Â鶹ÊÓƵ

Project Investigators: Dr. Berna Eren Tokgoz, Dr. Cagatay Tokgoz, Dr. Ginger Gummelt, Dr. Brian Williams and Dr. Seokyon Hwang

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Natural hazards, including floods, earthquakes, tsunamis, landslides, hurricanes, wildfires, and extreme
temperatures, have been demonstrated to exert significant impacts on global economies and societies.
Numerous structures in the US sustained damage as a result of the combined effects of wave forces and
debris impact during Hurricane Katrina in 2005, Hurricane Sandy in 2012 and Hurricane Harvey in 2017.
Although modeling and simulation tools have seen widespread use in assessing resilience within a typical
community, there is a noticeable scarcity of such tools tailored for integrated community as a system. This
deficit necessitates additional research efforts.
To overcome this necessity, the objective of the proposed research is to develop a customized community
resilience framework based on resilience indices and quantify resilience. The concept of resilience is
heavily influenced by functionality and interdependency, which are critical in determining a resilience
index. Principal Component Analysis (PCA) allows for condensation of data into definable and utilizable
subsets whereas Entropy Weight Method (EWM) assigns specific weights to each indicator, component,
and dimension over time. A significant consideration in this process is the availability of historical
functionality data spanning several years. This approach enables the application of machine learning
algorithms to develop an optimized model capable of predicting a community resilience index for
subsequent years or decades. Therefore, it is evident that this phase requires increased focus and exploration
to develop an innovative model for quantifying composite resilience index.
In this phase, prediction of resilience index will be our main interest. To do prediction, we will identify
methods to enhance our model’s ability to predict the composite resilience index. Supervised machine
learning techniques will be employed to discern genuine trends in the composite resilience index and
effectively predict this index prior to catastrophic events, based on historical data. Specifically, we suggest
utilizing deep learning algorithms such as Neural Network (NN) and non-deep learning algorithms like
Decision Tree Classifiers (DTC) to develop a predictive model. We aim to develop a comprehensive model
that not only represents the current resilience index of a community but also predicts future indices. It is
important to note that the primary reason for employing NN and DTC in constructing the prediction model
is to mitigate the limitations of the EWM model. The EWM model’s dependency on the number of years
can lead to significant errors when used to predict the composite resilience index based on historical data.
Therefore, we will utilize supervised machine learning algorithms for accurate prediction.

Project Investigators: James Henry and Wenhao Yang

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In refinery incidents, immediate action is often necessary to prevent additional equipment
damage and avoid human or environmental impacts. This project utilizes AR to provide real-time
feedback to refinery workers, reducing human error and increasing effective response rates. By
incorporating object recognition and electronic visual feedback, the AR system aims to support
workers in high-stress environments. The project has the potential to expand into emergency
response applications, providing critical information without the need for Internet connectivity.

Project Investigators: Dr. Jing Zhang

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Augmented Reality (AR) is a cutting-edge technology that offers significant potential for resilience analysis by providing interactive and dimmers simulations of various scenarios.

In Phase 1 of our research, we developed an AR platform, specifically designed to analyze resilience against natural disasters, including flooding, hurricanes, and varying weather conditions. This platform has demonstrated its effectiveness in visualizing and preparing for these environmental challenges, enhancing our ability to predict, respond to, and mitigate the impacts of such events.

In Phase 2, the research team aims to build upon this foundation by incorporating resilience analysis for hazards associated with refineries near Â鶹ÊÓƵ. Refinery incidents, including hazardous air emissions and explosions, pose significant risks to surrounding communities, making it crucial to understand and prepare for these potential threats. Texas has experienced several notable refinery incidents in the last 5 years, underscoring the importance of this research. For example, the TPC Group plant explosion in Port Neches in November 2019 caused extensive damage and forced evacuations while releasing hazardous chemicals into the environment. Similarly, the ExxonMobil Baytown Complex explosion in July 2019 led to significant air pollution and subsequent legal actions due to the release of toxic pollutants. Additionally, the Marathon Petroleum fire and the Shell Deer Park fire in 2023 not only resulted in fatalities but also raised major concerns about safety protocols and environmental compliance due to the considerable air pollution they caused. These incidents highlight the frequent and severe nature of refinery-related hazards.

Therefore, we will focus on two main types of refinery incidents, air pollution and explosions in this project for comprehensive resilience analysis. Hazardous air emissions from refineries can lead to long-term health issues, environmental degradation, and legal ramifications. Explosions pose immediate risks to human life, property, and the environment. By integrating simulations of these incidents into our AR platform, we can provide valuable insights into their potential impacts and improve emergency response strategies, and resilience planning.

