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Articles 1 - 4 of 4
Full-Text Articles in Computer Sciences
Machine Learning To Predict Warhead Fragmentation In-Flight Behavior From Static Data, Katharine Larsen
Machine Learning To Predict Warhead Fragmentation In-Flight Behavior From Static Data, Katharine Larsen
Doctoral Dissertations and Master's Theses
Accurate characterization of fragment fly-out properties from high-speed warhead detonations is essential for estimation of collateral damage and lethality for a given weapon. Real warhead dynamic detonation tests are rare, costly, and often unrealizable with current technology, leaving fragmentation experiments limited to static arena tests and numerical simulations. Stereoscopic imaging techniques can now provide static arena tests with time-dependent tracks of individual fragments, each with characteristics such as fragment IDs and their respective position vector. Simulation methods can account for the dynamic case but can exclude relevant dynamics experienced in real-life warhead detonations. This research leverages machine learning methodologies to …
A Meshless Approach To Computational Pharmacokinetics, Anthony Matthew Khoury
A Meshless Approach To Computational Pharmacokinetics, Anthony Matthew Khoury
Doctoral Dissertations and Master's Theses
The meshless method is an incredibly powerful technique for solving a variety of problems with unparalleled accuracy and efficiency. The pharmacokinetic problem of transdermal drug delivery (TDDD) is one such topic and is of significant complexity. The locally collocated meshless method (LCMM) is developed in solution to this topic. First, the meshless method is formulated to model this transport phenomenon and is then validated against an analytical solution of a pharmacokinetic problem set, to demonstrate this accuracy and efficiency. The analytical solution provides a locus by which convergence behavior are evaluated, demonstrating the super convergence of the locally collocated meshless …
Acoustic/Gravity Wave Phenomena In Wide-Field Imaging: From Data Analysis To A Modeling Framework For Observability In The Mlt Region And Beyond, Jaime Aguilar Guerrero
Acoustic/Gravity Wave Phenomena In Wide-Field Imaging: From Data Analysis To A Modeling Framework For Observability In The Mlt Region And Beyond, Jaime Aguilar Guerrero
Doctoral Dissertations and Master's Theses
Acoustic waves, gravity waves, and larger-scale tidal and planetary waves are significant drivers of the atmosphere’s dynamics and of the local and global circulation that have direct and indirect impacts on our weather and climate. Their measurements and characterization are fundamental challenges in Aeronomy that require a wide range of instrumentation with distinct operational principles. Most measurements share the common features of integrating optical emissions or effects on radio waves through deep layers of the atmosphere. The geometry of these integrations create line-of-sight effects that must be understood, described, and accounted for to properly present the measured data in traditional …
A Framework To Detect The Susceptibility Of Employees To Social Engineering Attacks, Hashim H. Alneami
A Framework To Detect The Susceptibility Of Employees To Social Engineering Attacks, Hashim H. Alneami
Doctoral Dissertations and Master's Theses
Social engineering attacks (SE-attacks) in enterprises are hastily growing and are becoming increasingly sophisticated. Generally, SE-attacks involve the psychological manipulation of employees into revealing confidential and valuable company data to cybercriminals. The ramifications could bring devastating financial and irreparable reputation loss to the companies. Because SE-attacks involve a human element, preventing these attacks can be tricky and challenging and has become a topic of interest for many researchers and security experts. While methods exist for detecting SE-attacks, our literature review of existing methods identified many crucial factors such as the national cultural, organizational, and personality traits of employees that enable …