Saudi Cultural Missions Theses & Dissertations
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Item Restricted SERVICE NETWORK OPTIMIZATION TO GUIDE DECISIONS ON INFRASTRUCTURE INVESTMENT(George Mason University, 2023-12-13) Alyahya, Bedor; Brodsky, AlexanderInterrelated infrastructures, such as manufacturing, supply chain, renewable energy and smart grid, are critical for achieving long-term organizational and societal goals and enabling future growth. Deciding on infrastructure portfolio investment is a complex problem, given the uncertainty in future supply and demand, the rapid emergence of new technologies, and non-trivial operational interactions among the infrastructure components. Today, models and systems supporting stakeholders in infrastructure investment decisions either (1) express the investment model in high-level financial terms, which fails to accurately express the underlying operational system behavior over the investment time horizon, or (2) are hard- wired to a siloed domain-specific investment problem, which does not take into account interactions with interrelated infrastructures across the silos and inhibits the widespread adoption and re-usability of these models. Thus, both accurate and flexible investment decision models and systems are needed to recommend investment alternatives and guide stakeholders in making Pareto-optimal trade-o↵s between competing performance indicators such as total cost of ownership, carbon emissions and quality of service. This dissertation is driven by the need to overcome the aforementioned gap of investment decisions made in silos, as opposed to accounting for the synergistic value of strongly interdependent infrastructures. More specifically, the key contributions of this dissertation are as follows. First, designed and developed are formal predictive Analytic Models (AM) for both steady-state and tran- sient Service Networks. These models express metrics, capacity, and demand constraints over a specified time horizon as functions of fixed and controllable parameters, representing investment choices and precise operational settings throughout investment periods. Second, developed is a modular, extensible repository of investment component models, such as pumps, renewable energy sources, water and energy storage, Reverse Osmosis plants, transformers, energy contracts and electric and gas boilers, renewable energy certificates (RECs) and carbon o↵sets. Third, designed and developed are Decision Guidance Systems for both steady-state and transient models for investment in Service Networks. These systems optimize performance metrics and analyze Pareto-optimal trade-o↵s between di↵erent financial, environmental, and quality-of-service investment objectives leveraging a mixed-integer linear programming solver. As a specialization in the domain of Energy and Sustainability, developed is the Green Assessment and Decision Guidance Tool (GADGET.) Finally, a case study is conducted to provide recommendations to George Mason Uni- versity’s stakeholders on the most cost-e↵ective approach to achieve its carbon neutrality goals by 2040. GADGET provides recommendations for Pareto-optimal operational settings and investment choices related to the integration of renewable energy sources and related infrastructures with existing systems.4 0Item Restricted ASSOCIATION BETWEEN PARENTS’ PERCEPTIONS ABOUT HUMAN PAPILLOMAVIRUS (HPV) AND CORONAVIRUS DISEASE-19 (COVID-19) VACCINES AND THEIR DECISION TO VACCINATE THEIR CHILD AGAINST HPV(2023) Almatruk, Ziyad; Axon, David R; Warholak, TerriBACKGROUND: The WHO classified vaccine hesitancy as one of the top ten threats to global health. During the COVID-19 pandemic, many people had doubt about vaccines. The HPV can lead to several types of cancer. The COVID-19 impact on US HPV vaccination reluctance is unknown. Thus, the aim of the study is to investigate parents' perceptions of Coronavirus Disease-19 (COVID-19), the Human Papillomavirus (HPV) vaccine, and HPV vaccination decisions. METHODS: A cross-sectional observational survey was administered using Qualtrics to United States parents with at least one child aged 9–18. The survey consisted of five sections: screening, parent’s perception of general Vaccination, COVID-19, HPV, and demographics. Rasch analysis was used to evaluate the instrument reliability and validity, which included principal component analysis (PCA), scale functionality, person measure, item reliability, and person reliability. A logistic regression model with variables selected using backward elimination (p<0.05) was used to evaluate the associations between parents’ perception of COVID-19 and HPV vaccine decisions. RESULTS: The study included 508 parents. The instrument contained four domains: General Vaccination, COVID-19, HPV, and Parents’ COVID-19 Experience. Except for General Vaccination, PCA showed unidimensionality. Response options satisfied scale functionality analysis. Average person measure was 0.7±8.0 logits. Person reliability was 0.7-0.9, whereas item reliability was 0.9-1.0. Item fit ranged from 0.7-2.1. A few of the difficult items to endorse with were I trust social media and/or TV to tell me the truth about vaccines, I would have my 11 children vaccinated for COVID-19 if their school required it, vaccinating my child against HPV helps to protect others from getting HPV, and I believe the COVID-19 vaccine was approved in a reasonable amount of time. A few of the easy items to endorse were physicians’ address vaccine concerns, there are safe COVID-19 vaccines for children, and I believe in vaccines. The multivariate logistic regression model with backward elimination showed that HPV Domain (adjusted odds ratio [AOR] = 1.89, 95% CI = 1.61 – 2.21), Parents COVID-19 Experience Domain (AOR = 1.32, 95% CI = 1.18 – 1.47), and men compared to women (AOR = 2.48, 95% CI = 1.37 – 4.47) were significantly associated with parents’ planning not to vaccinate their children with HPV. CONCLUSIONS: Our research offers insight into variables associated with parents’ decisions about children’s COVID-19 and HPV vaccines. More research is needed to improve the HPV vaccine uptake.7 0