Publications (2020-2021)

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http://hdl.handle.net/1969.1/194912

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    Design, Development, Implementation and Operation of CBTS-SGL Data Lake System to Produce Risk Analytics of Supply Chains Impacted by COVID-19 and Other Converging Threats Presentation Recording
    (Stochastic Geomechanics Laboratory, 2021-05-21) Duran Sierra, Guillermo; Medina-Cetina, Zenon; Pompelli, Gregory; Cochran, Matt; Sanchez-Siordia, Oscar; Rojas-Solis, Minerva; Olivares, Miriam; Perez-Patron, Maria Jose; Alvarado, Juan Pablo; Zarate-Losoya, Enrique; United States Department of Homeland Security (DHS)
    To address the public health impacts of the COVID-19 pandemic and other converging Threats on the U.S.- Mexico trade it is critical to support all health supply chain systems for both infrastructure and workforce, and to do it accounting for the inherent cultural regional differences, and considering the current and emerging regional social, economic and environmental risks.
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    Towards a Risk Index for the U.S.-Mexico Supply Chains - A Synthetic Case Study in U.S.-Mexico Border Land Ports of Entry
    (Stochastic Geomechanics Laboratory, 2021-09-21) Boze, Connor; Alvarado, Juan Pablo; Hernawan, Billy; Duran Sierra, Guillermo; Medina-Cetina, Zenon; Pompelli, Gregory; Cochran, Matt; United States Department of Homeland Security (DHS)
    The U.S. - Mexico border has a great significance for the movement of people, but also for the commercial trade. Different industries and supply chains, instrumental for the economic activity of both countries, are involved. To assess their state of risk, and manage potential disruptions at the ports, this study presents a proposal for a Risk Index applied to the border ports of entry, and their related U.S.-Mexico supply chains. In this study, we generated indexes based on an innovative Risk Framework as an extension of the CDC Social Vulnerability Index. This Risk framework defines the Risk as a function of the threats, the system vulnerabilities, and the impact on the systems. The different indexes were obtained through a series of socioeconomic and public health system capacity factors from data sources across both countries. The obtained risk index is a powerful tool to analyze binational supply chain vulnerabilities as it directly gives spatial information on the binational state of risk. Additionally, Risk index values, together with the location of ports of entry, can be used to study the effect that the state of vulnerability has on various metrics affecting supply chains.
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    CBTS-SGL Webinar - The U.S. Census Bureau's Community Resilience Estimates- Dr. Bethany DeSalvo
    (Stochastic Geomechanics Laboratory, 2021-03-03) DeSalvo, Bethany; Medina-Cetina, Zenon; Pompelli, Gregory; Cochran, Matt; Olivares, Miriam; Perez-Patron, Maria Jose; United States Department of Homeland Security (DHS)
    On March, 2021 the CBTS COE, and the Stochastic Geomechanics Laboratory (SGL) organized a webinar with Dr. Bethany DeSalvo from the U.S. Census Bureau as a guest speaker to present the methodology behind the Community Resilience Estimates (CRE). The CRE provide an easily understood metric for how at-risk every neighborhood in the United States is to the impacts of COVID-19. This metric uses granular data to measure the individual and community's ability to respond to the effects of the pandemic. Information from the CRE could be easily utilized by policy makers to inform vaccine distribution, where to provide education on public health standards, and pinpoint areas that are at a greater risk of inequitable incomes.
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    Evaluación y Administración del Estado de Riesgo de las Cadenas de Suministro por COVID-19 entre México y Estados Unidos: Presentación y Mesa Panel
    (Stochastic Geomechanics Laboratory, 2021-05-20) Medina-Cetina, Zenon; Duran Sierra, Guillermo; Zarate-Losoya, Enrique; Alvarado, Juan Pablo; Pompelli, Gregory; Cochran, Matt; Olivares, Miriam; Perez-Patron, Maria Jose; United States Department of Homeland Security (DHS)
    During this presentation, members of the Stochastic Geomechanics Laboratory at Texas A&M University presented their work of two different research projects. The projects, hosted at the Center Of Excellence CBTS are related to the Risk Assessment and Management of supply chains between The U.S. and Mexico. After the presentation, a panel with question from the attendees followed.
