Researchers from BITS-Pilani, Hyderabad, have developed a safer, fluoride-free synthesis method for metal-organic frameworks that significantly boosts their capacity to capture greenhouse gases and store clean fuels at room temperature.
A new study finds that machine learning models can identify behavioural cues in zebrafish to correctly predict when the fish is anxious.
Imagine if we could predict the properties of materials without having to test them in a lab. This would save a lot of time and money, and it could help scientists discover new materials with amazing properties, like super-strong metals or super-efficient semiconductors. This is exactly what researchers at the Indian Institute of Science (IISc) and University College London are working on. They are using machine learning tools to predict material properties, even when there is limited data available.
A new research has elevated self-learning to a whole new level by developing an intelligent “judge” who can predict the expertise of a Bharatnatyam dancer. Prof. Dinesh Babu Jayagopi and his team at the International Institute of Information Technology, Bangalore, have designed Machine Learning based software that predicts a dancer’s expertise by observing his/her poses and expressions during a dance performance. Such a software can also be used to automatically tag videos and analyse its contents in a video database like YouTube, thus simplifying video search.