Leaf functional traits—chlorophyll (CHL), carotenoid (CAR), equivalent water thickness (EWT), nitrogen (N), and leaf mass per ...

A systematic review newly published in the Journal of Pipeline Science and Engineering maps machine learning (ML) advances for pipelines across the full lifecycle: reliability-based design, structural ...

Explore predictive modeling for compound prioritization, including in silico screening, toxicology models, and lead selection ...

Abstract: Deep-learning-based health prognostics is receiving ever-increasing attention. Most existing methods leverage advanced neural networks for prognostics performance improvement, providing ...

Abstract: Grant-Free Non-Orthogonal Multiple Access (GF-NOMA) is considered as a promising technology to support the massive connectivity of Machine-Type Communications (MTC). The design of efficient ...

Somewhere between 2% and 19% of the genetic ancestry carried by present-day West African populations traces back to an ...

Learning from potential disinformation introduces specific cognitive biases, causing individuals to systematically deviate from an idealized Bayesian updating strategy.

Medicine is rapidly evolving from statistical, evidence-based approaches to predictive, genotype-directed care, driven by ...

The Decision & Action Layer translates fused predictions into concrete actions. The Decision Engine performs inference, ...

Climate and ocean models use a series of equations to represent complex natural processes. However, the equations used in ...

Three funds filed to let software run the portfolio. The sales pages promise a lot. The risk pages quietly take most of it back.

Machine learning is the ability of a machine to improve its performance based on previous results. Machine learning methods enable computers to learn without being explicitly programmed and have ...