Results 141 to 150 of about 145,710 (264)

Ultralow‐Power Real‐Time On‐Chip Thermal Prediction via Finite Element Method–Machine Learning Codesign and Field‐Programmable Gate Array Deployment

Advanced Intelligent Systems, EarlyView.
A lightweight machine learning (ML)‐based thermal prediction framework is demonstrated and implemented on a field‐programmable gate array (FPGA). Using measured temperature data from a real chiplet, the approach enables real‐time, die‐level heat‐map inference with low power consumption, validating practical on‐chip thermal monitoring for advanced ...
Jun Ho Lee, Jae Gyu Kim, Sung Jin Kim, Jae Yong Song, Byoung Don Kong   +4 more
wiley   +1 more source

Multiplexed Tandem Mass Spectrometry Imaging Enables Large‐Scale Isomer Mapping and Annotation in Tissues

Angewandte Chemie, EarlyView.
Parallel mass spectrometry imaging acquires high mass resolution and tandem mass spectrometry images from 108 isolation windows in a single run. Spatial similarity networking clusters product ions by spatial distribution, enabling annotation of isomers and isobars as demonstrated for phospholipids and oxidized cholesterol in mouse and human brain ...
Varun V. Sharma, Gabor Toth, Robert Martinis, Cathrin E. Hansen, Gijs Kooij, Ingela Lanekoff   +5 more
wiley   +2 more sources

Bayesian-optimized GRU network modeling for thermal error compensation in gantry guideway grinder spindle. [PDF]

Sci Rep
Zhu S, Deng J, Chen H, Nan P, Ye Y, Shi Q.   +5 more
europepmc   +1 more source

GraphNeuralCloth: A Graph‐Neural‐Network‐Based Framework for Non‐Skinning Cloth Simulation

Advanced Intelligent Systems, EarlyView.
This study presents a cloth motion capture system and a point‐cloud‐to‐mesh processing method to support the prediction of real‐world fabric deformation. GraphNeuralCloth, a graph neural‐network (GNN)‐based framework is also proposed to estimate the cloth morphology change in real time.
Yingqi Li, Xiaomei Wang, Xiaoqi Song, Chenchen Fan, Bohao Zhu, Jianan Peng, Qixin Liang, James Lam, Kam‐Yim Sze, Ka‐Wai Kwok   +9 more
wiley   +1 more source

Machine Learning-Enhanced Quantitative Structure-Activity Relationship Modeling for DNA Polymerase Inhibitor Discovery: Algorithm Development and Validation. [PDF]

JMIR AI
Kakraba S, Ayyadevara S, Yadem Clement A, Abraham KE, Compadre CM, Shmookler Reis RJ.   +5 more
europepmc   +1 more source

Slip‐Adaptive Neural Control of Gecko‐Inspired Adhesive Robots

Advanced Intelligent Systems, EarlyView.
This study introduces a neural adhesion controller to improve the stability of gecko‐inspired climbing robots. By integrating an echo state network and a multilayer perceptron, the system utilizes joint torque feedback to accurately estimate adhesion in both normal and shear directions and predict slips. This enables effective recovery from slip events,
Donghao Shao, Jian Chen, Guangyuan Zang, Yang Li   +3 more
wiley   +1 more source

A robust methodology for finite population mean estimation based on Generalized M estimation. [PDF]

Sci Rep
Abuhasel KA.
europepmc   +1 more source

KDLM: Lightweight Brain Tumor Segmentation via Knowledge Distillation

Advanced Intelligent Systems, EarlyView.
A lightweight student network is designed, which is based on multiscale and multilevel feature fusion and combined with the residual channel attention mechanism to achieve efficient feature extraction and fusion with very few parameters. A dual‐teacher collaborative knowledge distillation framework is proposed.
Baotian Li, Haoyu Tang, Jun Zhu, Fang Fang Gou, Jia Wu   +4 more
wiley   +1 more source

Deep learning-based automated positioning system for maxillary skeletal expander: development and clinical validation. [PDF]

Clin Oral Investig
Pan J, Liu Z, Liu Y, Zhang Y, Xu M, Li X, Chen X, Wei G, Liu D.   +8 more
europepmc   +1 more source

Artificial Intelligence for Multiscale Modeling in Solid‐State Physics and Chemistry: A Comprehensive Review

Advanced Intelligent Systems, EarlyView.
This review explores the transformative impact of artificial intelligence on multiscale modeling in materials research. It highlights advancements such as machine learning force fields and graph neural networks, which enhance predictive capabilities while reducing computational costs in various applications.
Artem Maevskiy, Vitalii Kapitan, Andrey Ustyuzhanin   +2 more
wiley   +1 more source