Saudi Cultural Missions Theses & Dissertations
Permanent URI for this communityhttps://drepo.sdl.edu.sa/handle/20.500.14154/10
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Item Restricted Sentiment Analysis of New Zealand Adults’ and Children’s Tweets Regarding the COVID-19 Vaccination Programme(Saudi Digital Library, 2023-12-02) Aldahmash, Lamyaa; Mpofu, CharlesThe SARS-CoV-2 virus, which caused the global COVID-19 pandemic, necessitated a significant worldwide response, with vaccination being a primary strategy. This dissertation explores the public sentiment towards New Zealand’s national vaccination campaign, through a machine learning analysis of large-scale text data gathered from the social media platform Twitter. Focusing on responses from both adults and children, this research aimed to assess the efficacy of health communication strategies and the wider acceptance of the vaccine within the community. The findings underscore a considerable disparity between policy decisions and public sentiment on Twitter, with a significant portion of the New Zealand population expressing negative views on vaccinations. Overall, this research reveals the need for enhanced public engagement, better communication, and more effective use of social media data by policymakers and healthcare professionals in order to address public concerns, mitigate fears, dispel misinformation, and ultimately increase vaccine uptake.5 0Item Restricted Pattern Recognition & Predictive Analysis of Cardiovascular Diseases: A Machine Learning Approach(Saudi Digital Library, 2023-11-23) Alseraihi, Faisal Fahad; Naich, AmmarCardiovascular disease (CVD) is a predominant global health concern, with its impact becoming increasingly pronounced in low- and middle- income countries due to challenges like limited healthcare access, inadequate public awareness, and lifestyle-related risks. Addressing CVD's multifactorial origins, which span genetic, environmental, and behavioral domains, requires advanced diagnostic techniques. This research leverages the UCI Heart Disease dataset to develop a deep learning predictive model for CVD, incorporating 14 vital heart health parameters. The models performance is critically assessed against conventional machine learning approaches, shedding light on its efficiency and areas of refinement. Utilizing sophisticated Neural Network structures, this study strives to enhance predictive health analytics, aiming for timely CVD identification and intervention. As the integration of machine learning into healthcare deepens, it's crucial to ensure that these tools are robust, thoroughly evaluated, and augment clinical insights to reduce misdiagnosis risks.77 0Item Restricted Life Cycle Assessment of Concrete Parking Structures to Enhance Durability and Structural Performance(OhioLINK Electronic Theses and Dissertations Center, 2024-04-21) Alismaeel, Abdulmoez; Sezen, HalilThe main objective of this study is to provide designers, manufacturers, and owners of new parking facilities with best practices and design choices considering lifecycle costs and extreme loading scenarios for several selected parking structures in Ohio. To achieve this overall goal, an interactive tool was developed using Python software to perform lifecycle cost analysis while considering various parameters like joint sealant, flange-to-flange connectors, and general repairs due to corrosion after environmental exposure. Also, snow load effects were investigated when a plow pushes all the uniform snow accumulated on the top of the roof slabs of thirteen parking garage structures to the corners or edges. Furthermore, the additional live load that could come from large numbers of driverless cars on cast-in-place and precast concrete parking structures was investigated. In this dissertation, a lifecycle assessment methodology is proposed for cast-in-place and precast concrete parking structures to identify and address durability and structural performance issues with the objective of answering these specific questions: (1) how to perform overall lifecycle assessment of parking structures, (2) how to perform performance assessment of double-tee beam flange-to-flange connections and joint leakage, and (3) how to investigate a parking structure’s ability to carry unexpected loads. The author had access to design, repair, and maintenance data from several existing concrete parking structures. Historical maintenance and repair records were used to assess the impact of design changes to improve the durability and structural performance. An interactive tool is developed in Python software to perform lifecycle cost analysis considering various parameters including joint sealants, flange-to-flange connector, periodical damage repairs, and general maintenance due to environmental exposure. The new program also evaluates the fatigue stress conditions considering the design life of connectors. The ability of existing parking structures to last into the future relies not only on proper maintenance but also on an ability to resist future unexpected loads that may not have been designed for. For example, this can be snow load produced when a plow pushes the uniform snow on the top deck of a garage to one corner or edge producing a load concentration. Another load with potential impact is the additional live loads that could come from driverless cars in the future. A procedure is proposed using three-dimensional influence surfaces to investigate the effects of these unusual loads on the structural performance of parking structures.23 0