A new study introduces a breakthrough in sustainable transport modeling through the use of explainable machine learning. The research, titled “Explainable Machine Learning Prediction of Vehicle CO₂ ...

Researchers have developed a blockchain-powered system that could redefine how solar energy is traded in decentralized markets. Their work integrates machine learning, blockchain smart contracts, and ...

As cost pressures, data sovereignty rules, and the rise of AI reshape IT priorities, we look at what organisations across Asia-Pacific can do to adopt the hybrid infrastructure model that places each ...

Researchers from the Xinjiang Astronomical Observatory of the Chinese Academy of Sciences have developed a hybrid deep learning model that can accurately predict atmospheric delay, a key source of ...

For years, we believed the Himalayas were a climatic sanctuary—untouched, pristine, and resilient to the turbulence of modernization. But what happens when mountain cities begin to mimic the dynamics ...

At the edge Models are built on the cloud and applied at the edge. Moving data from inspection/metrology systems to the cloud to make a decision to execute back at the system is simply impractical.

A forecasting-driven framework integrates ARIMA, LSTM, and ensemble learning to optimize cloud resource scheduling. By predicting CPU, memory, and network demands in real time, it enhances utilization ...

In recent years, new strategies such as automatic control, data mining, transfer learning, hybrid model building and soft sensor construction have enhanced the adaptability of ML in designing and ...

To safeguard enterprise data in hybrid cloud environments, organizations need to apply basic data security techniques such as encryption, data-loss prevention (DLP), secure web gateways (SWGs), and ...