Results 171 to 180 of about 3,967 (264)

AWJ Cutting Process Quality Modeling and Optimization Based on Footprint Angle. [PDF]

Materials (Basel)
Perec A, Kawecka E, Zajac W.
europepmc   +1 more source

AI‐Driven Cancer Multi‐Omics: A Review From the Data Pipeline Perspective

Advanced Intelligent Discovery, EarlyView.
The exponential growth of cancer multi‐omics data brings opportunities and challenges for precision oncology. This review systematically examines AI's role in addressing these challenges, covering generative models, integration architectures, Explainable AI for clinical trust, clinical applications, and key directions for clinical translation.
Shilong Liu, Shunxiang Li, Kun Qian
wiley   +1 more source

Multi objective optimization of AWJM parameters for ZrO₂ coated MWCNTs reinforced HDPE nanocomposites using Taguchi Grey relational analysis. [PDF]

Sci Rep
Suhas K, Murthy BRN, Hiremath A, Hiremath P.   +3 more
europepmc   +1 more source

Autonomous X‐Ray Fluorescence Mapping for Nanoscale Chemical Speciation of Fine Particulate Matter

Advanced Intelligent Discovery, EarlyView.
We present X‐AutoMap, an autonomous X‐ray fluorescence mapping framework that integrates real‐time analysis with rule‐based computer vision to selectively target chemically relevant regions. By avoiding background‐dominated areas, the method reduces acquisition time by fourfold while enabling accurate particle‐level speciation.
Carlos Deleon, Dmitri Gavrilov, Peggy O’Day, Ajith Pattammattel   +3 more
wiley   +1 more source

Study on Water-Jet-Guided Laser-Ultrasonic Grinding Hybrid Processing Technology for SiC_f/SiC Composite Materials. [PDF]

Materials (Basel)
Yu G, Zhang D, Pei X, Yang F.
europepmc   +1 more source

AI‐BioMech: Deep Learning Prediction of Mechanical Behavior in Aperiodic Biological Cellular Materials

Advanced Intelligent Discovery, EarlyView.
AI‐BioMech is a deep learning framework that predicts the mechanical behavior of biological cellular materials directly from 2D images. By replacing traditional finite element analysis with semantic segmentation, it identifies stress and strain distributions with 99% accuracy, offering a high‐speed, scalable alternative for analyzing complex, aperiodic
Haleema Sadia, Marcelo A. Dias, Parvez Alam   +2 more
wiley   +1 more source

Research on Stress Variations During the 4H-SiC Indentation Process. [PDF]

Micromachines (Basel)
Wang W, Lin S, Yu Y, Duan N.
europepmc   +1 more source

Data‐Efficient Cycle‐Level Capacity Prediction Using 1D Deep Convolutional Network

Advanced Intelligent Discovery, EarlyView.
We introduce DeepBat, a deep learning framework featuring a 1D convolutional backbone designed to extract latent degradation patterns from a microstructurally diverse electrode dataset. By learning complex formulation–performance relationships, the model accurately predicts long‐term specific discharge capacity using limited early‐cycle data, providing
Tao Huang, Bing Sun, Zhigang Chen, Chenyu Zhao, Eugene Bakker, Yaojie Lei, Lingfei Zhao, Shijian Wang, Chao Liu, Virginia Xiaojun He, Bahram Shirzadi, Hao Liu, Xin Xi, Ruiliu Liu, Dongqing Wu, Guodong Long, Guoxiu Wang   +16 more
wiley   +1 more source

Smart Denture with Embedded Thin‐Film Temperature Sensors Patterned by Femtosecond Laser Pulse for Elderly Healthcare

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
We demonstrate the direct‐laser patterning of a gold thin film on polymethyl methacrylate to fabricate a temperature sensor for dentures. The temperature sensor‐embedded smart dentures are evaluated in an oral environment, enabling in‐situ monitoring for elderly healthcare.
Han Ku Nam, Yong Kwon Chae, Seoung‐Jin Hong, Younggen Lee, Dongwook Yang, Byunggi Kim, Sang Wook Kang, Young‐Jin Kim   +7 more
wiley   +1 more source

Three-Dimensional Cutting Force Model and Experimental Study of Diamond Bead Wire Saw Cutting of Loaded Coal. [PDF]

Materials (Basel)
Li S, Lv C, Qian Y, Yi M, Yang Y, Tang Z, Huang X, Zhao T.   +7 more
europepmc   +1 more source