fabrication challenges of developing a low-cost, wearable and wireless spectrometer to measure Spectral Power Distributions (SPD) of light sources using ANNs. Neural network was identified as an effective method for improving the accuracy of the developed spectrometer. Additionally, the developed spectrometer offers real-time communication that enables it to be integrated into IoT-based intelligent lighting systems for tailoring indoor lighting systems according to individual circadian needs. The second study examines the practical applicability of developed spectrometer to continuously record personal lighting conditions of office workers in real-world environment. The study provides insights for enhancing occupants health and well-being within the built environment. The third study examines the potential of a web-based app to enable healthier living with light. By engaging the end-user directly throughout the entire process of design and development of the interactive dashboard, the study identified the interactive dashboard as a useful and usable tool for end-users.
This dissertation is one of the first attempts to develop a low-cost and wearable spectrometer together with an interactive application to provide vital information regarding the non-visual effects of light on health by real-time tracking of personal lighting conditions. The findings of this dissertation demonstrates the importance of an affordable and accessible human-centric lighting assist tool as a powerful driver of promoting healthy behavior change in buildings, outlining new directions in the design of buildings that are not only comfortable and energy efficient, but also healthier for their occupants.
