General Analysis
General analysis encompasses a broad range of methodologies applied across diverse scientific domains to extract meaningful insights from data. Current research focuses on developing robust and efficient analytical techniques, including the application of machine learning models like convolutional neural networks, graph neural networks, and transformer architectures, as well as statistical methods for data modeling and hypothesis testing. These advancements are improving the accuracy and efficiency of analyses in fields ranging from medical image processing and materials science to social media analysis and autonomous systems, ultimately leading to more reliable scientific findings and improved decision-making in various applications.
Papers
Creation and Analysis of an International Corpus of Privacy Laws
Sonu Gupta, Ellen Poplavska, Nora O'Toole, Siddhant Arora, Thomas Norton, Norman Sadeh, Shomir Wilson
Analysis of Individual Conversational Volatility in Tandem Telecollaboration for Second Language Learning
Alan F. Smeaton, Aparajita Dey-Plissonneau, Hyowon Lee, Mingming Liu, Michael Scriney
Simple and complex spiking neurons: perspectives and analysis in a simple STDP scenario
Davide Liberato Manna, Alex Vicente Sola, Paul Kirkland, Trevor Bihl, Gaetano Di Caterina