The integration of AI, specifically machine learning, into physical security architecture shows promise in helping organizations better identify threats, improve response times and aid security ...

Advanced sensor technologies and data analytics can proactively identify grid hazards, enhancing safety and operational ...

Choosing an MSSP shapes how well your financial business stands up to risk, change, and scrutiny. A thoughtful set of questions keeps the conversation focused on what matters most. Security. Trust.

Challenges with data quality and data governance have plagued healthcare analytics efforts for decades – and the stakes are only getting higher in the age of AI. Inaccurate or inconsistent data ...

Few engineers blend field practice, regulatory insight, and data science as tightly as Semiu Temidayo Fasasi. He currently serves as an Oil and Gas Permit Engineer at the Colorado Department of Public ...

ABSTRACT: Mathematical optimization is a fundamental aspect of machine learning (ML). An ML task can be conceptualized as optimizing a specific objective using the training dataset to discern patterns ...

Development and Validation of an Ipsilateral Breast Tumor Recurrence Risk Estimation Tool Incorporating Real-World Data and Evidence From Meta-Analyses: A Retrospective Multicenter Cohort Study Data ...

Biogas doesn’t just offer a backup plan for tech companies seeking more power; it provides a blueprint for sustainability. By transforming landfill, agricultural, and wastewater emissions into usable ...

Abstract: Network Intrusion Detection Systems (NIDS) are widely used to secure modern networks, but deploying accurate and scalable Machine Learning (ML)-based detection in high-speed environments ...