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    R7 - Model Development for Risks posed by COVID-19 on U.S. Trade Supply Chain Infrastructure. Semi-annual Report - Year 1
    (Stochastic Geomechanics Laboratory, 2020-11-24) Medina-Cetina, Zenon; Pompelli, Gregory; Cochran, Matt; Alvarado, Juan Pablo; Duran Sierra, Guillermo; United States Department of Homeland Security (DHS)
    Semi annual report of R7 project: R7 - Model Development for Risks posed by COVID-19 on U.S. Trade Supply Chain Infrastructure. The report lists and details on the activities conducted from June 2020 to November 2020.
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    R13-CBTS-SGL Semi-Annual Report
    (Stochastic Geomechanics Laboratory, 2020-11-24) Zarate-Losoya, Enrique; Duran Sierra, Guillermo; Medina-Cetina, Zenon; Pompelli, Gregory; Cochran, Matt; Olivares, Miriam; Perez-Patron, Maria Jose; Alvarado, Juan Pablo; United States Department of Homeland Security (DHS)
    The project's milestones include the integration of a triple-helix Binational Taskforce, production of spatio-temporal near real-time analytics following a risk systems approach, and publication of a monthly U.S.-Mexico COVID-19 Risk bulletin.
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    CBTS-SGL Webinar - Cool Things That One Can Do With Graphical Probabilistic Models - Dr. Marek Drudzel
    (Stochastic Geomechanics Laboratory, 2021-01-12) Drudzel, Marek; Medina-Cetina, Zenon; Pompelli, Gregory; Cochran, Matt; Olivares, Miriam; Perez-Patron, Maria Jose; United States Department of Homeland Security (DHS)
    On January, 2021 the CBTS COE and the Stochastic Geomechanics Laboratory (SGL) organized a webinar with Dr. Marek Drudzel as a guest speaker to give a presentation on graphical probabilistic models, and their potential applications to real-world problems. The talk reviewed briefly the theoretical foundations of Bayesian networks and their applications to practical problems. Dr. Drudzel showed several flavors of Bayesian networks, such as discrete, continuous, and hybrid networks, as well as qualitative, and dynamic networks. He also reviewed some applications of Bayesian network models in diagnosis, prognosis, data analysis, and strategic planning. Part of the talk was based on live demonstration of the concepts using GeNIe, a software developed originally in Dr. Druzdzel's lab at the University of Pittsburgh.
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    Model Development for Risks posed by COVID-19 on U.S. Trade Supply Chain Infrastructure - Presentation video
    (Stochastic Geomechanics Laboratory, 2021-04-29) Lopez-Acosta, Araceli; United States Department of Homeland Security (DHS)
    Video created for the R7 project: Project: Model Development for Risks posed by COVID-19 on U.S. Trade supply chains Infrastructure. The video presents the main objectives of the project, as well, as the Risk Assessment Framework, and methods to fulfill them
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    R7 - Internal Report on Bayesian Risk Assessment & Management Model Development V0.0
    (Stochastic Geomechanics Laboratory, 21-Feb) Medina-Cetina, Zenon; Pompelli, Gregory; Cochran, Matt; Alvarado, Juan Pablo; Duran Sierra, Guillermo; Zarate-Losoya, Enrique; Allen, Alexi; United States Department of Homeland Security (DHS)
    Internal report on the development steps for a Risk Assessment and Management model using Bayesian Networks. The objectives of the model include: mapping qualitatively participating processes needed to simulate prognosis and diagnosis scenarios of social, economic and environmental impacts posed by COVID19 on the U.S. trade supply chain infrastructure. To address the public health impacts of the COVID-19 pandemic on the U.S.- Mexico health supply chain systems for health infrastructure and for the health of the workforce, considering current and emerging regional social, economic and environmental Risks. To generate risk-mitigating strategies based on resiliency and sustainability supported by evidence collection and the associate risk assessment model, to address causes and effects posed by COVID19 on the U.S. trade supply chain infrastructure, U.S.- Mexico health supply chain systems for health infrastructure, and for health of the workforce between U.S. - Mexico.
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    R7 - Internal Report on Bayesian Risk Assessment & Management Model Development V1.0
    (Stochastic Geomechanics Laboratory, 2021-05-24) Medina-Cetina, Zenon; Pompelli, Gregory; Cochran, Matt; Alvarado, Juan Pablo; Duran Sierra, Guillermo; Zarate-Losoya, Enrique; United States Department of Homeland Security (DHS)
    The version 0.0 of the Bayesian Networks (BN) model was updated to include variables and processes identified during the development of R7 project, guided by the variables present in Social Vulnerability Indexes from both Mexico and The U.S. This internal report lists the indexes that complement the BN model, as well as the updated structure of the components, groups, and subgroups of the model.
