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The Ghostly Cyborg Author And The Living Reader Wonder, Supervision, And Scholarly Formation In The Age Of Ai, Connie Morrison, John L. Hoben

Journal of Academic Research and Innovation

No abstract provided.

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Supervising In The Age Of Ai Cognitive Authenticity, And Reframing Integrity Through Neurodiversity-Responsive Perspective, Precious Nwanze

Journal of Academic Research and Innovation

No abstract provided.

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From Gatekeeping To Cognitive Stewardship Rethinking Postgraduate Supervision In The Age Of Artificial Intelligence, Jon-Hans H. Coetzer Un, Erman Akilli Dr

Journal of Academic Research and Innovation

No abstract provided.

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Introducing Artificial Intelligence To The Metaverse, John O'Connor

Journal of Academic Research and Innovation

No abstract provided.

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Artificial Intelligence - A Threat To Natural Intelligence? Fears, Concerns And Uncertainties Facing Educators In The 21st Century, Ivaylo Peev, Murat Gülmez, Anna Zherdeva, Lia Pop, Lucia Morales

Journal of Academic Research and Innovation

No abstract provided.

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Mathematical Modeling And Simulation Of Wheel Hub Stresses Using Finite Element Analysis In Light Military Trainer Aircraft, Alysson Sousa Rabelo, José Aécio Gomes De Sousa, Feliciano José Ricardo Cangue, Luiz Leroy Thomé Vaughan

Journal of Aviation Technology and Engineering

The landing gear of modern aircraft accounts for approximately 20% of the structural weight and 5% of the total weight. Among its components, the wheel hub endures particularly high loads during landing, often leading to cracks and porosity associated with casting-induced micro-voids in magnesium and aluminum alloys. Over time, cyclic stresses enlarge these voids, converting them into critical stress concentrators. Differences in alloy properties, such as yield strength, fracture toughness, and corrosion resistance, further influence how cracks propagate, underscoring the importance of rigorous manufacturing methods and regular nondestructive inspections. To investigate these vulnerabilities, stress analyses were performed on a military …

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Developing Machine Learning Models For Sorption Of Pharmaceuticals To Soils And Sediments, Eyad Mohammed Al Salem

Thesis/ Dissertation Defenses

The growing environmental presence of pharmaceutically active compounds (PACs) creates a critical need for rapid, cost-effective methods to predict their movement through soils and sediments. Traditional laboratory batch experiments are time-consuming, and previous predictive models often relied on limited data or ignored complex chemical behavior. The primary objective of this thesis is to develop robust machine learning models for predicting the sorption distribution coefficient of PACs. The study aims to determine whether separating data by ionic state improves predictive accuracy and to identify the key physical and chemical factors governing the sorption of PACs onto soils and sediments. A large …

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