Machine learning to predict how fast biodegradable plastics break down in nature

Testing how quickly a biodegradable plastic actually breaks down in the environment can take months, sometimes years, of lab ...
TMCnet

MicroCloud Hologram Inc. Develops Approximate Quantum State Preparation and Entanglement-Dependent Complexity Algorithm Technology

MicroCloud Hologram Inc. (NASDAQ: HOLO), (“HOLO” or the “Company”), a technology service provider, has announced a groundbreaking achievement of great theoretical and engineering significance: its ...
Frontiers

Fairer non-negative matrix factorization

There has been a recent critical need to study fairness and bias in machine learning (ML) algorithms. Since there is clearly no one-size-fits-all solution to fairness, ML methods should be developed ...
IEEE

Conic Hull Fitting-Based Dictionary Matrix Learning for Nonnegative Matrix Factorization

Abstract: Nonnegative matrix factorization (NMF) is a powerful tool for signal processing and machine learning. Geometrically, it can be interpreted as the problem of finding a conic hull, which ...
fandomwire

The Matrix Symbolism: What Every Character Stands for in the Franchise

The name Neo is an anagram for the One, directly hinting at his destiny as the messiah who will save humanity. At the climax of The Matrix (1999), Neo is killed by Agent Smith and then resurrected, ...
Fox News

USPS worker found dead inside mailing machine in Michigan: 'Deeply saddened by the loss'

A U.S. Postal Service employee died after he became stuck inside a mail handling machine at a distribution center in Allen Park, Michigan, according to officials. Nicholas John Acker, 36, was stuck in ...
GitHub

Spectral Machine Learning for Market Microstructure: Fourier-Laplace Signal Decomposition for Alpha Discovery

Financial markets are noisy, chaotic systems—but beneath that chaos lie hidden frequency structures: cycles, mean-reversion waves, and volatility bursts that traditional time-domain models often miss.
IEEE

Non-Negative Matrix Factorization and Latent Semantic Analysis for Hybrid Feature Selection: A Proposed Machine Learning System for the Detection of Malicious Executable Files

Abstract: During a typical cyber-attack lifecycle, several key phases are involved, including footprinting and reconnaissance, scanning, exploitation, and covering tracks. The successful delivery of a ...