Results 151 to 160 of about 3,102 (223)

Toward Capacitive In‐Memory‐Computing: A Device to Systems Level Perspective on the Future of Artificial Intelligence Hardware

Advanced Intelligent Discovery, EarlyView.
Capacitive, charge‐domain compute‐in‐memory (CIM) stores weights as capacitance,eliminating DC sneak paths and IR‐drop, yielding near‐zero standbypower. In this perspective, we present a device to systems level performance analysis of most promising architectures and predict apathway for upscaling capacitive CIM for sustainable edge computing ...
Kapil Bhardwaj, Ella Paasio, Sayani Majumdar   +2 more
wiley   +1 more source

Association rule mining of clinical and biomarker data in neuroendocrine tumors: A prospective study on disease progression. [PDF]

J Neuroendocrinol
Knigge UP, Kjellman M, Grønbæk H, Thiis-Evensen E, Schalin-Jäntti C, Welin S, Sørbye H, Schneider MDP, Belusa R, Nordic NET Biomarker Group.   +9 more
europepmc   +1 more source

Advances in Thermal Modeling and Simulation of Lithium‐Ion Batteries with Machine Learning Approaches

Advanced Intelligent Discovery, EarlyView.
Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin, Kang Fu, Junjie Ding, Kai Sun, Peng Tan   +4 more
wiley   +1 more source

An Operational Status Assessment Model for SF₆ High-Voltage Circuit Breakers Based on IAR-BTR. [PDF]

Sensors (Basel)
Wang N, Wang Y, Zhang Y, Tang C, Sun C.
europepmc   +1 more source

Taguchi–Bayesian Sampling: A Roadmap for Polymer Database Construction Toward Small Representative Machine Learning

Advanced Intelligent Discovery, EarlyView.
This article establishes a Taguchi–Bayesian sampling strategy to reconstruct polymer processing–property landscape at minimal sampling cost, generically building the roadmap for materials database construction from sampling their vast design space. This sampling strategy is featured by an alternating lesson between uniformity and representativeness ...
Han Liu, Liantang Li
wiley   +1 more source

Understanding the ancient classic and famous prescriptions <i>via</i> the property of Chinese materia medica. [PDF]

Front Pharmacol
Qin D, Zhang H, Du B, Wang H, Liu L, Wang Y.   +5 more
europepmc   +1 more source

FIRE‐GNN: Force‐Informed, Relaxed Equivariance Graph Neural Network for Rapid and Accurate Prediction of Surface Properties

Advanced Intelligent Discovery, EarlyView.
This study introduces FIRE‐GNN, a force‐informed, relaxed equivariant graph neural network for predicting surface work functions and cleavage energies from slab structures. By incorporating surface‐normal symmetry breaking and machine learning interatomic potential‐derived force information, the approach achieves state‐of‐the‐art accuracy and enables ...
Circe Hsu, Claire Schlesinger, Karan Mudaliar, Jordan Leung, Robin Walters, Peter Schindler   +5 more
wiley   +1 more source

Hidden in the Pangenome? Machine Learning-Driven Discovery of Antimicrobial Potential in <i>Corynebacterium glutamicum</i>. [PDF]

Bioinform Biol Insights
Islam SI, Shahed K, Parvin MM, Sanjida S.   +3 more
europepmc   +1 more source

Sampling Strategy: An Overlooked Factor Affecting Artificial Intelligence Prediction Accuracy of Peptides’ Physicochemical Properties

Advanced Intelligent Discovery, EarlyView.
This study reveals that sampling strategy (i.e., sampling size and approach) is a foundational prerequisite for building accurate and generalizable AI models in peptide discovery. Reaching a threshold of 7.5% of the total tetrapeptide sequence space was essential to ensure reliable predictions.
Meiru Yan, Ankeer Abuduhebaier, Haojin Zhou, Jiaqi Wang   +3 more
wiley   +1 more source

Finding the needle in the haystack-An interpretable sequential pattern mining method for classification problems. [PDF]

Front Big Data
Grote A, Hariharan A, Weinhardt C.
europepmc   +1 more source