In one instance, to further enhance output voltage swing and linearity, the authors propose a novel “breakdown-voltage (BV) ...
Researchers have developed a new machine-learning-assisted approach to optimize micro-electro-discharge machining (µ-EDM) of ...
AI agents help businesses stop guessing — linking predictions to actions so teams can move from “what might happen” to ...
This paper presents a novel framework for optimizing Carbon Release (CR) through an AI-driven approach to Fossil Fuel Intake (FFI) management. We propose a new training methodology for AI models to ...
Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with pseudo-inverse training implemented using JavaScript. Compared to other training techniques, such as ...
Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...
A proof of concept shows how multi-agent orchestration in Visual Studio Code 1.109 can turn a fragile, one-pass AI workflow into a more reliable, auditable process by breaking long tasks into smaller, ...
Background Early graft failure within 90 postoperative days is the leading cause of mortality after heart transplantation. Existing risk scores, based on linear regression, often struggle to capture ...
Background Previous studies have suggested an adverse role of epicardial adipose tissue (EAT) in aortic stenosis (AS), ...
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