New platform unifies conversion tracking from CRMs, call tracking, and manual sources to automatically qualify leads ...

Database optimization has long relied on traditional methods that struggle with the complexities of modern data environments. These methods often fail to efficiently handle large-scale data, complex ...

Machine learning (ML) and deep learning (DL) as two well-known methods of artificial intelligence (AI) have emerged as powerful tools in extracting insights and patterns from vast amounts of data. In ...

FPMCO decomposes multi-constraint RL into KL-projection sub-problems, achieving higher reward with lower computing than second-order rivals on the new SCIG robotics benchmark.

Nanotechnology and machine learning are transforming energy systems by enhancing engine efficiency and sustainability. The integration of advanced nanomaterials, such as gold nanoparticles (AuNPs), ...

Abstract: The evolution of intelligent warehousing represents a paradigm shift in supply chain logistics, driven by the synergistic integration of machine learning (ML) algorithms, Internet of Things ...

Cell culture is a foundational technology widely used across fields such as pharmaceutical production, regenerative medicine, food science, and materials engineering. A critical component of ...

College of Mechanical and Electronic Engineering, Shanghai Jianqiao University, Shanghai, China Introduction: To enhance energy management in electric vehicles (EVs), this study proposes an ...

Researchers have found a way to make the chip design and manufacturing process much easier — by tapping into a hybrid blend of artificial intelligence and quantum computing. When you purchase through ...

Patent applications on artificial intelligence and machine learning have soared in recent years, yet legal guidance on the patentability of AI and machine learning algorithms remains scarce. The US ...