Physical Sciences and Mathematics Commons^™

Exploring Information For Quantum Machine Learning Models, Michael Telahun

Electronic Theses and Dissertations

Quantum computing performs calculations by using physical phenomena and quantum mechanics principles to solve problems. This form of computation theoretically has been shown to provide speed ups to some problems of modern-day processing. With much anticipation the utilization of quantum phenomena in the field of Machine Learning has become apparent. The work here develops models from two software frameworks: TensorFlow Quantum (TFQ) and PennyLane for machine learning purposes. Both developed models utilize an information encoding technique amplitude encoding for preparation of states in a quantum learning model. This thesis explores both the capacity for amplitude encoding to provide enriched state …

Computational Behavioral Analytics: Estimating Psychological Traits In Foreign Languages., Kristopher Wayne Reese

Electronic Theses and Dissertations

The rise of technology proliferating into the workplace has increased the threat of loss of intellectual property, classified, and proprietary information for companies, governments, and academics. This can cause economic damage to the creators of new IP, companies, and whole economies. This technology proliferation has also assisted terror groups and lone wolf actors in pushing their message to a larger audience or finding similar tribal groups that share common, sometimes flawed, beliefs across various social media platforms. These types of challenges have created numerous studies in psycholinguistics, as well as commercial tools, that look to assist in identifying potential threats …

Chemostratigraphy Of Carbonate Gravity Flows Of The Wolfcamp Formation In Crockett County, Midland Basin, Texas, Alex Blizzard, Julie Bloxson

Electronic Theses and Dissertations

Sediment gravity flows into deep-water environments are important stratigraphic traps in lithologically diverse reservoirs generating multiple plays for hydrocarbon exploration. These highly heterogeneous deposits can be studied by utilizing chemostratigraphy and higher-order sequence stratigraphy; being an accurate method for reservoir characterization. Studying these gravity flows along a carbonate platform’s slope can further expand an understanding of the stratigraphy that is filling adjacent basins. The application of elemental analyses can support in identifying mineralogy that impact reservoir quality, especially when conventional testing cannot be applied.

This study utilizes five cores containing the Wolfcamp Formation from the southeastern slope of the Central …

Experiments On The Neural Network Approach To The Handwritten Digit Classification Problem, William Meissner

Electronic Theses and Dissertations

When the MNIST dataset was introduced in 1998, training a network was a multiple week problem in order to receive results far less accurate than an average CPU can produce within a couple of hours today. While this indicates that training a network on such a dataset is not the complicated problem it may have been twenty years ago, the MNIST dataset makes a good tool for study and testing with beginner and medium complexity neural networks. This paper follows along with the work presented in the online textbook “Neural Networks and Deep Learning” by Michael Nielson and an updated …