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Articles 1 - 7 of 7
Full-Text Articles in Risk Analysis
Full Disclosure: Model Uncertainty In Adjusting For Confounders, Dieudonne Dusenge
Full Disclosure: Model Uncertainty In Adjusting For Confounders, Dieudonne Dusenge
Graduate Theses and Dissertations
This study examines the role of knowledge about underlying causal relationships in classifying controls in order to mitigate omitted- and included-variable biases. Using simulations and accounting examples, the study shows that the researcher may not distinguish good and bad controls because the underlying causal relationships are unobservable, and remedying strategies (such as the relative timing of measurement) may not remove the uncertainty in the classification. Because of the uncertainty about which controls to use, two or more models will be credible as will the distinct estimates derived from them. Next, the study shows that the current standard practice of singling …
Predicting The Likelihood And Scale Of Wildfires In California Using Meteorological And Vegetation Data, Matthew Walters
Predicting The Likelihood And Scale Of Wildfires In California Using Meteorological And Vegetation Data, Matthew Walters
Graduate Theses and Dissertations
Wildfires have devastating ecological, environmental, economical, and public health impacts through the deterioration of water and air quality, CO2 emissions, property damage, and lung illnesses. The early detection and prevention of wildfires allow for the minimization of these risks. The use of Artificial Intelligence (AI) in wildfire detection and prediction has been highly researched as a tool to assist firefighters in stopping wildfires in its early stages. The three common wildfire prediction categories include image and video detection, behavior prediction, and susceptibility prediction. Data such as climate, weather, vegetation, satellite images, and historical wildfire data is most commonly used. Many …
Optimization Of Vaccine Supply Chains In Low- And Middle-Income Countries Utilizing Drones, Maximilian Kolter
Optimization Of Vaccine Supply Chains In Low- And Middle-Income Countries Utilizing Drones, Maximilian Kolter
Graduate Theses and Dissertations
Despite tremendous efforts from governments and humanitarian organizations, millions of children in low- and low-middle-income countries (LICs and LMICs) are still excluded from the benefits of immunization. The vaccine distribution in LICs and LMICs is challenging for several reasons, such as limited cold chain capacities, vaccine wastage, uncertain demand, and lack of access to immunization services. A promising avenue to address these issues is the utilization of drones for vaccine delivery. Drones can fly at high speed on direct paths and could enable on-demand deliveries to mitigate limited storage capacities. Further, their independence of road networks could allow them reaching …
Resilience-Driven Post-Disruption Restoration Of Interdependent Critical Infrastructure Systems Under Uncertainty: Modeling, Risk-Averse Optimization, And Solution Approaches, Basem A. Alkhaleel
Resilience-Driven Post-Disruption Restoration Of Interdependent Critical Infrastructure Systems Under Uncertainty: Modeling, Risk-Averse Optimization, And Solution Approaches, Basem A. Alkhaleel
Graduate Theses and Dissertations
Critical infrastructure networks (CINs) are the backbone of modern societies, which depend on their continuous and proper functioning. Such infrastructure networks are subjected to different types of inevitable disruptive events which could affect their performance unpredictably and have direct socioeconomic consequences. Therefore, planning for disruptions to CINs has recently shifted from emphasizing pre-disruption phases of prevention and protection to post-disruption studies investigating the ability of critical infrastructures (CIs) to withstand disruptions and recover timely from them. However, post-disruption restoration planning often faces uncertainties associated with the required repair tasks and the accessibility of the underlying transportation network. Such challenges are …
Airport Security Investment Model, Joshua Daniel Bolton
Airport Security Investment Model, Joshua Daniel Bolton
Graduate Theses and Dissertations
In an increasingly mobile and diverse world, it is difficult to quantify the risk, or danger, associated with traveling. Airports have suffered greatly for being unable to define potential risks and protect against them. Intelligent adversary risk is a complicated high-level issue for many airports. Airports are targeted because of the large amount of people in a confined space and the social, economic, and psychological impact of terrorist attacks on the American people. In the months following September 11th, 2001, the airline industry in the United States lost $1.1 billion in revenue. The American people stayed grounded, for fear of …
Incorporating A New Class Of Uncertainty In Disaster Relief Logistics Planning, Emre Kirac
Incorporating A New Class Of Uncertainty In Disaster Relief Logistics Planning, Emre Kirac
Graduate Theses and Dissertations
In recent years, there has been a growing interest among emergency managers in using Social data in disaster response planning. However, the trustworthiness and reliability of posted information are two of the most significant concerns, because much of the user-generated data is initially not verified. Therefore, a key tradeoff exists for emergency managers when considering whether to incorporate Social data in disaster planning efforts. By considering Social data, a larger number of needs can be identified in a shorter amount of time, potentially enabling a faster response and satisfying a class of demand that might not otherwise be discovered. However, …
Reliability Analysis Of Social Networks, Kellie R. Schneider
Reliability Analysis Of Social Networks, Kellie R. Schneider
Graduate Theses and Dissertations
The primary focus of this dissertation is on the quantification of actor interaction and the dissemination of information through Social networks. Social networks have long been used to model the interactions between people in various Social and professional contexts. These networks allow for the explicit modeling of the complex interrelations between relevant individuals within an organization and the role they play in the decision making process. This dissertation considers Social networks represented as network flow models in which actors have the ability to provide some level of influence over other actors within the network. The models developed incorporate performance metrics …