首页|Shahid Beheshti University Researcher Reveals New Findings on Machine Learning ( Machine learning assisted sorting of active microswimmers)
Shahid Beheshti University Researcher Reveals New Findings on Machine Learning ( Machine learning assisted sorting of active microswimmers)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – A new study on artificial intelligence is now available. According to news reporting originating from Tehran, Iran, by NewsRx correspondents, research stated, “Active matter systems, being in a non- equilibrium state, exhibit complex behaviors, such as self-organization, giving rise to emergent phenomena.” Financial supporters for this research include Iran National Science Foundation. The news correspondents obtained a quote from the research from Shahid Beheshti University: “There are many examples of active particles with biological origins , including bacteria and spermatozoa, or with artificial origins, such as self-p ropelled swimmers and Janus particles. The ability to manipulate active particle s is vital for their effective application, e.g., separating motile spermatozoa from nonmotile and dead ones, to increase fertilization chance. In this study, w e proposed a mechanism-an apparatus-to sort and demix active particles based on their motility values (Peclet number). Initially, using Brownian simulations, we demonstrated the feasibility of sorting self-propelled particles. Following thi s, we employed machine learning methods, supplemented with data from comprehensi ve simulations that we conducted for this study, to model the complex behavior o f active particles. This enabled us to sort them based on their Peclet number.”
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