Abstract: In this article, we propose using new machine learning (ML)-based optimization methods as an alternative to traditional optimization methods, for complex antenna designs. This is an ...

Abstract: An automated, robust, noncontact sleep posture recognition technique is proposed in this letter, which uses optimizable (Bayesian hyperparameter tuning) machine learning (ML) classifiers ...

Supervised machine learning improves predictions of compressive strength in industrial waste-modified concrete, supporting ...

[O'Reilly] Natural-Language-Annotation-for-Machine-Learning.pdf [O'Reilly] Practical Natural Language Processing.pdf [O'Reilly] Prompt Engineering for LLMs.pdf [Springer] Deep Learning in Natural ...

Open-Source AI Tools while not widely publicized, are highly regarded within the developer community for their ability to simplify complex tasks ...

This review explains how soft materials, scalable manufacturing, energy-efficient hardware, and AI are converging to create ...

Specifically, machine learning algorithms can be trained on large datasets of patient information and mechanical ventilation settings. These algorithms can then predict patient responses to different ...

Physics is the search for and application of rules that can help us understand and predict the world around us. Central to physics are ideas such as energy, mass, particles and waves. Physics attempts ...

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

A research team has developed a machine learning–based quantitative structure–activity relationship (ML-QSAR) method to ...

Meta’s AI chief says new Muse Spark update will sharpen coding, agentic AI Alexandr Wang said the upcoming Muse Spark update will significantly improve coding and agentic capabilities, while analysts ...

Explore the latest news and expert commentary on Application Security, brought to you by the editors of Dark Reading ...