The deliverables of this project will include an enhanced AR application capable of simulating refinery hazards, detailed 3D models of local refineries, dynamic air emission, and explosion simulations, and comprehensive resilience analysis regarding the refinery hazards. These tools will facilitate better preparedness and response strategies for refinery-related incidents, ultimately contributing to the safety and resilience of Â鶹ÊÓƵ.

This project will benefit research, teaching, and outreach efforts at Â鶹ÊÓƵ. For research, it will provide an efficient tool for studying and mitigating the impacts of refinery incidents. In teaching, the AR platform will serve as an educational resource, allowing students to engage with realistic simulations and develop practical skills in resilience analysis. For outreach, the project will enhance community awareness and preparedness, demonstrating Â鶹ÊÓƵ's commitment to public safety.

By leveraging AR technology to analyze and simulate refinery hazards, this project will contribute to a safer and more resilient community, advancing our understanding of how to effectively respond to and mitigate the impacts of refinery incidents.

Project Investigators:Dan Qi (PI), Brian Williams (Co-PI)

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The Center for Resiliency (CfR) at Â鶹ÊÓƵ has dedicated its purpose to better define and understand resilience, and more specifically, community resilience under a system perspective where all elements of the community play a vital role to the creation of community resilience. The purpose of this research is to better understand the significance of each part of the community (natural, economic and local industry, social services, health care) to local government which is predominantly tasked with providing the support for community resilience to exist. This research takes a two-prong approach to this goal. The first approach is a political behavior analysis of the relationship between political behavior and community resilience. The second approach is a network analysis of the major players reported by local government in addressing resilience concerns.

The political behavior analysis will provide insight to the relationship between local politics and community resilience, shedding light on the influence of diverse population characteristics such as immigration, gender, and economics on the relationship between community stake holders and resilience. The network analysis portion or this project utilizes social network analysis that will allow us to not only identify who plays a role in the community but also the strength of the relationship between each reported community stake holder and local government. This will allow identification of the central, and most influential, community stake holder from the local government perspective. The end state goal is to provide stakeholders in the Center for Resiliency with a perspective of the role that each subsystem (natural, built infrastructure, economic financial, social-human-cultural, political-government) plays in community resilience. This knowledge will allow communities to identify weaknesses in the community resilience system to strengthen relations and thus community resilience. 

Project Investigators: Brielle Frost and Stephan Malick

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Dr. José Valentino is a four-time Latin Grammy Award winner who is versatile in the realms of jazz, business, communications, recording, and entrepreneurship. Brielle Frost and Stephan Malick will work in collaboration to bring José Valentino to Â鶹ÊÓƵ for a guest artist residency during the 2025 spring semester. This multi-disciplinary initiative will engage students, faculty, and organizations across campus to explore crucial roles of resilient communication, media, business, and the arts in supporting community recovery following mass trauma events.
As an emerging Hispanic serving institution, Â鶹ÊÓƵ is committed to fostering an environment where students feel represented and included. This artist residency will help reinforce cultural identity by offering students an opportunity to see themselves reflected in an artist while helping them cultivate a resilient mindset. Artistic musical performances and experiences such as this are important to our culture and society. They sustain us through difficult times and crises and give us an opportunity to come together as a community. Southeast Texas has endured significant trauma from environmental crises and natural disasters, leading to economic and social hardships. In moments of adversity, people seek to be entertained and uplifted, finding resiliency and solace in the shared experience of music. 

Project Investigators: Anna M. Jilla, Laura Coco, Yangyang Deng, Connie Howard, Peter Hansen and Carole Johnson.

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Hearing loss is a recognized disability under educational and civil law, affecting nearly 3,000,000
Texans. Timely access to hearing healthcare is crucial for mitigating the insidious effects of untreated
hearing loss in children and adults. However, the licensed Texas audiology workforce of ~1,000 in Texas
is insufficient for meeting Texas’s growing hearing healthcare needs, particularly for vulnerable, low income populations served through state-coordinated Medicaid health plans. Anecdotal reports suggest
declining audiologist networks in Texas Medicaid programs, limiting access for beneficiaries who may
already face barriers such as cost and transportation. The present investigation aims to promote resiliency of vulnerable low-income Texans with hearing loss by: (1) characterizing the geographic dispersion of Medicaid-enrolled audiology providers in Texas, considering service regions, rurality, and US-Mexico Border Health Initiative designations, and (2)evaluating the longitudinal participation trends of Medicaid-enrolled audiology providers in Texas. This investigation will explore strategies to enhance resiliency, such as telehealth services and community advocacy for improved healthcare policies. This state-level analysis is essential for informing future health policy, public health interventions, and supporting access to hearing healthcare services among vulnerable low-income populations in Texas with co-occurring hearing disabilities.