Physical Sciences and Mathematics Commons^™

Gans And Synthetic Financial Data: Calculating Var*, David E. Allen, Leonard Mushunje, Shelton Peiris

Research outputs 2022 to 2026

Generative Adversarial Neural nets (GANs) are a new branch of machine learning techniques. A GAN learns to generate new data from the training data set. We examine the characteristics of the fake financial data using GANs trained on samples of daily S&P 500 and FTSE 100 index values. GANs feature two competing neural networks in a game theoretic context. The Generator net generates pseudo data that is presented to the discriminator net which then attempts to distinguish between the real and the fake data. This facilitates unsupervised learning on the dataset. The generative network generates data sets, while the discriminative …

Unifying Context With Labeled Property Graph: A Pipeline-Based System For Comprehensive Text Representation In Nlp, Ali Hur, Naeem Janjua, Mohiuddin Ahmed

Research outputs 2022 to 2026

Extracting valuable insights from vast amounts of unstructured digital text presents significant challenges across diverse domains. This research addresses this challenge by proposing a novel pipeline-based system that generates domain-agnostic and task-agnostic text representations. The proposed approach leverages labeled property graphs (LPG) to encode contextual information, facilitating the integration of diverse linguistic elements into a unified representation. The proposed system enables efficient graph-based querying and manipulation by addressing the crucial aspect of comprehensive context modeling and fine-grained semantics. The effectiveness of the proposed system is demonstrated through the implementation of NLP components that operate on LPG-based representations. Additionally, the proposed …

Attitudes And Perceptions Towards Privacy And Surveillance In Australia, Aleatha J. Shanley

Theses: Doctorates and Masters

Understanding attitudes towards privacy and surveillance technologies used to enhance security objectives is a complex, but crucial aspect for policy makers to consider. Historically, terrorism-related incidents justified the uptake of surveillance practices. More recently however, biosecurity concerns have motivated nation-states to adopt more intrusive surveillance measures. There is a growing body of literature that supports the public’s desire to maintain privacy despite fears of biological or physical threats.

This research set out to explore attitudes towards privacy and surveillance in an Australian context. Throughout the course of this endeavour, the COVID-19 pandemic emerged bringing with it a variety of track …

Modeling Earthquake Catalog (1985-2022) In Northern Egypt Using Space-Time Epidemic-Type Aftershock Sequences (Etas), Mariam Ramadan, Amir Ismail, Amin E. Khalil, Hesham Abdelhafiez, Nouran S. Salama

Trends in advanced sciences and technology

Earthquakes have the largest damaging effects among natural disasters on a global scale. Efforts for reducing their effects have taken place for a long time. The prediction of earthquakes was the main target, however the studies conducted were not successful. As a replacement, seismic hazard assessments were adopted to predict the levels of ground motion for the possible future large earthquakes. This approach is probabilistic in nature that rely on the quality of earthquake catalog. The probabilistic model adopted is built on the assumption that the events in the earthquake catalog are random Poisson distribution, assuming that events are independent …