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    R13-CBTS-SGL Monthly Risk Bulletin October 2020
    (Stochastic Geomechanics Laboratory, 2020-11-03) Zarate-Losoya, Enrique; Duran Sierra, Guillermo; Medina-Cetina, Zenon; Pompelli, Gregory; Cochran, Matt; Olivares, Miriam; Perez-Patron, Maria Jose; Alvarado, Juan Pablo; Lopez-Acosta, Araceli; United States Department of Homeland Security (DHS)
    The objective of the Monthly Risk-Bulletin is to provide an overview a) of lessons learned during the past month in the project, b) of a score-card-type system to communicate the state of risk of supply chains impacted by COVID-19 supporting health infrastructure and the workforce between the U.S. and Mexico, and c) of a communication system to facilitate the restoration of broken supply chains and the formation of new ones to reactivate trade between U.S. and Mexico.
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    R13-CBTS-SGL Monthly Risk Bulletin September 2020
    (Stochastic Geomechanics Laboratory, 2020-10-26) Zarate-Losoya, Enrique; Duran Sierra, Guillermo; Medina-Cetina, Zenon; Pompelli, Gregory; Cochran, Matt; Olivares, Miriam; Perez-Patron, Maria Jose; Alvarado, Juan Pablo; Lopez-Acosta, Araceli; United States Department of Homeland Security (DHS)
    The objective of the Monthly Risk-Bulletin is to provide an overview a) of lessons learned during the past month in the project, b) of a score-card-type system to communicate the state of risk of supply chains impacted by COVID-19 supporting health infrastructure and the workforce between the U.S. and Mexico, and c) of a communication system to facilitate the restoration of broken supply chains and the formation of new ones to reactivate trade between U.S. and Mexico.
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    R13-CBTS-SGL Monthly Risk Bulletin November 2020
    (Stochastic Geomechanics Laboratory, 2020-12-04) Duran Sierra, Guillermo; Medina-Cetina, Zenon; Pompelli, Gregory; Cochran, Matt; Olivares, Miriam; Perez-Patron, Maria Jose; Alvarado, Juan Pablo; Lopez-Acosta, Araceli; United States Department of Homeland Security (DHS)
    The objective of the Monthly Risk-Bulletin is to provide an overview a) of lessons learned during the past month in the project, b) of a score-card-type system to communicate the state of risk of supply chains impacted by COVID-19 supporting health infrastructure and the workforce between the U.S. and Mexico, and c) of a communication system to facilitate the restoration of broken supply chains and the formation of new ones to reactivate trade between U.S. and Mexico.
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    R13-CBTS-SGL Monthly Risk Bulletin January 2021
    (Stochastic Geomechanics Laboratory, 2021-02-12) Duran Sierra, Guillermo; Medina-Cetina, Zenon; Pompelli, Gregory; Cochran, Matt; Olivares, Miriam; Perez-Patron, Maria Jose; Alvarado, Juan Pablo; Lopez-Acosta, Araceli; United States Department of Homeland Security (DHS)
    The objective of the Monthly Risk-Bulletin is to provide an overview a) of lessons learned during the past month in the project, b) of a score-card-type system to communicate the state of risk of supply chains impacted by COVID-19 supporting health infrastructure and the workforce between the U.S. and Mexico, and c) of a communication system to facilitate the restoration of broken supply chains and the formation of new ones to reactivate trade between U.S. and Mexico.
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    R13-CBTS-SGL Monthly Risk Bulletin February 2021
    (Stochastic Geomechanics Laboratory, 2021-03-03) Zarate-Losoya, Enrique; Duran Sierra, Guillermo; Medina-Cetina, Zenon; Pompelli, Gregory; Cochran, Matt; Olivares, Miriam; Perez-Patron, Maria Jose; Alvarado, Juan Pablo; Lopez-Acosta, Araceli; United States Department of Homeland Security (DHS)
    The objective of the Monthly Risk-Bulletin is to provide an overview a) of lessons learned during the past month in the project, b) of a score-card-type system to communicate the state of risk of supply chains impacted by COVID-19 supporting health infrastructure and the workforce between the U.S. and Mexico, and c) of a communication system to facilitate the restoration of broken supply chains and the formation of new ones to reactivate trade between U.S. and Mexico.
