Using Machine Learning Data to Achieve Sustainability, Performance and Governance Goals

In an environment defined by labor shortages, rising uptime expectations and pressure to improve overall equipment effectiveness (OEE), simple data collection is no longer enough.
IEEE

Implementation of Hybrid Machine Learning on Photonic Crystal Fiber Based Biosensor

Abstract: In this article, a machine learning (ML) regression approach is proposed for detecting the core loss (CL) and effective refractive index (ERI) of the core mode of photonic crystal fiber (PCF ...
IEEE

An Exploratory Study of Security Vulnerabilities in Machine Learning Deployment Projects

Abstract: Machine learning (ML) deployment projects are used by practitioners to automatically deploy ML models. While ML deployment projects aid practitioners, security vulnerabilities in these ...
Food Processing

Wayne-Sanderson Details its Journey into AI, Machine Learning Implementation

In this episode, recorded during the IPPE show in Atlanta in January, Juan DeVillena, senior vice president of quality assurance and food safety at Wayne-Sanderson Farms, walks through Wayne-Sanderson ...
GitHub

MARIE - Multi-Agent auto-Regressive Imagination for Efficient learning

🎉 [2025-12] MARIE now supports SMAX (JAX-based StarCraft Multi-Agent Challenge) with 14 available maps! We provide CPU-only JAX integration to ensure compatibility with Ray distributed workers. See ...