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Quantum machine learning: Small-scale photonic quantum processor can already outperform classical counterparts
One of the current hot research topics is the combination of two of the most recent technological breakthroughs: machine ...
C&EN8d
Automatic Machine Learning Combined with High-Throughput Computational Screening of Hydrophobic Metal–Organic Frameworks for Capture of Methanol and Ethanol from the Air
Guangzhou Key Laboratory for New Energy and Green Catalysis, School of Chemistry and Chemical Engineering, Guangzhou University, Guangzhou 510006, China Joint Institute of Guangzhou University & ...
Frontiers17d
A comparative study for landslide susceptibility assessment using machine learning algorithms based on grid unit and slope unit
Three typical machine learning models, including random forest forest by penalizing attributes (FPA) and rotation forest were merged by random subspace algorithm. Twelve evaluation factors, including ...
TMCnet19d
Aptar Digital Health Announces Licensing Agreement With AstraZeneca to Develop AI-Powered Screening Algorithms
Aptar Digital Health aims to leverage the cutting-edge AI-driven screening algorithms developed by AstraZeneca to accelerate ... We are collaborating at scale to deliver sustainable solutions for ...
IEEE20d
On the Necessity of Using Supervised Machine Learning for Risk-based Screening of Distribution Transformers: An Industrial Case Study
It is necessary to carry out risk-based screening of DTs to classify them, in order to perform detailed RBI&MA. This manuscript demonstrates the use of a supervised machine learning approach for the ...
CEO22d
Combined Sewer Overflow (CSO) monitoring: Opportunities for artificial intelligence and machine learning
A combined sewer community can leverage the following from machine learning: Algorithm speed can provide a result in seconds compared to traditional models that may require hours or days. The speed of ...
Frontiers26d
Chinese validation of “subjective motoric cognitive risk syndrome” screening tool in patients with coronary artery disease using Rasch analysis
Overall, the scale has good validity and external reliability. The item-CVI indicates outstanding content validity. Our findings also support the discriminative validity of MCR-S in screening for ...
IEEE27d
Classification of Alzheimer's Disease Using RF Signals and Machine Learning
Machine learning algorithms can be applied to recorded S-parameters in order to classify the stage of Alzheimer's disease in the brain. •The research presented in this work targets research in ...