Computer Sciences

A framework to evaluate techniques for simulating physical systems

The simulation of physical systems using computing tools can have numerous valuable applications, both in research and real-world settings. Most existing tools for simulating physical systems are based on physics theory and ...

Computer Sciences

New modelling methodology for large-scale dynamic networks

Engineering systems, such as power grids and transportation systems, are becoming increasingly complex and encompass numerous sub-systems that are spatially interconnected. Modeling of these 'dynamic networks' is an important ...

Computer Sciences

How will machine learning change science?

Machine learning has burst onto the scene in the past two decades and will be a defining technology of the future. It is transforming large sectors of society, including healthcare, education, transport, and food and industrial ...

Computer Sciences

Machine learning tool sorts the nuances of quantum data

An interdisciplinary team of Cornell and Harvard University researchers developed a machine learning tool to parse quantum matter and make crucial distinctions in the data, an approach that will help scientists unravel the ...

Computer Sciences

ProtoTree: Addressing the black-box nature of deep learning models

One of the biggest obstacles in the adoption of Artificial Intelligence is that it cannot explain what a prediction is based on. These machine-learning systems are so-called black boxes when the reasoning for a decision is ...

Electronics & Semiconductors

Exploring extremes: When is it too hot to handle?

Exploring extreme environments can put significant operational challenges on the engineering systems we depend upon to safely explore and at times operate within.

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