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Full-Text Articles in Physical Sciences and Mathematics
Predictive Modeling Of Cave Entrance Locations: Relationships Between Surface And Subsurface Morphology, William Blitch, Adia R. Sovie, Benjamin W. Tobin
Predictive Modeling Of Cave Entrance Locations: Relationships Between Surface And Subsurface Morphology, William Blitch, Adia R. Sovie, Benjamin W. Tobin
International Journal of Speleology
Cave entrances directly connect the surface and subsurface geomorphology in karst landscapes. Understanding the spatial distribution of these features can help identify areas on the landscape that are critical to flow in the karst groundwater system. Sinkholes and springs are major locations of inflow and outflow from the groundwater system, respectively, however not all sinkholes and springs are equally connected to the main conduit system. Predicting where on the landscape zones of high connectivity exist is a challenge because cave entrances are difficult to detect and imperfectly documented. Wildlife research has a similar issue of understanding the complexities of where …
Probabilistic Machine Learning Using Bayesian Inference, Mayank Pandey
Probabilistic Machine Learning Using Bayesian Inference, Mayank Pandey
Undergraduate Journal of Mathematical Modeling: One + Two
Machine Learning is a branch of AI (Artificial Intelligence) which expands on the idea of a computational system extending its knowledge about set methodical behaviors from the data that is fed to it to essentially develop analytical skills that can help in identifying patterns and making decisions with little to no participation of a real human being. Computer algorithms help in gaining experience to improve the facility over time for use by both consumers and corporations. In today’s technologically advanced world, Machine Learning has given us self-driving cars, speech recognition software, and AI agents like Siri and Google assistant. This …
Diagnosing Breast Cancer With A Neural Network, John Cullen
Diagnosing Breast Cancer With A Neural Network, John Cullen
Undergraduate Journal of Mathematical Modeling: One + Two
Fine needle aspiration (FNA) is a minimally invasive biopsy technique that can be used to successfully diagnose types of cancer, including breast cancer. Immediately, it is difficult for a human to spot any trends in the cell level data gathered during a fine needle aspiration procedure. One way to predict the type of tumor a patient has, is to use a computer to develop a mathematical model based on known data. This project utilizes the Diagnostic Wisconsin Breast Cancer Database (DWBCDB) to create an accurate mathematical model that predicts the type of a patient’s tumor (Malignant or Benign). A neural …
Evaluating Machine Learning Classifiers For Defensive Cyber Operations, Michael D. Rich, Robert F. Mills, Thomas E. Dube, Steven K. Rogers
Evaluating Machine Learning Classifiers For Defensive Cyber Operations, Michael D. Rich, Robert F. Mills, Thomas E. Dube, Steven K. Rogers
Military Cyber Affairs
Today’s defensive cyber sensors are dominated by signature-based analytical methods that require continuous maintenance and lack the ability to detect unknown threats. Anomaly detection offers the ability to detect unknown threats, but despite over 15 years of active research, the operationalization of anomaly detection and machine learning for Defensive Cyber Operations (DCO) is lagging. This article provides an introduction to machine learning concepts with a focus on the unique challenges to using machine learning for DCO. Traditional machine learning evaluation methods are challenged in favor of a value-focused evaluation method that incorporates evaluator-specific weights for classifier and sensitivity threshold selection …