Magnetic materials are in high demand. They're essential to the energy storage innovations on which electrification depends ...

Circuit Retrieval and Optimization with Parameter Guidance using LLMs” was published by researchers at Duke University and Synopsys. Abstract “Modern very large-scale integration (VLSI) design ...

Currently, PET scanner validation phantoms, methods, and acceptance criteria for clinical trials are not standardized. This situation generates substantial inefficiencies with many scanners being ...

To address the problems of low classification accuracy, redundancy of feature subsets, and performance susceptibility to parameters in wrapper-based feature selection in traditional Support Vector ...

Furthermore, we demonstrate that under the Kurdyka-Lojasiewicz inequality and certain conditions, the iterative sequence generated by our algorithm converges to a critical point of the problem. In ...

An autoregressive integrated moving average (ARIMA) model is a statistical analysis model that leverages time series data to forecast future trends.

Metaheuristic optimization algorithms are strongly present in the literature on discrete optimization. They typically 1) use stochastic operators, making each run unique, and 2) often have algorithmic ...

Machine learning uses algorithms to turn a data set into a model that can identify patterns or make predictions from new data. Which algorithm works best depends on the problem.