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    R13-CBTS-SGL Monthly Risk Bulletin April 2021
    (Stochastic Geomechanics Laboratory, 2021-05-10) Duran Sierra, Guillermo; Medina-Cetina, Zenon; Pompelli, Gregory; Cochran, Matt; Olivares, Miriam; Perez-Patron, Maria Jose; Alvarado, Juan Pablo; Lopez-Acosta, Araceli; United States Department of Homeland Security (DHS)
    The objective of the Monthly Risk-Bulletin is to provide an overview a) of lessons learned during the past month in the project, b) of a score-card-type system to communicate the state of risk of supply chains impacted by COVID-19 supporting health infrastructure and the workforce between the U.S. and Mexico, and c) of a communication system to facilitate the restoration of broken supply chains and the formation of new ones to reactivate trade between U.S. and Mexico.
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    R13-CBTS-SGL Monthly Risk Bulletin December 2020
    (Stochastic Geomechanics Laboratory, 2020-12-21) Duran Sierra, Guillermo; Medina-Cetina, Zenon; Pompelli, Gregory; Cochran, Matt; Olivares, Miriam; Perez-Patron, Maria Jose; Alvarado, Juan Pablo; Lopez-Acosta, Araceli; United States Department of Homeland Security (DHS)
    The objective of the Monthly Risk-Bulletin is to provide an overview a) of lessons learned during the past month in the project, b) of a score-card-type system to communicate the state of risk of supply chains impacted by COVID-19 supporting health infrastructure and the workforce between the U.S. and Mexico, and c) of a communication system to facilitate the restoration of broken supply chains and the formation of new ones to reactivate trade between U.S. and Mexico.
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    CBTS-SGL Webinar - Breaking Silos. The power of collaboration and abstraction - Catalina Herrera (Dataiku)
    (Stochastic Geomechanics Laboratory, 2021-08-16) Herrera, Catalina; Medina-Cetina, Zenon; Pompelli, Gregory; Cochran, Matt; Olivares, Miriam; Perez-Patron, Maria Jose; United States Department of Homeland Security (DHS)
    As part of the CBTS's Distinguished Speaker Series, CBTS and SGL presented the webinar "Breaking Silos: the power of collaboration and abstraction", by Dataiku's Senior Engineer Catalina Herrera. This webinar introduced examples of a community working together to deliver a common end result using (and reusing data) to maximize community outcomes. It also presented how to leverage Dataikus capabilities to a wide spectrum of applications, including Data4Good, wind turbines with public data, Co2 emissions, among others, to help drive understanding of how to deliver and consume data and insights from many diverse data sources, including observations, model predictions, and experts knowledge (i.e. evidence). The presentation showed how once you break down silos, its important to enhance data products through collaboration, and leverage Machine Learning / Artificial Intelligence to deliver applied data science as transparent consumables.
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    CBTS- TAMU-SGL R-13 Project: U.S.-Mexico Risk Taskforce to Support the Health Supply Chain Systems Video
    (Stochastic Geomechanics Laboratory, 2021-04-29) Medina-Cetina, Zenon; Pompelli, Gregory; Cochran, Matt; Perez-Patron, Maria Jose; Zarate-Losoya, Enrique; Duran Sierra, Guillermo; Alvarado, Juan Pablo; Lopez-Acosta, Araceli; United States Department of Homeland Security (DHS)
    R-13 CBTS-TAMU is a strategic collaboration to improve supply-chain resilience and sustainability on multi-sectorial trade between U.S. and Mexico. The project's milestones include the integration of a triple-helix Binational Taskforce, production of spatio-temporal near real-time analytics following a risk systems approach, and publication of a monthly U.S.-Mexico COVID-19 Risk bulletin.
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    R13-CBTS-SGL Monthly Risk Bulletin May 2021
    (Stochastic Geomechanics Laboratory, 2021-05-14) Duran Sierra, Guillermo; Medina-Cetina, Zenon; Pompelli, Gregory; Cochran, Matt; Olivares, Miriam; Perez-Patron, Maria Jose; Alvarado, Juan Pablo; Lopez-Acosta, Araceli; United States Department of Homeland Security (DHS)
    The objective of the Monthly Risk-Bulletin is to provide an overview a) of lessons learned during the past month in the project, b) of a score-card-type system to communicate the state of risk of supply chains impacted by COVID-19 supporting health infrastructure and the workforce between the U.S. and Mexico, and c) of a communication system to facilitate the restoration of broken supply chains and the formation of new ones to reactivate trade between U.S. and Mexico.