A signal-processing–based framework converts DNA sequences into numerical signals to identify protein-coding regions. By integrating spectral analysis and SVM classification, the approach improves ...

Machine learning holds great promise for classifying and identifying fossils, and has recently been marshaled to identify trackmakers of dinosaur ...

A deep learning framework combines convolutional and bidirectional recurrent networks to improve protein function prediction from genomic sequences. By automating feature extraction and capturing long ...

This framework was developed as part of consciousness AI research to validate pattern detection methodologies on certified random number generators before applying them to neural dynamics and quantum ...

The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Department of Biology, Massachusetts Institute of Technology, United States; ...

Nuclear power has the potential to be a viable economic option for shipowners by 2050 if the industry sticks to its current green targets, according to a new study. Major economic and regulatory ...

One former Air Force leader anticipates that there are a plethora of additional ways that artificial intelligence (AI) and large language models (LLMs) can assist crews in accomplishing their tasks ...

Introduction: Accurately predicting the remaining mechanical equipment is of great significance for ensuring the safe operation of the equipment and improving economic efficiency. Methods: To ...

Abstract: Deterministic Turing machines and their associated complexity measures, by construction, cannot capture the complexity of the output of stochastic processes - like those in the real world.