This proposal outlines a machine learning-based approach aimed at improving productivity in haulage operations within open-pit mining. Since hauling accounts for up to 60% of total operational costs, ...
Using limited human motion data, researchers trained a humanoid robot to track fast balls and rally with humans in real time.
Detecting behavioural signatures of depression from everyday digital traces is a central challenge in computational psychiatry. Real-world datasets from smartphones and wearables often suffer from ...
Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in ...
Abstract: Accurate forecasts of short-term electricity consumption are essential for efficient energy management in buildings and residential households. This research introduces a new approach for ...
The true nature of our universe as been an open debate for millennia, and recently, scientists and philosophers have pondered whether it might be a hyper-realistic simulation perpetuated by some super ...
The consortium running the European Space Agency's (ESA) Euclid mission has published the most extensive simulation of the cosmos to date. The modeling was based on algorithms developed by UZH ...
It’s no secret that much of social media has become profoundly dysfunctional. Rather than bringing us together into one utopian public square and fostering a healthy exchange of ideas, these platforms ...
Abstract: Aiming at the influence of various external factors on the range of projectile launching, and the problems of time error accumulation and precision decline ...
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