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How Negative Sampling Provides Class Balance To Rare Event Case Data Using A Vehicular Accident Prediction Project As A Use Case Scenario, Jeremy Roland Dec 2020

How Negative Sampling Provides Class Balance To Rare Event Case Data Using A Vehicular Accident Prediction Project As A Use Case Scenario, Jeremy Roland

Masters Theses and Doctoral Dissertations

Rare event case data occur at such an infrequent rate that even having high amounts of it can leave researchers starving for more information. There has always existed a tug and pull relationship among rare event case data, where a higher count of entries often leads to a lack of explanatory variables, and vice versa. In the research spectrum of rare event case probability prediction, several methods of data sampling exist to remedy the main issue of rare event case data: a lack of data to collect and learn from. The most effective methods often involve altering the distribution of …


Clustering Algorithms To Further Enhance Predictable Situational Data In Vehicular Ad-Hoc Networks, Adam Dean Dec 2020

Clustering Algorithms To Further Enhance Predictable Situational Data In Vehicular Ad-Hoc Networks, Adam Dean

Masters Theses and Doctoral Dissertations

The modern world is constantly in a state of technological revolution. Everyday some new technological idea, invention, or threat emerges. With modern computer software and hardware advancements, we have the emergence of more internet-enabled devices - or, Internet of Things (IoT) devices. We can now create large networks with any device to gather real-time information about an environment. In conjunction, modern car companies across the board have a push from public demand for a fully-autonomous car. In order to accomplish autonomy safely and effectively, Vehicular Ad-Hoc Networks (VANETs) must be established for a local group of cars and their environment …


Behavioral Model Based Trust Management Design For Iot At Scale, Brennan Huber Aug 2020

Behavioral Model Based Trust Management Design For Iot At Scale, Brennan Huber

Masters Theses and Doctoral Dissertations

With the rise in the number of devices in the Internet of Things (IoT), the number of malicious devices will also drastically increase. Smart cities' decisions are based on data being collected by IoT devices in real-time, of which a connected-vehicle system is included. Behaviors such as malicious data injection can significantly impact connected vehicles. To aid in combating this threat, monitoring smart city and connected vehicle's sensor data will allow for construction of a behavioral model. Implementing machine learning will aid in constructing a standard behavior such that any device that begins to malfunction or behave maliciously can be …


Applying Deep Learning For Cell Detection In Time-Lapse Microscopic Images, Jay Patel Aug 2020

Applying Deep Learning For Cell Detection In Time-Lapse Microscopic Images, Jay Patel

Honors Theses

The budding yeast Saccharomyces cerevisiae is an effective model for studying cellular aging. We can measure the lifespan of yeast cells in two ways: replicative and chronological lifespans. Chronological focuses on the time that a cell can survive. The replicative lifespan (RLS) is the number of cell divisions that a single mother cell can go through before ceases to be dividing. RLS is a measurement of individual cells and is more informative on the aging process than in chronological lifespan. Many genes that influence yeast RLS have been shown to be highly conserved and have a similar effect on aging …


Behavioral Model Anomaly Detection In Automatic Identification Systems (Ais), Jacob Coleman May 2020

Behavioral Model Anomaly Detection In Automatic Identification Systems (Ais), Jacob Coleman

Masters Theses and Doctoral Dissertations

Over 90% of all goods in the world, at some point in their life, are on a vessel at sea. Currently, the maritime industry relies on the Automatic Identification System (AIS) for collision avoidance and vessel tracking. AIS is an unencrypted, unauthenticated protocol that is vulnerable to various types of cyber attacks allowing malicious actors to alter the location of vessels. With the advent of the Ocean of Things (OoT), vessels are sharing more information than vessel location alone at sea. Increasingly, more information is becoming critical for safe and efficient operation at sea. This method is a novel approach …