Abstract: One of the prominent challenges encountered in real-world data is an imbalance, characterized by unequal distribution of observations across different target classes, which complicates ...

The zero-day exploitations of Ivanti's MDM platform meant unprecedented pwning of 1000s of orgs by a Chinese APT — and ...

As enterprises continue navigating the complexities of digital transformation, Rahul Jain's work reflects how thoughtful, ...

Discover the power of predictive modeling to forecast future outcomes using regression, neural networks, and more for improved business strategies and risk management.

Machine learning is transforming many scientific fields, including computational materials science. For about two decades, scientists have been using it to make accurate yet inexpensive calculations ...

Redgate Software, the end-to-end Database DevOps solution provider, is launching Redgate Data Modeler, a new SaaS-based data modeling tool that enables teams to collaboratively design, document, and ...

A rotating cylinder with its side cut away to expose the core, showing patches of purple, blue, green, yellow, and orange that are dense in the middle and more diffuse toward the edges. This rotating ...

Years ago, before the rise of the gig economy, people developed their careers over time, often more slowly than desired. Folks who became DBAs, Data Modelers, or Data Architects had a rule-following ...

As semiconductor technologies advance, device structures are becoming increasingly complex. New materials and architectures introduce intricate physical effects requiring accurate modeling to ensure ...

GoLogica provides the best Data Modeling Online Training, which helps you gain the knowledge on designing, building and maintaining effective business data models that are central to business ...

The Ohio Power Siting Board approved one of two proposed natural gas power plants in New Albany. The approved plant, Socrates South, will be built by Will-Power OH, a subsidiary of Williams Companies.

Abstract: Deep probabilistic learning networks have been applied in industrial soft sensors. However, they face significant challenges in latent variable inference, deep learning backend ...